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1. Creating a Discipline-specific Commons for Infectious Disease Epidemiology

Author: Wagner, Michael M., Hogan, William, Levander, John, Darr, Adam, Diller, Matt, Sibilla, Max, Sperringer, Jr., Alexander T. Loiacono. Terence, and Brown, Shawn T.
Subjects: Computer Science - Software Engineering, Computer Science - Artificial Intelligence
Abstract: Objective: To create a commons for infectious disease (ID) epidemiology in which epidemiologists, public health officers, data producers, and software developers can not only share data and software, but receive assistance in improving their interoperability. Materials and Methods: We represented 586 datasets, 54 software, and 24 data formats in OWL 2 and then used logical queries to infer potentially interoperable combinations of software and datasets, as well as statistics about the FAIRness of the collection. We represented the objects in DATS 2.2 and a software metadata schema of our own design. We used these representations as the basis for the Content, Search, FAIR-o-meter, and Workflow pages that constitute the MIDAS Digital Commons. Results: Interoperability was limited by lack of standardization of input and output formats of software. When formats existed, they were human-readable specifications (22/24; 92%); only 3 formats (13%) had machine-readable specifications. Nevertheless, logical search of a triple store based on named data formats was able to identify scores of potentially interoperable combinations of software and datasets. Discussion: We improved the findability and availability of a sample of software and datasets and developed metrics for assessing interoperability. The barriers to interoperability included poor documentation of software input/output formats and little attention to standardization of most types of data in this field. Conclusion: Centralizing and formalizing the representation of digital objects within a commons promotes FAIRness, enables its measurement over time and the identification of potentially interoperable combinations of data and software., Comment: 12 pages, 6 figures
Published: 2023

2. brainlife.io: a decentralized and open-source cloud platform to support neuroscience research

Author: Hayashi, Soichi, Caron, Bradley A., Heinsfeld, Anibal Sólon, Vinci-Booher, Sophia, McPherson, Brent, Bullock, Daniel N., Bertò, Giulia, Niso, Guiomar, Hanekamp, Sandra, Levitas, Daniel, Ray, Kimberly, MacKenzie, Anne, Avesani, Paolo, Kitchell, Lindsey, Leong, Josiah K., Nascimento-Silva, Filipi, Koudoro, Serge, Willis, Hanna, Jolly, Jasleen K., Pisner, Derek, Zuidema, Taylor R., Kurzawski, Jan W., Mikellidou, Kyriaki, Bussalb, Aurore, Chaumon, Maximilien, George, Nathalie, Rorden, Christopher, Victory, Conner, Bhatia, Dheeraj, Aydogan, Dogu Baran, Yeh, Fang-Cheng F., Delogu, Franco, Guaje, Javier, Veraart, Jelle, Fischer, Jeremy, Faskowitz, Joshua, Fabrega, Ricardo, Hunt, David, McKee, Shawn, Brown, Shawn T., Heyman, Stephanie, Iacovella, Vittorio, Mejia, Amanda F., Marinazzo, Daniele, Craddock, R. Cameron, Olivetti, Emanuale, Hanson, Jamie L., Garyfallidis, Eleftherios, Stanzione, Dan, Carson, James, Henschel, Robert, Hancock, David Y., Stewart, Craig A., Schnyer, David, Eke, Damian O., Poldrack, Russell A., Bollmann, Steffen, Stewart, Ashley, Bridge, Holly, Sani, Ilaria, Freiwald, Winrich A., Puce, Aina, Port, Nicholas L., and Pestilli, Franco
Published: 2024
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3. brainlife.io: A decentralized and open source cloud platform to support neuroscience research

Author: Hayashi, Soichi, Caron, Bradley A., Heinsfeld, Anibal Sólon, Vinci-Booher, Sophia, McPherson, Brent, Bullock, Daniel N., Bertò, Giulia, Niso, Guiomar, Hanekamp, Sandra, Levitas, Daniel, Ray, Kimberly, MacKenzie, Anne, Kitchell, Lindsey, Leong, Josiah K., Nascimento-Silva, Filipi, Koudoro, Serge, Willis, Hanna, Jolly, Jasleen K., Pisner, Derek, Zuidema, Taylor R., Kurzawski, Jan W., Mikellidou, Kyriaki, Bussalb, Aurore, Rorden, Christopher, Victory, Conner, Bhatia, Dheeraj, Aydogan, Dogu Baran, Yeh, Fang-Cheng F., Delogu, Franco, Guaje, Javier, Veraart, Jelle, Bollman, Steffen, Stewart, Ashley, Fischer, Jeremy, Faskowitz, Joshua, Chaumon, Maximilien, Fabrega, Ricardo, Hunt, David, McKee, Shawn, Brown, Shawn T., Heyman, Stephanie, Iacovella, Vittorio, Mejia, Amanda F., Marinazzo, Daniele, Craddock, R. Cameron, Olivetti, Emanuele, Hanson, Jamie L., Avesani, Paolo, Garyfallidis, Eleftherios, Stanzione, Dan, Carson, James, Henschel, Robert, Hancock, David Y., Stewart, Craig A., Schnyer, David, Eke, Damian O., Poldrack, Russell A., George, Nathalie, Bridge, Holly, Sani, Ilaria, Freiwald, Winrich A., Puce, Aina, Port, Nicholas L., and Pestilli, Franco
Subjects: Computer Science - Distributed, Parallel, and Cluster Computing, Quantitative Biology - Neurons and Cognition, Quantitative Biology - Quantitative Methods
Abstract: Neuroscience research has expanded dramatically over the past 30 years by advancing standardization and tool development to support rigor and transparency. Consequently, the complexity of the data pipeline has also increased, hindering access to FAIR (Findable, Accessible, Interoperabile, and Reusable) data analysis to portions of the worldwide research community. brainlife.io was developed to reduce these burdens and democratize modern neuroscience research across institutions and career levels. Using community software and hardware infrastructure, the platform provides open-source data standardization, management, visualization, and processing and simplifies the data pipeline. brainlife.io automatically tracks the provenance history of thousands of data objects, supporting simplicity, efficiency, and transparency in neuroscience research. Here brainlife.io's technology and data services are described and evaluated for validity, reliability, reproducibility, replicability, and scientific utility. Using data from 4 modalities and 3,200 participants, we demonstrate that brainlife.io's services produce outputs that adhere to best practices in modern neuroscience research.
Published: 2023
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4. Author Correction: brainlife.io: a decentralized and open-source cloud platform to support neuroscience research

Author: Hayashi, Soichi, Caron, Bradley A., Heinsfeld, Anibal Sólon, Vinci-Booher, Sophia, McPherson, Brent, Bullock, Daniel N., Bertò, Giulia, Niso, Guiomar, Hanekamp, Sandra, Levitas, Daniel, Ray, Kimberly, MacKenzie, Anne, Avesani, Paolo, Kitchell, Lindsey, Leong, Josiah K., Nascimento-Silva, Filipi, Koudoro, Serge, Willis, Hanna, Jolly, Jasleen K., Pisner, Derek, Zuidema, Taylor R., Kurzawski, Jan W., Mikellidou, Kyriaki, Bussalb, Aurore, Chaumon, Maximilien, George, Nathalie, Rorden, Christopher, Victory, Conner, Bhatia, Dheeraj, Aydogan, Dogu Baran, Yeh, Fang-Cheng F., Delogu, Franco, Guaje, Javier, Veraart, Jelle, Fischer, Jeremy, Faskowitz, Joshua, Fabrega, Ricardo, Hunt, David, McKee, Shawn, Brown, Shawn T., Heyman, Stephanie, Iacovella, Vittorio, Mejia, Amanda F., Marinazzo, Daniele, Craddock, R. Cameron, Olivetti, Emanuale, Hanson, Jamie L., Garyfallidis, Eleftherios, Stanzione, Dan, Carson, James, Henschel, Robert, Hancock, David Y., Stewart, Craig A., Schnyer, David, Eke, Damian O., Poldrack, Russell A., Bollmann, Steffen, Stewart, Ashley, Bridge, Holly, Sani, Ilaria, Freiwald, Winrich A., Puce, Aina, Port, Nicholas L., and Pestilli, Franco
Published: 2024
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5. Data and Tools Integration in the Canadian Open Neuroscience Platform

Author: Poline, Jean-Baptiste, Das, Samir, Glatard, Tristan, Madjar, Cécile, Dickie, Erin W., Lecours, Xavier, Beaudry, Thomas, Beck, Natacha, Behan, Brendan, Brown, Shawn T., Bujold, David, Beauvais, Michael, Caron, Bryan, Czech, Candice, Dharsee, Moyez, Dugré, Mathieu, Evans, Ken, Gee, Tom, Ippoliti, Giulia, Kiar, Gregory, Knoppers, Bartha Maria, Kuehn, Tristan, Le, Diana, Lo, Derek, Mazaheri, Mandana, MacFarlane, Dave, Muja, Naser, O’Brien, Emmet A., O’Callaghan, Liam, Paiva, Santiago, Park, Patrick, Quesnel, Darcy, Rabelais, Henri, Rioux, Pierre, Legault, Mélanie, Tremblay-Mercier, Jennifer, Rotenberg, David, Stone, Jessica, Strauss, Ted, Zaytseva, Ksenia, Zhou, Joey, Duchesne, Simon, Khan, Ali R., Hill, Sean, and Evans, Alan C.
Published: 2023
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6. Early trajectories of virological and immunological biomarkers and clinical outcomes in patients admitted to hospital for COVID-19: an international, prospective cohort study

Author: Sahner, David, Tierney, John, Vogel, Susan E., Herpin, Betsey R., Smolskis, Mary C., McKay, Laura A., Cahill, Kelly, Crew, Page, Sardana, Ratna, Raim, Sharon Segal, Hensely, Lisa, Lorenzo, Johsua, Mock, Rebecca, Zuckerman, Judith, Atri, Negin, Miller, Mark, Vallee, David, Chung, Lucy, Kang, Nayon, Barrett, Kevin, Adam, Stacey J., Read, Sarah, Draghia-Akli, Ruxandra, Currier, Judy, Hughes, Eric, Harrigan, Rachel H., Amos, Laura, Carlsen, Amy, Carter, Anita, Collins, Gary, Davis, Bionca, Denning, Eileen, DuChene, Alain, Eckroth, Kate, Engen, Nicole, Frase, Alex, Gandits, Greg, Grund, Birgit, Harrison, Merrie, Hurlbut, Nancy, Kaiser, Payton, Koopmeiners, Joseph, Larson, Gregg, Meger, Sue, Mistry, Shweta Sharma, Murray, Thomas, Nelson, Ray, Quan, Kien, Quan, Siu Fun, Reilly, Cavan, Siegel, Lianne, Thompson, Greg, Vock, David, Walski, Jamie, Gelijns, Annetine C., Moskowitz, Alan J., Bagiella, Emilia, Moquete, Ellen, O'Sullivan, Karen, Marks, Mary E., Accardi, Evan, Kinzel, Emily, Burris, Sarah, Bedoya, Gabriela, Gupta, Lola, Overbey, Jessica R., Santos, Milerva, Gillinov, Marc A., Miller, Marissa A., Taddei-Peters, Wendy C., Fenton, Kathleen, Sandkovsky, Uriel, Gottlieb, Robert L., Mack, Michael, Berhe, Mezgebe, Haley, Clinton, Dishner, Emma, Bettacchi, Christopher, Golden, Kevin, Duhaime, Erin, Ryan, Madison, Tallmadge, Catherine, Estrada, Lorie, Jones, Felecia, Villa, Samatha, Wang, Samatha, Robert, Raven, Coleman, Tanquinisha, Clariday, Laura, Baker, Rebecca, Hurutado-Rodriguez, Mariana, Iram, Nazia, Fresnedo, Michelle, Davis, Allyson, Leonard, Kiara, Ramierez, Noelia, Thammavong, Jon, Duque, Krizia, Turner, Emma, Fisher, Tammy, Robinson, Dianna, Ransom, Desirae, Maldonado, Nicholas, Lusk, Erica, Killian, Aaron, Palacious, Adriana, Solis, Edilia, Jerrow, Janet, Watts, Matthew, Whitacre, Heather, Cothran, Elizabeth, Smith, Peter K., Barkauskas, Christina E., Vekstein, Andrew M., Ko, Emily R., Dreyer, Grace R., Stafford, Neil, Brooks, Megan, Der, Tatyana, Witte, Marie, Gamarallage, Ruwan, Franzone, John, Ivey, Noel, Lumsden, Rebecca H., Mosaly, Nilima, Mourad, Ahmaad, Holland, Thomas L., Motta, Mary, Lane, Kathleen, McGowan, Lauren M., Stout, Jennifer, Aloor, Heather, Bragg, Kennesha M., Toledo, Barvina, McLendon-Arvik, Beth, Bussadori, Barbara, Hollister, Beth A., Griffin, Michelle, Giangiacomo, Dana M., Rodriguez, Vicente, Bokhart, Gordon, Eichman, Sharon M., Parrino, Patrick E., Spindel, Stephen, Bansal, Aditya, Baumgarten, Katherine, Hand, Johnathan, Vonderhaar, Derek, Nossaman, Bobby, Sylvia Laudun, Ames, DeAnna, Broussard, Shane, Hernandez, Nilmo, Isaac, Geralyn, Dinh, Huan, Zheng, Yiling, Tran, Sonny, McDaniel, Hunter, Crovetto, Nicolle, Perin, Emerson, Costello, Briana, Manian, Prasad, Sohail, M. Rizwan, Postalian, Alexander, Hinsu, Punit, Watson, Carolyn, Chen, James, Fink, Melyssa, Sturgis, Lydia, Walker, Kim, Mahon, Kim, Parenti, Jennifer, Kappenman, Casey, Knight, Aryn, Sturek, Jeffrey M., Barros, Andrew, Enfield, Kyle B., Kadl, Alexandra, Green, China J., Simon, Rachel M., Fox, Ashley, Thornton, Kara, Adams, Amy, Badhwar, Vinay, Sharma, Sunil, Peppers, Briana, McCarthy, Paul, Krupica, Troy, Sarwari, Arif, Reece, Rebecca, Fornaresico, Lisa, Glaze, Chad, Evans, Raquel, Di, Fang, Carlson, Shawn, Aucremanne, Tanja, Tennant, Connie, Sutton, Lisa Giblin, Buterbaugh, Sabrina, Williams, Roger, Bunner, Robin, Traverse, Jay H., Rhame, Frank, Huelster, Joshua, Kethireddy, Rajesh, Davies, Irena, Salamanca, Julianne, Majeski, Christine, Skelton, Paige, Zarambo, Maria, Sarafolean, Andrea, Bowdish, Michael E., Borok, Zea, Wald-Dickler, Noah, Hutcheon, Douglass, Towfighi, Amytis, Lee, Mary, Lewis, Meghan R., Spellberg, Brad, Sher, Linda, Sharma, Aniket, Olds, Anna P., Justino, Chris, Loxano, Edward, Romero, Chris, Leong, Janet, Rodina, Valentina, Quesada, Christine, Hamilton, Luke, Escobar, Jose, Leshnower, Brad, Bender, William, Sharifpour, Milad, Miller, Jeffrey, Farrington, Woodrow, Baio, Kim T., McBride, Mary, Fielding, Michele, Mathewson, Sonya, Porte, Kristina, Maton, Missy, Ponder, Chari, Haley, Elisabeth, Spainhour, Christine, Rogers, Susan, Tyler, Derrick, Madathil, Ronson J., Rabin, Joseph, Levine, Andrea, Saharia, Kapil, Tabatabai, Ali, Lau, Christine, Gammie, James S., Peguero, Maya-Loren, McKernan, Kimberly, Audette, Mathew, Fleischmann, Emily, Akbari, Kreshta, Lee, Myounghee, Chi, Andrew, Salehi, Hanna, Pariser, Alan, Nyguyen, Phuong Tran, Moore, Jessica, Gee, Adrienne, Vincent, Shelika, Zuckerman, Richard A., Iribarne, Alexander, Metzler, Sara, Shipman, Samantha, Johnson, Haley, Newton, Crystallee, Parr, Doug, Miller, Leslie, Schelle, Beth, McLean, Sherry, Rothbaum, Howard R., Alvarez, Michael S., Kalan, Shivam P., Germann, Heather H., Hendershot, Jennifer, Moroney, Karen, Herring, Karen, Cook, Sharri, Paul, Pam, Walker-Ignasiak, Rebecca, North, Crystal, Oldmixon, Cathryn, Ringwood, Nancy, Muzikansky, Ariela, Morse, Richard, Fitzgerald, Laura, Morin, Haley D., Brower, Roy G., Reineck, Lora A., Bienstock, Karen, Steingrub, Jay H., Hou, Peter K., Steingrub, Jay S., Tidswell, Mark A., Kozikowski, Lori-Ann, Kardos, Cynthia, DeSouza, Leslie, Romain, Sarah, Thornton-Thompson, Sherell, Talmor, Daniel, Shapiro, Nathan, Andromidas, Konstantinos, Banner-Goodspeed, Valerie, Bolstad, Michael, Boyle, Katherine L., Cabrera, Payton, deVilla, Arnaldo, Ellis, Joshua C., Grafals, Ana, Hayes, Sharon, Higgins, Conor, Kurt, Lisa, Kurtzman, Nicholas, Redman, Kimberly, Rosseto, Elinita, Scaffidi, Douglas, Filbin, Michael R., Hibbert, Kathryn A., Parry, Blair, Margolin, Justin, Hillis, Brooklynn, Hamer, Rhonda, Brait, Kelsey, Beakes, Caroline, McKaig, Brenna, Kugener, Eleonore, Jones, Alan E., Galbraith, James, Nandi, Utsav, Peacock, Rebekah, Hendey, Gregory, Kangelaris, Kirsten, Ashktorab, Kimia, Gropper, Rachel, Agrawal, Anika, Yee, Kimberley J., Jauregui, Alejandra E., Zhuo, Hanjing, Almasri, Eyad, Fayed, Mohamed, Hubel, Kinsley A., Hughes, Alyssa R., Garcia, Rebekah L., Lim, George W., Chang, Steven Y., Lin, Michael Y., Vargas, Julia, Sihota, Hena, Beutler, Rebecca, Agarwal, Trisha, Wilson, Jennifer G., Vojnik, Rosemary, Perez, Cynthia, McDowell, Jordan H., Roque, Jonasel, Wang, Henry, Huebinger, Ryan M., Patel, Bela, Vidales, Elizabeth, Albertson, Timothy, Hardy, Erin, Harper, Richart, Moss, Marc A., Baduashvili, Amiran, Chauhan, Lakshmi, Douin, David J., Martinez, Flora, Finck, Lani L., Bastman, Jill, Howell, Michelle, Higgins, Carrie, McKeehan, Jeffrey, Finigan, Jay, Stubenrauch, Peter, Janssen, William J., Griesmer, Christine, VerBurg, Olivia, Hyzy, Robert C., Park, Pauline K., Nelson, Kristine, McSparron, Jake I., Co, Ivan N., Wang, Bonnie R., Jimenez, Jose, Olbrich, Norman, McDonough, Kelli, Jia, Shijing, Hanna, Sinan, Gong, Michelle N., Richardson, Lynne D., Nair, Rahul, Lopez, Brenda, Amosu, Omowunmi, Offor, Obiageli, Tzehaie, Hiwet, Nkemdirim, William, Boujid, Sabah, Mosier, Jarrod M., Hypes, Cameron, Campbell, Elizabeth Salvagio, Bixby, Billie, Gilson, Boris, Lopez, Anitza, Bime, Christian, Parthasarathy, Sairam, Cano, Ariana M., Hite, R. Duncan, Terndrup, Thomas E., Wiedemann, Herbert P., Hudock, Kristin, Tanzeem, Hammad, More, Harshada, Martinkovic, Jamie, Sellers, Susan, Houston, Judy, Burns, Mary, Kiran, Simra, Roads, Tammy, Kennedy, Sarah, Duggal, Abhijit, Thiruchelvam, Nirosshan, Ashok, Kiran, King, Alexander H., Mehkri, Omar, Dugar, Siddharth, Sahoo, Debasis, Yealy, Donald M., Angus, Derek C., Weissman, Alexandra J., Vita, Tina M., Berryman, Emily, Hough, Catherine L., Khan, Akram, Krol, Olivia F., Mills, Emmanuel, Kinjal, Mistry, Briceno, Genesis, Reddy, Raju, Hubel, Kinsley, Jouzestani, Milad K., McDougal, Madeline, Deshmukh, Rupali, Johnston, Nicholas J., Robinson, Bryce H., Gundel, Staphanie J., Katsandres, Sarah C., Chen, Peter, Torbati, Sam S., Parimon, Tanyalak, Caudill, Antonina, Mattison, Brittany, Jackman, Susan E., Chen, Po-En, Bayoumi, Emad, Ojukwu, Cristabelle, Fine, Devin, Weissberg, Gwendolyn, Isip, Katherine, Choi-Kuaea, Yunhee, Mehdikhani, Shaunt, Dar, Tahir B., Fleury Augustin, Nsole Biteghe, Tran, Dana, Dukov, Jennifer Emilow, Matusov, Yuri, Choe, June, Hindoyan, Niree A., Wynter, Timothy, Pascual, Ethan, Clapham, Gregg J., Herrera, Lisa, Caudill, Antonia, O’Mahony, D. Shane, Nyatsatsang, Sonam T., Wilson, David M., Wallick, Julie A., Duven, Alexandria M., Fletcher, Dakota D., Miller, Chadwick, Files, D. Clark, Gibbs, Kevin W., Flores, Lori S., LaRose, Mary E., Landreth, Leigha D., Palacios, D. Rafael, Parks, Lisa, Hicks, Madeline, Goodwin, Andrew J., Kilb, Edward F., Lematty, Caitlan T., Patti, Kerilyn, Grady, Abigail, Rasberry, April, Morris, Peter E., Sturgill, Jamie L., Cassity, Evan P., Dhar, Sanjay, Montgomery-Yates, Ashley A., Pasha, Sarah N., Mayer, Kirby P., Pharm.D., Brittany Bissel, Trott, Terren, Rehman, Shahnaz, de Wit, Marjolein, Mason, Jessica, Bledsoe, Joseph, Knowlton, Kirk U., Brown, Samuel, Lanspa, Michael, Leither, Lindsey, Pelton, Ithan, Armbruster, Brent P., Montgomery, Quinn, Kumar, Naresh, Fergus, Melissa, Imel, Karah, Palmer, Ghazal, Webb, Brandon, Klippel, Carolyn, Jensen, Hannah, Duckworth, Sarah, Gray, Andrew, Burke, Tyler, Knox, Dan, Lumpkin, Jenna, Aston, Valerie T., Applegate, Darrin, Serezlic, Erna, Brown, Katie, Merril, Mardee, Harris, Estelle S., Middleton, Elizabeth A., Barrios, Macy A.G., Greer, Jorden, Schmidt, Amber D., Webb, Melissa K., Paine, Roert, Callahan, Sean J., Waddoups, Lindsey J., Yamane, Misty B., Self, Wesley H., Rice, Todd W., Casey, Jonathan D., Johnson, Jakea, Gray, Christopher, Hays, Margaret, Roth, Megan, Menon, Vidya, Kasubhai, Moiz, Pillai, Anjana, Daniel, Jean, Sittler, Daniel, Kanna, Balavenkatesh, Jilani, Nargis, Amaro, Francisco, Santana, Jessica, Lyakovestsky, Aleksandr, Madhoun, Issa, Desroches, Louis Marie, Amadon, Nicole, Bahr, Alaa, Ezzat, Imaan, Guerrero, Maryanne, Padilla, Joane, Fullmer, Jessie, Singh, Inderpreet, Ali Shah, Syed Hamad, Narang, Rajeev, Mock, Polly, Shadle, Melissa, Hernandez, Brenda, Welch, Kevin, Payne, Andrea, Ertl, Gabriela, Canario, Daniel, Barrientos, Isabel, Goss, Danielle, DeVries, Mattie, Folowosele, Ibidolapo, Garner, Dorothy, Gomez, Mariana, Price, Justin, Bansal, Ekta, Wong, Jim, Faulhaber, Jason, Fazili, Tasaduq, Yeary, Brian, Ndolo, Ruth, Bryant, Christina, Smigeil, Bridgette, Robinson, Philip, Najjar, Rana, Jones, Patrice, Nguyen, Julie, Chin, Christina, Taha, Hassan, Najm, Salah, Smith, Christopher, Moore, Jason, Nassar, Talal, Gallinger, Nick, Christian, Amy, Mauer, D’Amber, Phipps, Ashley, Waters, Michael, Zepeda, Karla, Coslet, Jordan, Landazuri, Rosalynn, Pineda, Jacob, Uribe, Nicole, Garcia, Jose Ruiz, Barbabosa, Cecilia, Sandler, Kaitlyn, Overcash, J. Scott, Marquez, Adrienna, Chu, Hanh, Lee, Kia, Quillin, Kimberly, Garcia, Andrea, Lew, Pauline, Rogers, Ralph, Shehadeh, Fadi, Mylona, Evangelia K., Kaczynski, Matthew, Tran, Quynh-Lam, Benitez, Gregorio, Mishra, Biswajit, Felix, Lewis Oscar, Vafea, Maria Tsikala, Atalla, Eleftheria, Davies, Robin, Hedili, Salma, Monkeberg, Maria Andrea, Tabler, Sandra, Harrington, Britt, Meegada, Sreenath, Koripalli, Venkata Sandeep, Muddana, Prithvi, Jain, Lakshay, Undavalli, Chaitanya, Kavya, Parasa, Ibiwoye, Mofoluwaso, Akilo, Hameed, Lovette, Bryce D., Wylie, Jamie-Crystal, Smith, Diana M., Poon, Kenneth, Eckardt, Paula, Heysu, Rubio-Gomez, Sundararaman, Nithya, Alaby, Doris, Sareli, Candice, Sánchez, Adriana, Popielski, Laura, Kambo, Amy, Viens, Kimberley, Turner, Melissa, Vjecha, Michael J., Weintrob, Amy, Brar, Indira, Markowitz, Norman, Pastor, Erika, Corpuz, Roweena, Alangaden, George, McKinnon, John, Ramesh, Mayur, Herc, Erica, Yared, Nicholas, Lanfranco, Odaliz Abreu, Rivers, Emanuel, Swiderek, Jennifer, Gupta, Ariella Hodari, Pabla, Pardeep, Eliya, Sonia, Jazrawi, Jehan, Delor, Jeremy, Desai, Mona, Cook, Aaron, Jaehne, Anja Kathrina, Gill, Jasreen Kaur, Renaud, Sheri, Sarveswaran, Siva, Gardner, Edward, Scott, James, Bianchini, Monica, Melvin, Casey, Kim, Gina, Wyles, David, Kamis, Kevin, Miller, Rachel, Douglas, Ivor, Haukoos, Jason, Hicks, Carrie, Lazarte, Susana, Marines-Price, Rubria, Osuji, Alice, Agbor Agbor, Barbine Tchamba, Petersen, Tianna, Kamel, Dena, Hansen, Laura, Garcia, Angie, Cha, Christine, Mozaffari, Azadeh, Hernandez, Rosa, Cutrell, James, Kim, Mina, DellaValle, Natalie, Gonzales, Sonia, Somboonwit, Charurut, Oxner, Asa, Guerra, Lucy, Hayes, Michael, Nguyen, Thi, Tran, Thanh, Pinto, Avenette, Hatlen, Timothy, Anderson, Betty, Zepeda-Gutierrez, Ana, Martin, Dannae, Temblador, Cindi, Cuenca, Avon, Tanoviceanu, Roxanne, Prieto, Martha, Guerrero, Mario, Daar, Eric, Correa, Ramiro, Hartnell, Gabe, Wortmann, Glenn, Doshi, Saumil, Moriarty, Theresa, Gonzales, Melissa, Garman, Kristin, Baker, Jason V., Frosch, Anne, Goldsmith, Rachael, Driver, Brian, Frank, Christine, Leviton, Tzivia, Prekker, Matthew, Jibrell, Hodan, Lo, Melanie, Klaphake, Jonathan, Mackedanz, Shari, Ngo, Linh, Garcia-Myers, Kelly, Kunisaki, Ken M., Wendt, Chris, Melzer, Anne, Wetherbee, Erin, Drekonja, Dimitri, Pragman, Alexa, Hamel, Aimee, Thielen, Abbie, Hassler, Miranda, Walquist, Mary, Augenbraun, Michael, George, Jensen, Demeo, Lynette, Mishko, Motria, Thomas, Lorraine, Tatem, Luis, Dehovitz, Jack, Abassi, Mahsa, Leuck, Anne-Marie, Rao, Via, Pullen, Matthew, Luke, Darlette, LaBar, Derek, Christiansen, Theresa, Howard, Diondra, Biswas, Kousick, Harrington, Cristin, Garcia, Amanda, Bremer, Tammy, Burke, Tara, Koker, Brittany, Davis-Karim, Anne, Pittman, David, Vasudeva, Shikha S., Johnstone, Jaylynn R., Agnetti, Kate, Davis, Ruby, Trautner, Barbara, Hines-Munson, Casey, Van, John, Dillon, Laura, Wang, Yiqun, Nagy-Agren, Stephanie, Vasudeva, Shikha, Ochalek, Tracy, Caldwell, Erin, Humerickhouse, Edward, Boone, David, McGraw, William, Looney, David J., Mehta, Sanjay R., Johns, Scott Thompson, St. John, Melissa, Raceles, Jacqueline, Sear, Emily, Funk, Stephen, Cesarini, Rosa, Fang, Michelle, Nicalo, Keith, Drake, Wonder, Jones, Beatrice, Holtman, Teresa, Nguyen, Hien H., Maniar, Archana, Johnson, Eric A., Nguyen, Lam, Tran, Michelle T., Barrett, Thomas W., Johnston, Tera, Huggins, John T., Beiko, Tatsiana Y., Hughes, Heather Y., McManigle, William C., Tanner, Nichole T., Washburn, Ronald G., Ardelt, Magdalena, Tuohy, Patricia A., Mixson, Jennifer L., Hinton, Charles G., Thornley, Nicola, Allen, Heather, Elam, Shannon, Boatman, Barry, Baber, Brittany J., Ryant, Rudell, Roller, Brentin, Nguyen, Chinh, Mikail, Amani Morgan, Research, Marivic Hansen, Lichtenberger, Paola, Baracco, Gio, Ramos, Carol, Bjork, Lauren, Sueiro, Melyssa, Tien, Phyllis, Freasier, Heather, Buck, Theresa, Nekach, Hafida, Holodniy, Mark, Chary, Aarthi, Lu, Kan, Peters, Theresa, Lopez, Jessica, Tan, Susanna Yu, Lee, Robert H., Asghar, Aliya, Karyn Isip, Tasadduq Karim, Le, Katherine, Nguyen, Thao, Wong, Shinn, Raben, Dorthe, Murray, Daniel D., Jensen, Tomas O., Peters, Lars, Aagaard, Bitten, Nielsen, Charlotte B., Krapp, Katharina, Nykjær, Bente Rosdahl, Olsson, Christina, Kanne, Katja Lisa, Grevsen, Anne Louise, Joensen, Zillah Maria, Bruun, Tina, Bojesen, Ane, Woldbye, Frederik, Normand, Nick E., Esman, Frederik V.L., Benfield, Thomas, Clausen, Clara Lundetoft, Hovmand, Nichlas, Israelsen, Simone Bastrup, Iversen, Katrine, Leding, Caecilie, Pedersen, Karen Brorup, Thorlacius-Ussing, Louise, Tinggaard, Michaela, Tingsgard, Sandra, Krohn-Dehli, Louise, Pedersen, Dorthe, Villadsen, Signe, Staehr Jensen, Jens-Ulrik, Overgaard, Rikke, Rastoder, Ema, Heerfordt, Christian, Hedsund, Caroline, Ronn, Christian Phillip, Kamstrup, Peter Thobias, Hogsberg, Dorthe Sandbaek, Bergsoe, Christina, Søborg, Christian, Hissabu, Nuria M.S., Arp, Bodil C., Ostergaard, Lars, Staerke, Nina Breinholt, Yehdego, Yordanos, Sondergaard, Ane, Johansen, Isik S., Pedersen, Andreas Arnholdt, Knudtzen, Fredrikke C., Larsen, Lykke, Hertz, Mathias A., Fabricius, Thilde, Holden, Inge K., Lindvig, Susan O., Helleberg, Marie, Gerstoft, Jan, Kirk, Ole, Jensen, Tomas Ostergaard, Madsen, Birgitte Lindegaard, Pedersen, Thomas Ingemann, Harboe, Zitta Barrella, Roge, Birgit Thorup, Hansen, Thomas Michael, Glesner, Matilde Kanstrup, Lofberg, Sandra Valborg, Nielsen, Ariella Denize, Leicht von Huth, Sebastian, Nielsen, Henrik, Thisted, Rikke Krog, Petersen, Kristine Toft, Juhl, Maria Ruwald, Podlekareva, Daria, Johnsen, Stine, Andreassen, Helle Frost, Pedersen, Lars, Clara Ellinor Lindnér, Cecilia Ebba, Wiese, Lothar, Knudsen, Lene Surland, Skrøder Nytofte, Nikolaj Julian, Havmøller, Signe Ravn, Expósito, Maria, Badillo, José, Martínez, Ana, Abad, Elena, Chamorro, Ana, Figuerola, Ariadna, Mateu, Lourdes, España, Sergio, Lucero, Maria Constanza, Santos, José Ramón, Lladós, Gemma, Lopez, Cristina, Carabias, Lydia, Molina-Morant, Daniel, Loste, Cora, Bracke, Carmen, Siles, Adrian, Fernández-Cruz, Eduardo, Di Natale, Marisa, Padure, Sergiu, Gomez, Jimena, Ausin, Cristina, Cervilla, Eva, Balastegui, Héctor, Sainz, Carmen Rodríguez, Lopez, Paco, Carbone, Javier, Escobar, Mariam, Balerdi, Leire, Legarda, Almudena, Roldan, Montserrat, Letona, Laura, Muñoz, José, Camprubí, Daniel, Arribas, Jose R., Sánchez, Rocio Montejano, Díaz-Pollán, Beatriz, Stewart, Stefan Mark, Garcia, Irene, Borobia, Alberto, Mora-Rillo, Marta, Estrada, Vicente, Cabello, Noemi, Nuñez-Orantos, M.J., Sagastagoitia, I., Homen, J.R., Orviz, E., Montalvá, Adrián Sánchez, Espinosa-Pereiro, Juan, Bosch-Nicolau, Pau, Salvador, Fernando, Burgos, Joaquin, Morales-Rull, Jose Luis, Moreno Pena, Anna Maria, Acosta, Cristina, Solé-Felip, Cristina, Horcajada, Juan P., Sendra, Elena, Castañeda, Silvia, López-Montesinos, Inmaculada, Gómez-Junyent, Joan, Gonzáles, Carlota Gudiol, Cuervo, Guilermo, Pujol, Miquel, Carratalà, Jordi, Videla, Sebastià, Günthard, Huldrych, Braun, Dominique L., West, Emily, M’Rabeth-Bensalah, Khadija, Eichinger, Mareile L., Grüttner-Durmaz, Manuela, Grube, Christina, Zink, Veronika, pharmacist, Goes pharmacist, Josefine, Fätkenheuer, Gerd, Malin, Jakob J., Tsertsvadze, Tengiz, Abutidze, Akaki, Chkhartishvili, Nikoloz, Metchurtchlishvili, Revaz, Endeladze, Marina, Paciorek, Marcin, Bursa, Dominik, Krogulec, Dominika, Pulik, Piotr, Ignatowska, Anna, Horban, Andrzej, Bakowska, Elzbieta, Kowaska, Justyna, Bednarska, Agnieszka, Jurek, Natalia, Skrzat-Klapaczynska, Agata, Bienkowski, Carlo, Hackiewicz, Malgorzata, Makowiecki, Michal, Platowski, Antoni, Fishchuk, Roman, Kobrynska, Olena, Levandovska, Khrystyna, Kirieieva, Ivanna, Kuziuk, Mykhailo, Naucler, Pontus, Perlhamre, Emma, Mazouch, Lotta, Kelleher, Anthony, Polizzotto, Mark, Carey, Catherine, Chang, Christina C., Hough, Sally, Virachit, Sophie, Davidson, Sarah, Bice, Daniel J., Ognenovska, Katherine, Cabrera, Gesalit, Flynn, Ruth, Young, Barnaby E., Chia, Po Ying, Lee, Tau Hong, Lin, Ray J., Lye, David C., Ong, Sean W.X., Puah, Ser Hon, Yeo, Tsin Wen, Diong, Shiau Hui, Ongko, Juwinda, Yeo, He Ping, Eriobu, Nnakelu, Kwaghe, Vivian, Zaiyad, Habib, Idoko, Godwin, Uche, Blessing, Selvamuthu, Poongulali, Kumarasamy, Nagalingeswaran, Beulah, Faith Ester, Govindarajan, Narayan, Mariyappan, Kowsalya, Losso, Marcelo H., Abela, Cecilia, Moretto, Renzo, Belloc, Carlos G., Ludueña, Jael, Amar, Josefina, Toibaro, Javier, Macias, Laura Moreno, Fernandez, Lucia, Frare, Pablo S., Chaio, Sebastian R., Pachioli, Valeria, Timpano, Stella M., Sanchez, Marisa del Lujan, de Paz Sierra, Mariana, Stanek, Vanina, Belloso, Waldo, Cilenti, Flavia L., Valentini, Ricardo N., Stryjewski, Martin E., Locatelli, Nicolas, Soler Riera, Maria C., Salgado, Clara, Baeck, Ines M., Di Castelnuovo, Valentina, Zarza, Stella M., Hudson, Fleur, Parmar, Mahesh K.B., Goodman, Anna L., Dphil, Badrock, Jonathan, Gregory, Adam, Goodall, Katharine, Harris, Nicola, Wyncoll, James, Bhagani, S., Rodger, A., Luntiel, A., Patterson, C., Morales, J., Witele, E., Preston, A.-M., Nandani, A., Price, D.A., Hanrath, Aiden, Nell, Jeremy, Patel, Bijal, Hays, Carole, Jones, Geraldine, Davidson, Jade, Bawa, T., Mathews, M., Mazzella, A., Bisnauthsing, K., Aguilar-Jimenez, L., Borchini, F., Hammett, S., Touloumi, Giota, Pantazis, Nikos, Gioukari, Vicky, Souliou, Tania, Antoniadou, A., Protopapas, K., Kavatha, D., Grigoropoulou, S., Oikonomopoulo, C., Moschopoulos, C., Koulouris, N.G., Tzimopoulos, K., Koromilias, A., Argyraki, K., Lourida, P., Bakakos, P., Kalomenidis, I., Vlachakos, V., Barmparessou, Z., Balis, E., Zakynthinos, S., Sigala, I., Gianniou, N., Dima, E., Magkouta, S., Synolaki, E., Konstanta, S., Vlachou, M., Stathopoulou, P., Panagopoulos, P., Petrakis, V., Papazoglou, D., Tompaidou, E., Isaakidou, E., Poulakou, G., Rapti, V., Leontis, K., Nitsotolis, T., Athanasiou, K., Syrigos, K., Kyriakoulis, K., Trontzas, I., Arfara-Melanini, M., Kolonis, V., Kityo, Cissy, Mugerwa, Henry, Kiweewa, Francis, Kimuli, Ivan, Lukaakome, Joseph, Nsereko, Christoher, Lubega, Gloria, Kibirige, Moses, Nakahima, William, Wangi, Deus, Aguti, Evelyne, Generous, Lilian, Massa, Rosemary, Nalaki, Margaret, Magala, Felix, Nabaggala, Phiona Kaweesi, Kidega, Robert, Faith, Oryem Daizy, Florence, Apio, Emmanuel, Ocung, Beacham, Mugoonyi Paul, Geoffrey, Amone, Nakiboneka, Dridah, Apiyo, Paska, Kirenga, Bruce, Atukunda, Angella, Muttamba, Winters, Remmy, Kyeyume, Segawa, Ivan, Pheona, Nsubuga, Kigere, David, Mbabazi, Queen Lailah, Boersalino, Ledra, Nyakoolo, Grace, Fred, Aniongo, Alupo, Alice, Ebong, Doryn, Monday, Edson, Nalubwama, Ritah Norah, Kainja, Milton, Ambrose, Munu, Kwehayo, Vanon, Nalubega, Mary Grace, Ongoli, Augustine, Obbo, Stephen, Sebudde, Nicholus, Alaba, Jeniffer, Magombe, Geoffrey, Tino, Harriet, Obonya, Emmanuel, Lutaakome, Joseph, Kitonsa, Jonathan, Onyango, Martin, Naboth, Tukamwesiga, Naluyinda, Hadijah, Nanyunja, Regina, Irene, Muttiibwa, Jane, Biira, Wimfred, Kyobejja, Leonard, Ssemazzi, Deus, Tkiinomuhisha, Babra, Namasaba, Taire, Paul, Nabankema, Evelyn, Ogavu, Joseph, Mugerwa, Oscar, Okoth, Ivan, Mwebaze, Raymond, Mugabi, Timothy, Makhoba, Anthony, Arikiriza, Phiona, Theresa, Nabuuma, Nakayima, Hope, Frank, Kisuule, Ramgi, Patrícia, Pereira, Kássia, Osinusi, Anu, Cao, Huyen, Klekotka, Paul, Price, Karen, Nirula, Ajay, Osei, Suzette, Tipple, Craig, Wills, Angela, Peppercorn, Amanda, Watson, Helen, Gupta, Rajesh, Alexander, Elizabeth, Mogalian, Erik, Lin, Leo, Ding, Xiao, Margolis, David, Yan, Li, Girardet, Jean-Luc, Ma, Ji, Hong, Zhi, Zhu, Quing, Seegobin, Seth, Gibbs, Michael, Latchman, Mickel, Hasior, Katarzyna, Bouquet, Jerome, Wei, Jianxin, Streicher, Katie, Schmelzer, Albert, Brooks, Dennis, Butcher, Jonny, Tonev, Dimitar, Arbetter, Douglas, Damstetter, Philippe, Legenne, Philippe, Stumpp, Michael, Goncalves, Susana, Ramanathan, Krishnan, Chandra, Richa, Baseler, Beth, Teitelbaum, Marc, Schechner, Adam, Holley, H. Preston, Jankelevich, Shirley, Becker, Nancy, Dolney, Suzanne, Hissey, Debbie, Simpson, Shelly, Kim, Mi Ha, Beeler, Joy, Harmon, Liam, Asomah, Mabel, Jato, Yvonne, Stottlemyer, April, Tang, Olivia, Vanderpuye, Sharon, Yeon, Lindsey, Buehn, Molly, Eccard-Koons, Vanessa, Frary, Sadie, MacDonald, Leah, Cash, Jennifer, Hoopengardner, Lisa, Linton, Jessica, Schaffhauser, Marylu, Nelson, Michaela, Spinelli-Nadzam, Mary, Proffitt, Calvin, Lee, Christopher, Engel, Theresa, Fontaine, Laura, Osborne, C.K., Hohn, Matt, Galcik, Michael, Thompson, DeeDee, Kopka, Stacey, Shelley, Denise M., Mendez, Gregg, Brown, Shawn, Albert, Sara, Balde, Abby, Baracz, Michelle, Bielica, Mona, Billouin-Frazier, Shere, Choudary, Jay, Dixon, Mary, Eyler, Carolyn, Frye, Leanne, Gertz, Jensen, Giebeig, Lisa, Gulati, Neelam, Hankinson, Liz, Hogarty, Debi, Huber, Lynda, Krauss, Gary, Lake, Eileen, Manandhar, Meryan, Rudzinski, Erin, Sandrus, Jen, Suders, Connie, Natarajan, Ven, Rupert, Adam W., Baseler, Michael, Lynam, Danielle, Imamichi, Tom, Laverdure, Sylvain, McCormack, Ashley, Paudel, Sharada, Cook, Kyndal, Haupt, Kendra, Khan, Ayub, Hazen, Allison, Badralmaa, Yunden, Smith, Kenneth, Patel, Bhakti, Kubernac, Amanda, Kubernac, Robert, Hoover, Marie L., Solomon, Courtney, Rashid, Marium, Murphy, Joseph, Brown, Craig, DuChateau, Nadine, Ellis, Sadie, Flosi, Adam, Fox, Lisa, Johnson, Les, Nelson, Rich, Stojanovic, Jelena, Treagus, Amy, Wenner, Christine, Williams, Richard, Jensen, Tomas O, Murray, Thomas A, Grandits, Greg A, Jain, Mamta K, Shaw-Saliba, Kathryn, Matthay, Michael A, Baker, Jason V, Dewar, Robin L, Goodman, Anna L, Hatlen, Timothy J, Highbarger, Helene C, Lallemand, Perrine, Leshnower, Bradley G, Looney, David, Moschopoulos, Charalampos D, Murray, Daniel D, Mylonakis, Eleftherios, Rehman, M Tauseef, Rupert, Adam, Stevens, Randy, Turville, Stuart, Wick, Katherine, Lundgren, Jens, and Ko, Emily R
Published: 2024
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7. Novel multi-cluster workflow system to support real-time HPC-enabled epidemic science: Investigating the impact of vaccine acceptance on COVID-19 spread

Author: Bhattacharya, Parantapa, Machi, Dustin, Chen, Jiangzhuo, Hoops, Stefan, Lewis, Bryan, Mortveit, Henning, Venkatramanan, Srinivasan, Wilson, Mandy L., Marathe, Achla, Porebski, Przemyslaw, Klahn, Brian, Outten, Joseph, Vullikanti, Anil, Xie, Dawen, Adiga, Abhijin, Brown, Shawn, Barrett, Christopher, and Marathe, Madhav
Published: 2024
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8. SARS-CoV-2 seroprevalence in vaccine-naïve participants from the Democratic Republic of Congo, Guinea, Liberia, and Mali

Author: Akpa, Esther, Bah, Fatoumata Binta, Barash, Yi-Chi, Beavogui, Abdoul Habib, Biampata, Jean-Luc, Bonnett, Tyler, Brown, Shawn, Burkey, Alissa, Camara, Daouda, Camara, Sekou, Cline-Cole, Elfrida, Coulibaly, Mamadou D, Coulibaly, Nadie, Dewar, Robin, Diallo, Mountaga, Diarra, Samba, Doumbia, Seydou, Eyler, Allison, Fouth Tchos, Karine, Francis, Alyson, Grue, Louis, Highbarger, Helene, Highbarger, Jeroen, Ibanda, Augustin Mbala, Kallon, Kadé, Kindombe, Esaie Luzolu, Kingebeni, Placide Mbala, Kolié, Cece Francis, Lallemand, Perrine, Lim, Caeul, Lokilo, Emmanuel, Lumembe, Raphael, McCormack, Ashley Louise, McNay, Laura, Mukendi, Gael, Mukendi, Thierry, Muyembe, Jean Jacques, Newell, Kevin, Njoh, Wissedi, Pankwa, Isaac Balmayel, Pukuta, Elisabeth, Riziki, Yogolelo, Rupert, Adam, Samake, Seydou, Sandrus, Jennifer, Sangare, Adama, Smolskis, Mary, Souto Adeva, Gema, Stevens, Randy, Tangara, Cheick Oumar, Tounkara, Moctar, Trumbull-Kennedy, Meghan, Tshomba, Antoine, Wague, Mamadou, Weyers, Shera, Worthington, Chris, Laverdure, Sylvain, Kazadi, Donatien, Kone, Kadidia, Callier, Viviane, Dabitao, Djeneba, Dennis, Dehkontee, Haidara, Mory Cherif, Hunsberger, Sally, Mbaya, Olivier Tshiani, Ridzon, Renee, Sereti, Irini, and Shaw-Saliba, Katy
Published: 2024
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9. Control strategies for the invasive plant kudzu (Pueraria montana) only minimally impacts soil activity, chemistry, and bacterial and fungal communities

Author: Shahrtash, Maryam, Tucker, Avery E., Weaver, Mark A., and Brown, Shawn P.
Published: 2023
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10. Deploying large fixed file datasets with SquashFS and Singularity

Author: Rioux, Pierre, Kiar, Gregory, Hutton, Alexandre, Evans, Alan C., and Brown, Shawn T.
Subjects: Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Performance
Abstract: Shared high-performance computing (HPC) platforms, such as those provided by XSEDE and Compute Canada, enable researchers to carry out large-scale computational experiments at a fraction of the cost of the cloud. Most systems require the use of distributed filesystems (e.g. Lustre) for providing a highly multi-user, large capacity storage environment. These suffer performance penalties as the number of files increases due to network contention and metadata performance. We demonstrate how a combination of two technologies, Singularity and SquashFS, can help developers, integrators, architects, and scientists deploy large datasets (O(10M) files) on these shared systems with minimal performance limitations. The proposed integration enables more efficient access and indexing than normal file-based dataset installations, while providing transparent file access to users and processes. Furthermore, the approach does not require administrative privileges on the target system. While the examples studied here have been taken from the field of neuroimaging, the technologies adopted are not specific to that field. Currently, this solution is limited to read-only datasets. We propose the adoption of this technology for the consumption and dissemination of community datasets across shared computing resources., Comment: 5 pages, 2 figures, 2 tables. Submitted to PEARC 2020 conference
Published: 2020

11. Performance benefits of Intel(R) OptaneTM DC persistent memory for the parallel processing of large neuroimaging data

Author: Hayot-Sasson, Valerie, Brown, Shawn T, and Glatard, Tristan
Subjects: Computer Science - Performance
Abstract: Open-access neuroimaging datasets have reached petabyte scale, and continue to grow. The ability to leverage the entirety of these datasets is limited to a restricted number of labs with both the capacity and infrastructure to process the data. Whereas Big Data engines have significantly reduced application performance penalties with respect to data movement, their applied strategies (e.g. data locality, in-memory computing and lazy evaluation) are not necessarily practical within neuroimaging workflows where intermediary results may need to be materialized to shared storage for post-processing analysis. In this paper we evaluate the performance advantage brought by Intel(R) OptaneTM DC persistent memory for the processing of large neuroimaging datasets using the two available configurations modes: Memory mode and App Direct mode. We employ a synthetic algorithm on the 76 GiB and 603 GiB BigBrain, as well as apply a standard neuroimaging application on the Consortium for Reliability and Reproducibility (CoRR) dataset using 25 and 96 parallel processes in both cases. Our results show that the performance of applications leveraging persistent memory is superior to that of other storage devices,with the exception of DRAM. This is the case in both Memory and App Direct mode and irrespective of the amount of data and parallelism. Furthermore, persistent memory in App Direct mode is believed to benefit from the use of DRAM as a cache for writing when output data is significantly smaller than available memory. We believe the use of persistent memory will be beneficial to both neuroimaging applications running on HPC or visualization of large, high-resolution images.
Published: 2019

12. Effects of water chemistry and flow on lead release from plastic pipes versus copper pipes, implications for plumbing decontamination

Author: Ghoochani, Shima, Hadiuzzaman, Md, Mirza, Nahreen, Brown, Shawn P., and Salehi, Maryam
Published: 2023
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13. Comparing Perturbation Models for Evaluating Stability of Neuroimaging Pipelines

Author: Kiar, Gregory, Castro, Pablo de Oliveira, Rioux, Pierre, Petit, Eric, Brown, Shawn T., Evans, Alan C., and Glatard, Tristan
Subjects: Quantitative Biology - Neurons and Cognition, Electrical Engineering and Systems Science - Image and Video Processing
Abstract: A lack of software reproducibility has become increasingly apparent in the last several years, calling into question the validity of scientific findings affected by published tools. Reproducibility issues may have numerous sources of error, including the underlying numerical stability of algorithms and implementations employed. Various forms of instability have been observed in neuroimaging, including across operating system versions, minor noise injections, and implementation of theoretically equivalent algorithms. In this paper we explore the effect of various perturbation methods on a typical neuroimaging pipeline through the use of i) targeted noise injections, ii) Monte Carlo Arithmetic, and iii) varying operating systems to identify the quality and severity of their impact. The work presented here demonstrates that even low order computational models such as the connectome estimation pipeline that we used are susceptible to noise. This suggests that stability is a relevant axis upon which tools should be compared, developed, or improved, alongside more commonly considered axes such as accuracy/biological feasibility or performance. The heterogeneity observed across participants clearly illustrates that stability is a property of not just the data or tools independently, but their interaction. Characterization of stability should therefore be evaluated for specific analyses and performed on a representative set of subjects for consideration in subsequent statistical testing. Additionally, identifying how this relationship scales to higher-order models is an exciting next step which will be explored. Finally, the joint application of perturbation methods with post-processing approaches such as bagging or signal normalization may lead to the development of more numerically stable analyses while maintaining sensitivity to meaningful variation., Comment: 9 pages, 5 figures, 1 table, paper published at IJHPCA
Published: 2019

14. Performance Evaluation of Big Data Processing Strategies for Neuroimaging

Author: Hayot-Sasson, Valérie, Brown, Shawn T, and Glatard, Tristan
Subjects: Computer Science - Distributed, Parallel, and Cluster Computing
Abstract: Neuroimaging datasets are rapidly growing in size as a result of advancements in image acquisition methods, open-science and data sharing. However, the adoption of Big Data processing strategies by neuroimaging processing engines remains limited. Here, we evaluate three Big Data processing strategies (in-memory computing, data locality and lazy evaluation) on typical neuroimaging use cases, represented by the BigBrain dataset. We contrast these various strategies using Apache Spark and Nipype as our representative Big Data and neuroimaging processing engines, on Dell EMC's Top-500 cluster. Big Data thresholds were modelled by comparing the data-write rate of the application to the filesystem bandwidth and number of concurrent processes. This model acknowledges the fact that page caching provided by the Linux kernel is critical to the performance of Big Data applications. Results show that in-memory computing alone speeds-up executions by a factor of up to 1.6, whereas when combined with data locality, this factor reaches 5.3. Lazy evaluation strategies were found to increase the likelihood of cache hits, further improving processing time. Such important speed-up values are likely to be observed on typical image processing operations performed on images of size larger than 75GB. A ballpark speculation from our model showed that in-memory computing alone will not speed-up current functional MRI analyses unless coupled with data locality and processing around 280 subjects concurrently. Furthermore, we observe that emulating in-memory computing using in-memory file systems (tmpfs) does not reach the performance of an in-memory engine, presumably due to swapping to disk and the lack of data cleanup. We conclude that Big Data processing strategies are worth developing for neuroimaging applications.
Published: 2018

15. A Serverless Tool for Platform Agnostic Computational Experiment Management

Author: Kiar, Gregory, Brown, Shawn T, Glatard, Tristan, and Evans, Alan C
Subjects: Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Software Engineering
Abstract: Neuroscience has been carried into the domain of big data and high performance computing (HPC) on the backs of initiatives in data collection and an increasingly compute-intensive tools. While managing HPC experiments requires considerable technical acumen, platforms and standards have been developed to ease this burden on scientists. While web-portals make resources widely accessible, data organizations such as the Brain Imaging Data Structure and tool description languages such as Boutiques provide researchers with a foothold to tackle these problems using their own datasets, pipelines, and environments. While these standards lower the barrier to adoption of HPC and cloud systems for neuroscience applications, they still require the consolidation of disparate domain-specific knowledge. We present Clowdr, a lightweight tool to launch experiments on HPC systems and clouds, record rich execution records, and enable the accessible sharing of experimental summaries and results. Clowdr uniquely sits between web platforms and bare-metal applications for experiment management by preserving the flexibility of do-it-yourself solutions while providing a low barrier for developing, deploying and disseminating neuroscientific analysis., Comment: 12 pages, 3 figures, 1 tool
Published: 2018

16. Lead (Pb) deposition onto new and biofilm-laden potable water pipes

Author: Haddiuzaman, Md, Mirza, Nahreen, Brown, Shawn P., Ladner, David A., and Salehi, Maryam
Published: 2023
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17. Model-Based Community Analyses Identify Fungal Endophytes that May Modulate Symptom Development of Charcoal Rot Disease in Soybean

Author: Brown, Shawn P., primary, Shahrtash, Maryam, additional, Stokes, C. Elizabeth, additional, Baird, Sonya, additional, Baird, Richard, additional, and Lu, Shien, additional
Published: 2024
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18. Rapid Restructuring of Rhizosphere and Endospheric Fungal Communities with Drought in Multiple Lines of Domesticated Sunflower

Author: Brown, Shawn P., primary and Mandel, Jennifer R., additional
Published: 2024
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19. Sampling a gradient of red snow algae bloom density reveals novel connections between microbial communities and environmental features

Author: Tucker, Avery E. and Brown, Shawn P.
Published: 2022
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20. Developing interdisciplinary research teams in neurosurgery: key elements to success in brachial plexus and peripheral nerve surgery

Author: Muhlestein, Whitney E., primary, Chang, Kate W. C., additional, Justice, Denise, additional, Johnson, Sarah, additional, Brown, Shawn, additional, and Popadich, Miriana, additional
Published: 2023
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21. Correction to: FungalTraits: a user friendly traits database of fungi and fungus-like stramenopiles

Author: Põlme, Sergei, Abarenkov, Kessy, Henrik Nilsson, R., Lindahl, Björn D., Clemmensen, Karina Engelbrecht, Kauserud, Havard, Nguyen, Nhu, Kjøller, Rasmus, Bates, Scott T., Baldrian, Petr, Frøslev, Tobias Guldberg, Adojaan, Kristjan, Vizzini, Alfredo, Suija, Ave, Pfister, Donald, Baral, Hans-Otto, Järv, Helle, Madrid, Hugo, Nordén, Jenni, Liu, Jian-Kui, Pawlowska, Julia, Põldmaa, Kadri, Pärtel, Kadri, Runnel, Kadri, Hansen, Karen, Larsson, Karl-Henrik, Hyde, Kevin David, Sandoval-Denis, Marcelo, Smith, Matthew E., Toome-Heller, Merje, Wijayawardene, Nalin N., Menolli, Jr., Nelson, Reynolds, Nicole K., Drenkhan, Rein, Maharachchikumbura, Sajeewa S. N., Gibertoni, Tatiana B., Læssøe, Thomas, Davis, William, Tokarev, Yuri, Corrales, Adriana, Soares, Adriene Mayra, Agan, Ahto, Machado, Alexandre Reis, Argüelles-Moyao, Andrés, Detheridge, Andrew, de Meiras-Ottoni, Angelina, Verbeken, Annemieke, Dutta, Arun Kumar, Cui, Bao-Kai, Pradeep, C. K., Marín, César, Stanton, Daniel, Gohar, Daniyal, Wanasinghe, Dhanushka N., Otsing, Eveli, Aslani, Farzad, Griffith, Gareth W., Lumbsch, Thorsten H., Grossart, Hans-Peter, Masigol, Hossein, Timling, Ina, Hiiesalu, Inga, Oja, Jane, Kupagme, John Y., Geml, József, Alvarez-Manjarrez, Julieta, Ilves, Kai, Loit, Kaire, Adamson, Kalev, Nara, Kazuhide, Küngas, Kati, Rojas-Jimenez, Keilor, Bitenieks, Krišs, Irinyi, László, Nagy, László G., Soonvald, Liina, Zhou, Li-Wei, Wagner, Lysett, Aime, M. Catherine, Öpik, Maarja, Mujica, María Isabel, Metsoja, Martin, Ryberg, Martin, Vasar, Martti, Murata, Masao, Nelsen, Matthew P., Cleary, Michelle, Samarakoon, Milan C., Doilom, Mingkwan, Bahram, Mohammad, Hagh-Doust, Niloufar, Dulya, Olesya, Johnston, Peter, Kohout, Petr, Chen, Qian, Tian, Qing, Nandi, Rajasree, Amiri, Rasekh, Perera, Rekhani Hansika, dos Santos Chikowski, Renata, Mendes-Alvarenga, Renato L., Garibay-Orijel, Roberto, Gielen, Robin, Phookamsak, Rungtiwa, Jayawardena, Ruvishika S., Rahimlou, Saleh, Karunarathna, Samantha C., Tibpromma, Saowaluck, Brown, Shawn P., Sepp, Siim-Kaarel, Mundra, Sunil, Luo, Zhu-Hua, Bose, Tanay, Vahter, Tanel, Netherway, Tarquin, Yang, Teng, May, Tom, Varga, Torda, Li, Wei, Coimbra, Victor Rafael Matos, de Oliveira, Virton Rodrigo Targino, de Lima, Vitor Xavier, Mikryukov, Vladimir S., Lu, Yongzhong, Matsuda, Yosuke, Miyamoto, Yumiko, Kõljalg, Urmas, and Tedersoo, Leho
Published: 2021
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22. The Cuban Human Brain Mapping Project, a young and middle age population-based EEG, MRI, and cognition dataset

Author: Valdes-Sosa, Pedro A., Galan-Garcia, Lidice, Bosch-Bayard, Jorge, Bringas-Vega, Maria L., Aubert-Vazquez, Eduardo, Rodriguez-Gil, Iris, Das, Samir, Madjar, Cecile, Virues-Alba, Trinidad, Mohades, Zia, MacIntyre, Leigh C., Rogers, Christine, Brown, Shawn, Valdes-Urrutia, Lourdes, Evans, Alan C., and Valdes-Sosa, Mitchell J.
Published: 2021
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23. Correction to: Soil origin and plant genotype structure distinct microbiome compartments in the model legume Medicago truncatula

Author: Brown, Shawn P., Grillo, Michael A., Podowski, Justin C., and Heath, Katy D.
Published: 2021
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24. Pool-Seq genomic based analytical approaches can yield novel insights into unculturable taxa: an example from the red snow algae Sanguina nivaloides

Author: Tucker, Avery E., primary and Brown, Shawn P., additional
Published: 2023
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25. SynthEco - A multi-layered digital ecosystem for analysing complex human behaviour in context

Author: Gieschen, Antonia, primary, Paquet, Catherine, additional, Sengupta, Raja, additional, Aunio, Anna-Liisa, additional, Belkhiria, Fares, additional, Brown, Shawn, additional, and Dube, Laurette, additional
Published: 2023
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26. Impact Of Frequent Sweet Potato Ingestion On Gut Microbiome, Cholesterol, And Exercise Performance

Author: Smith, JohnEric W., primary, Brown, Shawn P., additional, Bello, Marissa L., additional, Gallegos, Alexis, additional, and Baird, Richard E., additional
Published: 2023
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27. FungalTraits: a user-friendly traits database of fungi and fungus-like stramenopiles

Author: Põlme, Sergei, Abarenkov, Kessy, Henrik Nilsson, R., Lindahl, Björn D., Clemmensen, Karina Engelbrecht, Kauserud, Havard, Nguyen, Nhu, Kjøller, Rasmus, Bates, Scott T., Baldrian, Petr, Frøslev, Tobias Guldberg, Adojaan, Kristjan, Vizzini, Alfredo, Suija, Ave, Pfister, Donald, Baral, Hans-Otto, Järv, Helle, Madrid, Hugo, Nordén, Jenni, Liu, Jian-Kui, Pawlowska, Julia, Põldmaa, Kadri, Pärtel, Kadri, Runnel, Kadri, Hansen, Karen, Larsson, Karl-Henrik, Hyde, Kevin David, Sandoval-Denis, Marcelo, Smith, Matthew E., Toome-Heller, Merje, Wijayawardene, Nalin N., Menolli, Jr., Nelson, Reynolds, Nicole K., Drenkhan, Rein, Maharachchikumbura, Sajeewa S. N., Gibertoni, Tatiana B., Læssøe, Thomas, Davis, William, Tokarev, Yuri, Corrales, Adriana, Soares, Adriene Mayra, Agan, Ahto, Machado, Alexandre Reis, Argüelles-Moyao, Andrés, Detheridge, Andrew, de Meiras-Ottoni, Angelina, Verbeken, Annemieke, Dutta, Arun Kumar, Cui, Bao-Kai, Pradeep, C. K., Marín, César, Stanton, Daniel, Gohar, Daniyal, Wanasinghe, Dhanushka N., Otsing, Eveli, Aslani, Farzad, Griffith, Gareth W., Lumbsch, Thorsten H., Grossart, Hans-Peter, Masigol, Hossein, Timling, Ina, Hiiesalu, Inga, Oja, Jane, Kupagme, John Y., Geml, József, Alvarez-Manjarrez, Julieta, Ilves, Kai, Loit, Kaire, Adamson, Kalev, Nara, Kazuhide, Küngas, Kati, Rojas-Jimenez, Keilor, Bitenieks, Krišs, Irinyi, Laszlo, Nagy, László G., Soonvald, Liina, Zhou, Li-Wei, Wagner, Lysett, Aime, M. Catherine, Öpik, Maarja, Mujica, María Isabel, Metsoja, Martin, Ryberg, Martin, Vasar, Martti, Murata, Masao, Nelsen, Matthew P., Cleary, Michelle, Samarakoon, Milan C., Doilom, Mingkwan, Bahram, Mohammad, Hagh-Doust, Niloufar, Dulya, Olesya, Johnston, Peter, Kohout, Petr, Chen, Qian, Tian, Qing, Nandi, Rajasree, Amiri, Rasekh, Perera, Rekhani Hansika, dos Santos Chikowski, Renata, Mendes-Alvarenga, Renato L., Garibay-Orijel, Roberto, Gielen, Robin, Phookamsak, Rungtiwa, Jayawardena, Ruvishika S., Rahimlou, Saleh, Karunarathna, Samantha C., Tibpromma, Saowaluck, Brown, Shawn P., Sepp, Siim-Kaarel, Mundra, Sunil, Luo, Zhu-Hua, Bose, Tanay, Vahter, Tanel, Netherway, Tarquin, Yang, Teng, May, Tom, Varga, Torda, Li, Wei, Coimbra, Victor Rafael Matos, de Oliveira, Virton Rodrigo Targino, de Lima, Vitor Xavier, Mikryukov, Vladimir S., Lu, Yongzhong, Matsuda, Yosuke, Miyamoto, Yumiko, Kõljalg, Urmas, and Tedersoo, Leho
Published: 2020
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28. Microbial Ecology of Snow Reveals Taxa-Specific Biogeographical Structure

Author: Brown, Shawn P. and Jumpponen, Ari
Published: 2019

29. Quantifying the Exposure to Antibiotic-Resistant Pathogens Among Patients Discharged From a Single Hospital Across All California Healthcare Facilities

Author: Datta, Rupak, Brown, Shawn, Nguyen, Vinh Q, Cao, Chenghua, Billimek, John, Avery, Taliser, Lee, Bruce Y, and Huang, Susan S
Subjects: Medical Microbiology, Biomedical and Clinical Sciences, Clinical Sciences, Biodefense, Clinical Research, Antimicrobial Resistance, Vaccine Related, Health Services, Emerging Infectious Diseases, Patient Safety, Prevention, Infectious Diseases, Aetiology, 2.2 Factors relating to the physical environment, Infection, Adolescent, Adult, Aged, Aged, 80 and over, Anti-Bacterial Agents, California, Carrier State, Clostridium, Cross Infection, Drug Resistance, Bacterial, Female, Hospitals, Humans, Klebsiella pneumoniae, Length of Stay, Male, Methicillin-Resistant Staphylococcus aureus, Middle Aged, Nursing Homes, Patient Discharge, Patient Readmission, Retrospective Studies, Vancomycin-Resistant Enterococci, Young Adult, Medical and Health Sciences, Epidemiology, Biomedical and clinical sciences, Health sciences
Abstract: ObjectiveTo assess the time-dependent exposure of California healthcare facilities to patients harboring methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococci (VRE), extended-spectrum β-lactamase (ESBL)-producing Escherichia coli and Klebsiella pneumoniae, and Clostridium difficile infection (CDI) upon discharge from 1 hospital.MethodsRetrospective multiple-cohort study of adults discharged from 1 hospital in 2005-2009, counting hospitals, nursing homes, cities, and counties in which carriers were readmitted, and comparing the number and length of stay of readmissions and the number of distinct readmission facilities among carriers versus noncarriers.ResultsWe evaluated 45,772 inpatients including those with MRSA (N=1,198), VRE (N=547), ESBL (N=121), and CDI (N=300). Within 1 year of discharge, MRSA, VRE, and ESBL carriers exposed 137, 117, and 45 hospitals and 103, 83, and 37 nursing homes, generating 58,804, 33,486, and 15,508 total exposure-days, respectively. Within 90 days of discharge, CDI patients exposed 36 hospitals and 35 nursing homes, generating 7,318 total exposure-days. Compared with noncarriers, carriers had more readmissions to hospitals (MRSA:1.8 vs 0.9/patient; VRE: 2.6 vs 0.9; ESBL: 2.3 vs 0.9; CDI: 0.8 vs 0.4; all P
Published: 2015

30. Advanced Techniques for Scientific Programming and Collaborative Development of Open Source Software Packages at the International Centre for Theoretical Physics (ICTP)

Author: Girotto, Ivan, Kohlmeyer, Axel, Grellscheid, David, and Brown, Shawn T.
Subjects: Computer Science - Software Engineering, Computer Science - Mathematical Software
Abstract: A large number of computational scientific research projects make use of open source software packages. However, the development process of such tools frequently differs from conventional software development; partly because of the nature of research, where the problems being addressed are not always fully understood; partly because the majority of the development is often carried out by scientists with limited experience and exposure to best practices of software engineering. Often the software development suffers from the pressure to publish scientific results and that credit for software development is limited in comparison. Fundamental components of software engineering like modular and reusable design, validation, documentation, and software integration as well as effective maintenance and user support tend to be disregarded due to lack of resources and qualified specialists. Thus innovative developments are often hindered by steep learning curves required to master development for legacy software packages full of ad hoc solutions. The growing complexity of research, however, requires suitable and maintainable computational tools, resulting in a widening gap between the potential users (often growing in number) and contributors to the development of such a package. In this paper we share our experiences aiming to improve the situation by training particularly young scientists, through disseminating our own experiences at contributing to open source software packages and practicing key components of software engineering adapted for scientists and scientific software development. Specifically we summarize the outcome of the Workshop in Advanced Techniques for Scientific Programming and Collaborative Development of Open Source Software Packages run at the Abdus Salam International Centre for Theoretical Physics in March 2013, and discuss our conclusions for future efforts.
Published: 2013

31. Advances in molecular quantum chemistry contained in the Q-Chem 4 program package

Author: Shao, Yihan, Gan, Zhengting, Epifanovsky, Evgeny, Gilbert, Andrew TB, Wormit, Michael, Kussmann, Joerg, Lange, Adrian W, Behn, Andrew, Deng, Jia, Feng, Xintian, Ghosh, Debashree, Goldey, Matthew, Horn, Paul R, Jacobson, Leif D, Kaliman, Ilya, Khaliullin, Rustam Z, Kuś, Tomasz, Landau, Arie, Liu, Jie, Proynov, Emil I, Rhee, Young Min, Richard, Ryan M, Rohrdanz, Mary A, Steele, Ryan P, Sundstrom, Eric J, Woodcock, H Lee, Zimmerman, Paul M, Zuev, Dmitry, Albrecht, Ben, Alguire, Ethan, Austin, Brian, Beran, Gregory JO, Bernard, Yves A, Berquist, Eric, Brandhorst, Kai, Bravaya, Ksenia B, Brown, Shawn T, Casanova, David, Chang, Chun-Min, Chen, Yunqing, Chien, Siu Hung, Closser, Kristina D, Crittenden, Deborah L, Diedenhofen, Michael, DiStasio, Robert A, Do, Hainam, Dutoi, Anthony D, Edgar, Richard G, Fatehi, Shervin, Fusti-Molnar, Laszlo, Ghysels, An, Golubeva-Zadorozhnaya, Anna, Gomes, Joseph, Hanson-Heine, Magnus WD, Harbach, Philipp HP, Hauser, Andreas W, Hohenstein, Edward G, Holden, Zachary C, Jagau, Thomas-C, Ji, Hyunjun, Kaduk, Benjamin, Khistyaev, Kirill, Kim, Jaehoon, Kim, Jihan, King, Rollin A, Klunzinger, Phil, Kosenkov, Dmytro, Kowalczyk, Tim, Krauter, Caroline M, Lao, Ka Un, Laurent, Adèle D, Lawler, Keith V, Levchenko, Sergey V, Lin, Ching Yeh, Liu, Fenglai, Livshits, Ester, Lochan, Rohini C, Luenser, Arne, Manohar, Prashant, Manzer, Samuel F, Mao, Shan-Ping, Mardirossian, Narbe, Marenich, Aleksandr V, Maurer, Simon A, Mayhall, Nicholas J, Neuscamman, Eric, Oana, C Melania, Olivares-Amaya, Roberto, O’Neill, Darragh P, Parkhill, John A, Perrine, Trilisa M, Peverati, Roberto, Prociuk, Alexander, Rehn, Dirk R, Rosta, Edina, Russ, Nicholas J, Sharada, Shaama M, Sharma, Sandeep, Small, David W, and Sodt, Alexander
Subjects: Chemical Sciences, Physical Chemistry, Theoretical and Computational Chemistry, quantum chemistry, electron correlation, electronic structure theory, Q-Chem, computational modelling, software, density functional theory, Atomic, Molecular, Nuclear, Particle and Plasma Physics, Physical Chemistry (incl. Structural), Chemical Physics, Physical chemistry, Theoretical and computational chemistry
Abstract: A summary of the technical advances that are incorporated in the fourth major release of the Q-Chem quantum chemistry program is provided, covering approximately the last seven years. These include developments in density functional theory methods and algorithms, nuclear magnetic resonance (NMR) property evaluation, coupled cluster and perturbation theories, methods for electronically excited and open-shell species, tools for treating extended environments, algorithms for walking on potential surfaces, analysis tools, energy and electron transfer modelling, parallel computing capabilities, and graphical user interfaces. In addition, a selection of example case studies that illustrate these capabilities is given. These include extensive benchmarks of the comparative accuracy of modern density functionals for bonded and non-bonded interactions, tests of attenuated second order Møller-Plesset (MP2) methods for intermolecular interactions, a variety of parallel performance benchmarks, and tests of the accuracy of implicit solvation models. Some specific chemical examples include calculations on the strongly correlated Cr2 dimer, exploring zeolite-catalysed ethane dehydrogenation, energy decomposition analysis of a charged ter-molecular complex arising from glycerol photoionisation, and natural transition orbitals for a Frenkel exciton state in a nine-unit model of a self-assembling nanotube.
Published: 2015

32. Convergence research and innovation digital backbone

Author: Dube, Laurette, primary, Wolfert, Sjaak, additional, Zimmerman, Karin, additional, Yang, Nathan, additional, Diaz-Lopez, Fernando, additional, Arvanitis, Rigas, additional, Schillo, Sandra, additional, Hamalova, Sabina, additional, Nie, Jian Yun, additional, and Brown, Shawn, additional
Published: 2020
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33. Optimizing Select Fraser Fir (Abies fraseri) Reforestation Methods within an Artificial Bald at Mount Buckley, Great Smoky Mountains National Park

Author: Smith, Benjamin, primary, Brown, Shawn P., additional, Frampton, John, additional, Braham, AnneMargaret, additional, Stokes, C. Elizabeth, additional, and Baird, Richard, additional
Published: 2023
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34. Tools for Developing Effective Interdisciplinary Research Teams in Neurosurgery

Author: Muhlestein, Whitney E., primary, Chang, Kate W.-C., additional, Justice, Denise, additional, Johnson, Sarah, additional, Brown, Shawn, additional, and Popadich, Miriana, additional
Published: 2023
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35. Impact of seasonal influenza vaccination in the presence of vaccine interference

Author: Shim, Eunha, Smith, Kenneth J., Nowalk, Mary Patricia, Raviotta, Jonathan M., Brown, Shawn T., DePasse, Jay, and Zimmerman, Richard K.
Published: 2018
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36. Soil origin and plant genotype structure distinct microbiome compartments in the model legume Medicago truncatula

Author: Brown, Shawn P., Grillo, Michael A., Podowski, Justin C., and Heath, Katy D.
Published: 2020
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37. Modeling the regional spread and control of vancomycin-resistant enterococci

Author: Lee, Bruce Y, Yilmaz, S Levent, Wong, Kim F, Bartsch, Sarah M, Eubank, Stephen, Song, Yeohan, Avery, Taliser R, Christie, Richard, Brown, Shawn T, Epstein, Joshua M, Parker, Jon I, and Huang, Susan S
Subjects: Health Services and Systems, Biomedical and Clinical Sciences, Clinical Sciences, Health Sciences, Clinical Research, Emerging Infectious Diseases, Patient Safety, Good Health and Well Being, Anti-Bacterial Agents, California, Computer Simulation, Cross Infection, Enterococcus, Gram-Positive Bacterial Infections, Hospitals, Humans, Infection Control, Prevalence, Vancomycin, Vancomycin Resistance, Vancomycin-resistant Enterococcus, Health care-associated infections, Modeling, Simulation, article, bacterial colonization, bacterial transmission, disease surveillance, emergency care, infection control, nonhuman, United States, vancomycin resistant Enterococcus, Nursing, Public Health and Health Services, Epidemiology, Clinical sciences, Public health
Abstract: BackgroundBecause patients can remain colonized with vancomycin-resistant enterococci (VRE) for long periods of time, VRE may spread from one health care facility to another.MethodsUsing the Regional Healthcare Ecosystem Analyst, an agent-based model of patient flow among all Orange County, California, hospitals and communities, we quantified the degree and speed at which changes in VRE colonization prevalence in a hospital may affect prevalence in other Orange County hospitals.ResultsA sustained 10% increase in VRE colonization prevalence in any 1 hospital caused a 2.8% (none to 62%) average relative increase in VRE prevalence in all other hospitals. Effects took from 1.5 to >10 years to fully manifest. Larger hospitals tended to have greater affect on other hospitals.ConclusionsWhen monitoring and controlling VRE, decision makers may want to account for regional effects. Knowing a hospital's connections with other health care facilities via patient sharing can help determine which hospitals to include in a surveillance or control program.
Published: 2013

38. The Regional Healthcare Ecosystem Analyst (RHEA): a simulation modeling tool to assist infectious disease control in a health system

Author: Lee, Bruce Y, Wong, Kim F, Bartsch, Sarah M, Yilmaz, S Levent, Avery, Taliser R, Brown, Shawn T, Song, Yeohan, Singh, Ashima, Kim, Diane S, and Huang, Susan S
Subjects: Biomedical and Clinical Sciences, Clinical Sciences, Bioengineering, Infectious Diseases, Emerging Infectious Diseases, Infection, Good Health and Well Being, California, Computer Simulation, Delivery of Health Care, Hospital Administration, Humans, Infection Control, Software, Healthcare System, Hospital Acquired Infections, Hospitals, Patient Sharing, article, computer program, disease simulation, disease transmission, ethnicity, health care facility, health care policy, health care system, hospital bed capacity, hospital readmission, human, infection, infection control, insurance, intensive care unit, length of stay, methicillin resistant Staphylococcus aureus, morbidity, prevalence, probability, regional healthcare ecosystem analyst, social status, theoretical model, computer simulation, health care delivery, hospital, hospital management, methodology, organization and management, United States, Information and Computing Sciences, Engineering, Medical and Health Sciences, Medical Informatics, Biomedical and clinical sciences, Health sciences, Information and computing sciences
Abstract: ObjectiveAs healthcare systems continue to expand and interconnect with each other through patient sharing, administrators, policy makers, infection control specialists, and other decision makers may have to take account of the entire healthcare 'ecosystem' in infection control.Materials and methodsWe developed a software tool, the Regional Healthcare Ecosystem Analyst (RHEA), that can accept user-inputted data to rapidly create a detailed agent-based simulation model (ABM) of the healthcare ecosystem (ie, all healthcare facilities, their adjoining community, and patient flow among the facilities) of any region to better understand the spread and control of infectious diseases.ResultsTo demonstrate RHEA's capabilities, we fed extensive data from Orange County, California, USA, into RHEA to create an ABM of a healthcare ecosystem and simulate the spread and control of methicillin-resistant Staphylococcus aureus. Various experiments explored the effects of changing different parameters (eg, degree of transmission, length of stay, and bed capacity).DiscussionOur model emphasizes how individual healthcare facilities are components of integrated and dynamic networks connected via patient movement and how occurrences in one healthcare facility may affect many other healthcare facilities.ConclusionsA decision maker can utilize RHEA to generate a detailed ABM of any healthcare system of interest, which in turn can serve as a virtual laboratory to test different policies and interventions.
Published: 2013

39. The Importance of Nursing Homes in the Spread of Methicillin-resistant Staphylococcus aureus (MRSA) Among Hospitals

Author: Lee, Bruce Y, Bartsch, Sarah M, Wong, Kim F, Singh, Ashima, Avery, Taliser R, Kim, Diane S, Brown, Shawn T, Murphy, Courtney R, Yilmaz, Server Levent, Potter, Margaret A, and Huang, Susan S
Subjects: Health Services and Systems, Nursing, Health Sciences, Clinical Research, Infectious Diseases, Antimicrobial Resistance, Health Services, Emerging Infectious Diseases, Infection, Good Health and Well Being, Adult, California, Cross Infection, Disease Outbreaks, Health Facility Size, Hospitals, Humans, Infection Control, Interinstitutional Relations, Methicillin-Resistant Staphylococcus aureus, Nursing Homes, Patient Transfer, Prevalence, Staphylococcal Infections, MRSA, outbreak, long-term care, nursing homes, hospitals, article, disease transmission, epidemic, health care facility, hospital infection, human, methicillin resistant Staphylococcus aureus infection, nursing home, patient transport, prevalence, priority journal, United States, Public Health and Health Services, Applied Economics, Health Policy & Services, Applied economics, Health services and systems, Policy and administration
Abstract: BackgroundHospital infection control strategies and programs may not consider control of methicillin-resistant Staphylococcus aureus (MRSA) in nursing homes in a county.MethodsUsing our Regional Healthcare Ecosystem Analyst, we augmented our existing agent-based model of all hospitals in Orange County (OC), California, by adding all nursing homes and then simulated MRSA outbreaks in various health care facilities.ResultsThe addition of nursing homes substantially changed MRSA transmission dynamics throughout the county. The presence of nursing homes substantially potentiated the effects of hospital outbreaks on other hospitals, leading to an average 46.2% (range, 3.3%-156.1%) relative increase above and beyond the impact when only hospitals are included for an outbreak in OC's largest hospital. An outbreak in the largest hospital affected all other hospitals (average 2.1% relative prevalence increase) and the majority (~90%) of nursing homes (average 3.2% relative increase) after 6 months. An outbreak in the largest nursing home had effects on multiple OC hospitals, increasing MRSA prevalence in directly connected hospitals by an average 0.3% and in hospitals not directly connected through patient transfers by an average 0.1% after 6 months. A nursing home outbreak also had some effect on MRSA prevalence in other nursing homes.ConclusionsNursing homes, even those not connected by direct patient transfers, may be a vital component of a hospital's infection control strategy. To achieve effective control, a hospital may want to better understand how regional nursing homes and hospitals are connected through both direct and indirect (with intervening stays at home) patient sharing.
Published: 2013

40. The Potential Regional Impact of Contact Precaution Use in Nursing Homes to Control Methicillin-Resistant Staphylococcus aureus

Author: Lee, Bruce Y, Singh, Ashima, Bartsch, Sarah M, Wong, Kim F, Kim, Diane S, Avery, Taliser R, Brown, Shawn T, Murphy, Courtney R, Yilmaz, S Levent, and Huang, Susan S
Subjects: Biomedical and Clinical Sciences, Clinical Sciences, Prevention, Patient Safety, Antimicrobial Resistance, Emerging Infectious Diseases, Infectious Diseases, Clinical Research, Health Services, Infection, California, Cross Infection, Disease Outbreaks, Hospitals, Humans, Methicillin-Resistant Staphylococcus aureus, Models, Theoretical, Nursing Homes, Staphylococcal Infections, article, disease surveillance, disease transmission, health care facility, human, infection control, length of stay, methicillin resistant Staphylococcus aureus, methicillin resistant Staphylococcus aureus infection, nursing home, prevalence, sensitivity analysis, Medical and Health Sciences, Epidemiology, Biomedical and clinical sciences, Health sciences
Abstract: ObjectiveImplementation of contact precautions in nursing homes to prevent methicillin-resistant Staphylococcus aureus (MRSA) transmission could cost time and effort and may have wide-ranging effects throughout multiple health facilities. Computational modeling could forecast the potential effects and guide policy making.DesignOur multihospital computational agent-based model, Regional Healthcare Ecosystem Analyst (RHEA).SettingAll hospitals and nursing homes in Orange County, California.MethodsOur simulation model compared the following 3 contact precaution strategies: (1) no contact precautions applied to any nursing home residents, (2) contact precautions applied to those with clinically apparent MRSA infections, and (3) contact precautions applied to all known MRSA carriers as determined by MRSA screening performed by hospitals.ResultsOur model demonstrated that contact precautions for patients with clinically apparent MRSA infections in nursing homes resulted in a median 0.4% (range, 0%-1.6%) relative decrease in MRSA prevalence in nursing homes (with 50% adherence) but had no effect on hospital MRSA prevalence, even 5 years after initiation. Implementation of contact precautions (with 50% adherence) in nursing homes for all known MRSA carriers was associated with a median 14.2% (range, 2.1%-21.8%) relative decrease in MRSA prevalence in nursing homes and a 2.3% decrease (range, 0%-7.1%) in hospitals 1 year after implementation. Benefits accrued over time and increased with increasing compliance.ConclusionsOur modeling study demonstrated the substantial benefits of extending contact precautions in nursing homes from just those residents with clinically apparent infection to all MRSA carriers, which suggests the benefits of hospitals and nursing homes sharing and coordinating information on MRSA surveillance and carriage status.
Published: 2013

41. Geotemporal Analysis ofNeisseria meningitidis Clones in the United States: 2000–2005

Author: Wiringa, Ann E, Shutt, Kathleen A, Marsh, Jane W, Cohn, Amanda C, Messonnier, Nancy E, Zansky, Shelley M, Petit, Susan, Farley, Monica M, Gershman, Ken, Lynfield, Ruth, Reingold, Arthur, Schaffner, William, Thompson, Jamie, Brown, Shawn T, Lee, Bruce Y, and Harrison, Lee H
Subjects: Microbiology, Biological Sciences, Biomedical and Clinical Sciences, Immunization, Vaccine Related, Prevention, Aetiology, 2.2 Factors relating to the physical environment, Infection, Bacterial Outer Membrane Proteins, Clone Cells, Epidemiological Monitoring, Gene Expression, Humans, Meningococcal Infections, Multilocus Sequence Typing, Neisseria meningitidis, Retrospective Studies, Serotyping, Spatio-Temporal Analysis, United States, General Science & Technology
Abstract: BackgroundThe detection of meningococcal outbreaks relies on serogrouping and epidemiologic definitions. Advances in molecular epidemiology have improved the ability to distinguish unique Neisseria meningitidis strains, enabling the classification of isolates into clones. Around 98% of meningococcal cases in the United States are believed to be sporadic.MethodsMeningococcal isolates from 9 Active Bacterial Core surveillance sites throughout the United States from 2000 through 2005 were classified according to serogroup, multilocus sequence typing, and outer membrane protein (porA, porB, and fetA) genotyping. Clones were defined as isolates that were indistinguishable according to this characterization. Case data were aggregated to the census tract level and all non-singleton clones were assessed for non-random spatial and temporal clustering using retrospective space-time analyses with a discrete Poisson probability model.ResultsAmong 1,062 geocoded cases with available isolates, 438 unique clones were identified, 78 of which had ≥2 isolates. 702 cases were attributable to non-singleton clones, accounting for 66.0% of all geocoded cases. 32 statistically significant clusters comprised of 107 cases (10.1% of all geocoded cases) were identified. Clusters had the following attributes: included 2 to 11 cases; 1 day to 33 months duration; radius of 0 to 61.7 km; and attack rate of 0.7 to 57.8 cases per 100,000 population. Serogroups represented among the clusters were: B (n = 12 clusters, 45 cases), C (n = 11 clusters, 27 cases), and Y (n = 9 clusters, 35 cases); 20 clusters (62.5%) were caused by serogroups represented in meningococcal vaccines that are commercially available in the United States.ConclusionsAround 10% of meningococcal disease cases in the U.S. could be assigned to a geotemporal cluster. Molecular characterization of isolates, combined with geotemporal analysis, is a useful tool for understanding the spread of virulent meningococcal clones and patterns of transmission in populations.
Published: 2013

42. Geotemporal analysis of Neisseria meningitidis clones in the United States: 2000-2005.

Author: Wiringa, Ann E, Shutt, Kathleen A, Marsh, Jane W, Cohn, Amanda C, Messonnier, Nancy E, Zansky, Shelley M, Petit, Susan, Farley, Monica M, Gershman, Ken, Lynfield, Ruth, Reingold, Arthur, Schaffner, William, Thompson, Jamie, Brown, Shawn T, Lee, Bruce Y, and Harrison, Lee H
Subjects: Clone Cells, Humans, Neisseria meningitidis, Meningococcal Infections, Bacterial Outer Membrane Proteins, Serotyping, Retrospective Studies, Gene Expression, United States, Multilocus Sequence Typing, Epidemiological Monitoring, Spatio-Temporal Analysis, General Science & Technology
Abstract: BackgroundThe detection of meningococcal outbreaks relies on serogrouping and epidemiologic definitions. Advances in molecular epidemiology have improved the ability to distinguish unique Neisseria meningitidis strains, enabling the classification of isolates into clones. Around 98% of meningococcal cases in the United States are believed to be sporadic.MethodsMeningococcal isolates from 9 Active Bacterial Core surveillance sites throughout the United States from 2000 through 2005 were classified according to serogroup, multilocus sequence typing, and outer membrane protein (porA, porB, and fetA) genotyping. Clones were defined as isolates that were indistinguishable according to this characterization. Case data were aggregated to the census tract level and all non-singleton clones were assessed for non-random spatial and temporal clustering using retrospective space-time analyses with a discrete Poisson probability model.ResultsAmong 1,062 geocoded cases with available isolates, 438 unique clones were identified, 78 of which had ≥2 isolates. 702 cases were attributable to non-singleton clones, accounting for 66.0% of all geocoded cases. 32 statistically significant clusters comprised of 107 cases (10.1% of all geocoded cases) were identified. Clusters had the following attributes: included 2 to 11 cases; 1 day to 33 months duration; radius of 0 to 61.7 km; and attack rate of 0.7 to 57.8 cases per 100,000 population. Serogroups represented among the clusters were: B (n = 12 clusters, 45 cases), C (n = 11 clusters, 27 cases), and Y (n = 9 clusters, 35 cases); 20 clusters (62.5%) were caused by serogroups represented in meningococcal vaccines that are commercially available in the United States.ConclusionsAround 10% of meningococcal disease cases in the U.S. could be assigned to a geotemporal cluster. Molecular characterization of isolates, combined with geotemporal analysis, is a useful tool for understanding the spread of virulent meningococcal clones and patterns of transmission in populations.
Published: 2013

43. Simulation Shows Hospitals That Cooperate On Infection Control Obtain Better Results Than Hospitals Acting Alone

Author: Lee, Bruce Y, Bartsch, Sarah M, Wong, Kim F, Yilmaz, S Levent, Avery, Taliser R, Singh, Ashima, Song, Yeohan, Kim, Diane S, Brown, Shawn T, Potter, Margaret A, Platt, Richard, and Huang, Susan S
Subjects: Health Services and Systems, Policy and Administration, Health Sciences, Human Society, Emerging Infectious Diseases, Infectious Diseases, Antimicrobial Resistance, Clinical Research, Infection, California, Computer Simulation, Cross Infection, Hospital Shared Services, Hospitals, Humans, Methicillin-Resistant Staphylococcus aureus, Patient Transfer, Staphylococcal Infections, United States, article, bacterial strain, clinical decision making, computer simulation, contact isolation, controlled study, disease surveillance, disease transmission, glove, health care personnel, hospital admission, hospital management, human, infection control, major clinical study, methicillin resistant Staphylococcus aureus, methicillin resistant Staphylococcus aureus infection, multicenter study, patient care, prevalence, surgical gown, Public Health and Health Services, Applied Economics, Health Policy & Services, Health services and systems, Policy and administration
Abstract: Efforts to control life-threatening infections, such as with methicillin-resistant Staphylococcus aureus (MRSA), can be complicated when patients are transferred from one hospital to another. Using a detailed computer simulation model of all hospitals in Orange County, California, we explored the effects when combinations of hospitals tested all patients at admission for MRSA and adopted procedures to limit transmission among patients who tested positive. Called "contact isolation," these procedures specify precautions for health care workers interacting with an infected patient, such as wearing gloves and gowns. Our simulation demonstrated that each hospital's decision to test for MRSA and implement contact isolation procedures could affect the MRSA prevalence in all other hospitals. Thus, our study makes the case that further cooperation among hospitals--which is already reflected in a few limited collaborative infection control efforts under way--could help individual hospitals achieve better infection control than they could achieve on their own.
Published: 2012

44. Recovery and resiliency of skin microbial communities on the southern leopard frog (Lithobates sphenocephalus) following two biotic disturbances

Author: Weeks, Denita M., Parris, Matthew J., and Brown, Shawn P.
Published: 2020
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45. Cost-effectiveness and public health impact of alternative influenza vaccination strategies in high-risk adults

Author: Raviotta, Jonathan M., Smith, Kenneth J., DePasse, Jay, Brown, Shawn T., Shim, Eunha, Nowalk, Mary Patricia, Wateska, Angela, France, Glenson S., and Zimmerman, Richard K.
Published: 2017
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46. Long-Term Care Facilities: Important Participants of the Acute Care Facility Social Network?

Author: Lee, Bruce Y., Song, Yeohan, Bartsch, Sarah M., Kim, Diane S., Singh, Ashima, Avery, Taliser R., Brown, Shawn T., Yilmaz, S. Levent, Wong, Kim F., Potter, Margaret A., Burke, Donald S., Platt, Richard, and Huang, Susan S.
Subjects: resistant staphylococcus-aureus, orange-county, hospitals, california, continuum, spread
Abstract: BackgroundAcute care facilities are connected via patient sharing, forming a network. However, patient sharing extends beyond this immediate network to include sharing with long-term care facilities. The extent of long-term care facility patient sharing on the acute care facility network is unknown. The objective of this study was to characterize and determine the extent and pattern of patient transfers to, from, and between long-term care facilities on the network of acute care facilities in a large metropolitan county.Methods/Principal FindingsWe applied social network constructs principles, measures, and frameworks to all 2007 annual adult and pediatric patient transfers among the healthcare facilities in Orange County, California, using data from surveys and several datasets. We evaluated general network and centrality measures as well as individual ego measures and further constructed sociograms. Our results show that over the course of a year, 66 of 72 long-term care facilities directly sent and 67 directly received patients from other long-term care facilities. Long-term care facilities added 1,524 ties between the acute care facilities when ties represented at least one patient transfer. Geodesic distance did not closely correlate with the geographic distance among facilities.Conclusions/SignificanceThis study demonstrates the extent to which long-term care facilities are connected to the acute care facility patient sharing network. Many long-term care facilities were connected by patient transfers and further added many connections to the acute care facility network. This suggests that policy-makers and health officials should account for patient sharing with and among long-term care facilities as well as those among acute care facilities when evaluating policies and interventions.
Published: 2011

47. Modeling the Spread of Methicillin-Resistant Staphylococcus aureus (MRSA) Outbreaks throughout the Hospitals in Orange County, California

Author: Lee, Bruce Y, McGlone, Sarah M, Wong, Kim F, Yilmaz, S Levent, Avery, Taliser R, Song, Yeohan, Christie, Richard, Eubank, Stephen, Brown, Shawn T, Epstein, Joshua M, Parker, Jon I, Burke, Donald S, Platt, Richard, and Huang, Susan S
Subjects: Biomedical and Clinical Sciences, Clinical Sciences, Antimicrobial Resistance, Emerging Infectious Diseases, Vaccine Related, Infectious Diseases, Prevention, Patient Safety, Infection, California, Computer Simulation, Cross Infection, Disease Outbreaks, Epidemiologic Methods, Humans, Length of Stay, Methicillin-Resistant Staphylococcus aureus, Patient Readmission, Patient Transfer, Prevalence, Staphylococcal Infections, Time Factors, article, disease transmission, epidemic, hospital, hospital readmission, human, length of stay, major clinical study, methicillin resistant Staphylococcus aureus infection, patient transport, prevalence, sensitivity analysis, United States, Medical and Health Sciences, Epidemiology, Biomedical and clinical sciences, Health sciences
Abstract: BackgroundSince hospitals in a region often share patients, an outbreak of methicillin-resistant Staphylococcus aureus (MRSA) infection in one hospital could affect other hospitals.MethodsUsing extensive data collected from Orange County (OC), California, we developed a detailed agent-based model to represent patient movement among all OC hospitals. Experiments simulated MRSA outbreaks in various wards, institutions, and regions. Sensitivity analysis varied lengths of stay, intraward transmission coefficients (β), MRSA loss rate, probability of patient transfer or readmission, and time to readmission.ResultsEach simulated outbreak eventually affected all of the hospitals in the network, with effects depending on the outbreak size and location. Increasing MRSA prevalence at a single hospital (from 5% to 15%) resulted in a 2.9% average increase in relative prevalence at all other hospitals (ranging from no effect to 46.4%). Single-hospital intensive care unit outbreaks (modeled increase from 5% to 15%) caused a 1.4% average relative increase in all other OC hospitals (ranging from no effect to 12.7%).ConclusionMRSA outbreaks may rarely be confined to a single hospital but instead may affect all of the hospitals in a region. This suggests that prevention and control strategies and policies should account for the interconnectedness of health care facilities.
Published: 2011

48. Geospatial Planning and the Resulting Economic Impact of Human Papillomavirus Vaccine Introduction in Mozambique

Author: Haidari, Leila A., Brown, Shawn T., Constenla, Dagna, Zenkov, Eli, Ferguson, Marie, de Broucker, Gatien, Ozawa, Sachiko, Clark, Samantha, Portnoy, Allison, and Lee, Bruce Y.
Published: 2017

49. Wildfire severity alters soil microbial exoenzyme production and fungal abundances in the Southern Appalachian Mountains

Author: SCHILL, Megan L., primary, BAIRD, Richard, additional, BROWN, Shawn P., additional, and VEACH, Allison M., additional
Published: 2023
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50. Convergent shifts in soil fungal communities associated with Fagaceae reforestation in the Southern Appalachian Mountains

Author: Brown, Shawn P., primary, Clark, Stacy L., additional, Ford, Emerald, additional, Mirza, Nahreen, additional, Odeh, Amerah, additional, Schlarbaum, Scott E., additional, Jumpponen, Ari, additional, and Baird, Richard, additional
Published: 2023
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