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1. Lens functions for exploring UMAP Projections with Domain Knowledge

Author

Bot, Daniel M. and Aerts, Jan

Subjects
Computer Science - Machine Learning, Computer Science - Computational Geometry, Computer Science - Human-Computer Interaction
Abstract

Dimensionality reduction algorithms are often used to visualise high-dimensional data. Previously, studies have used prior information to enhance or suppress expected patterns in projections. In this paper, we adapt such techniques for domain knowledge guided interactive exploration. Inspired by Mapper and STAD, we present three types of lens functions for UMAP, a state-of-the-art dimensionality reduction algorithm. Lens functions enable analysts to adapt projections to their questions, revealing otherwise hidden patterns. They filter the modelled connectivity to explore the interaction between manually selected features and the data's structure, creating configurable perspectives each potentially revealing new insights. The effectiveness of the lens functions is demonstrated in two use cases and their computational cost is analysed in a synthetic benchmark. Our implementation is available in an open-source Python package: https://github.com/vda-lab/lensed_umap., Comment: 11 pages, 5 figures, submitted to IEEE Transactions on Visualization and Computer Graphics

Published
2024

4. Challenges and Opportunities in Data Visualization Education: A Call to Action

Author

Bach, Benjamin, Keck, Mandy, Rajabiyazdi, Fateme, Losev, Tatiana, Meirelles, Isabel, Dykes, Jason, Laramee, Robert S., AlKadi, Mashael, Stoiber, Christina, Huron, Samuel, Perin, Charles, Morais, Luiz, Aigner, Wolfgang, Kosminsky, Doris, Boucher, Magdalena, Knudsen, Søren, Manataki, Areti, Aerts, Jan, Hinrichs, Uta, Roberts, Jonathan C., and Carpendale, Sheelagh

Subjects
Computer Science - Human-Computer Interaction
Abstract

This paper is a call to action for research and discussion on data visualization education. As visualization evolves and spreads through our professional and personal lives, we need to understand how to support and empower a broad and diverse community of learners in visualization. Data Visualization is a diverse and dynamic discipline that combines knowledge from different fields, is tailored to suit diverse audiences and contexts, and frequently incorporates tacit knowledge. This complex nature leads to a series of interrelated challenges for data visualization education. Driven by a lack of consolidated knowledge, overview, and orientation for visualization education, the 21 authors of this paper-educators and researchers in data visualization-identify and describe 19 challenges informed by our collective practical experience. We organize these challenges around seven themes People, Goals & Assessment, Environment, Motivation, Methods, Materials, and Change. Across these themes, we formulate 43 research questions to address these challenges. As part of our call to action, we then conclude with 5 cross-cutting opportunities and respective action items: embrace DIVERSITY+INCLUSION, build COMMUNITIES, conduct RESEARCH, act AGILE, and relish RESPONSIBILITY. We aim to inspire researchers, educators and learners to drive visualization education forward and discuss why, how, who and where we educate, as we learn to use visualization to address challenges across many scales and many domains in a rapidly changing world: viseducationchallenges.github.io., Comment: Accepted for publication at VIS 2023 Conference, Melbourne, VIC

Published
2023

6. Improving the Projection of Global Structures in Data through Spanning Trees

Author

Alcaide, Daniel and Aerts, Jan

Subjects
Computer Science - Graphics, Computer Science - Machine Learning
Abstract

The connection of edges in a graph generates a structure that is independent of a coordinate system. This visual metaphor allows creating a more flexible representation of data than a two-dimensional scatterplot. In this work, we present STAD (Spanning Trees as Approximation of Data), a dimensionality reduction method to approximate the high-dimensional structure into a graph with or without formulating prior hypotheses. STAD generates an abstract representation of high-dimensional data by giving each data point a location in a graph which preserves the distances in the original high-dimensional space. The STAD graph is built upon the Minimum Spanning Tree (MST) to which new edges are added until the correlation between the distances from the graph and the original dataset is maximized. Additionally, STAD supports the inclusion of additional functions to focus the exploration and allow the analysis of data from new perspectives, emphasizing traits in data which otherwise would remain hidden. We demonstrate the effectiveness of our method by applying it to two real-world datasets: traffic density in Barcelona and temporal measurements of air quality in Castile and Le\'on in Spain.

Published
2019

11. Predicting disease-causing variant combinations

Author

Papadimitriou, Sofia, Gazzo, Andrea, Versbraegen, Nassim, Nachtegael, Charlotte, Aerts, Jan, Moreau, Yves, Van Dooren, Sonia, Nowé, Ann, Smits, Guillaume, and Lenaerts, Tom

Published
2019

12. Challenges and Opportunities in Data Visualization Education:A Call to Action

Author

Bach, Benjamin, Keck, Mandy, Rajabiyazdi, Fateme, Losev, Tatiana, Meirelles, Isabel, Dykes, Jason, Laramee, Robert S., Alkadi, Mashael, Stoiber, Christina, Huron, Samuel, Perin, Charles, Morais, Luiz, Aigner, Wolfgang, Kosminsky, Doris, Boucher, Magdalena, Knudsen, Søren, Manataki, Areti, Aerts, Jan, Hinrichs, Uta, Roberts, Jonathan C., Carpendale, Sheelagh, Bach, Benjamin, Keck, Mandy, Rajabiyazdi, Fateme, Losev, Tatiana, Meirelles, Isabel, Dykes, Jason, Laramee, Robert S., Alkadi, Mashael, Stoiber, Christina, Huron, Samuel, Perin, Charles, Morais, Luiz, Aigner, Wolfgang, Kosminsky, Doris, Boucher, Magdalena, Knudsen, Søren, Manataki, Areti, Aerts, Jan, Hinrichs, Uta, Roberts, Jonathan C., and Carpendale, Sheelagh

Abstract

This paper is a call to action for research and discussion on data visualization education. As visualization evolves and spreads through our professional and personal lives, we need to understand how to support and empower a broad and diverse community of learners in visualization. Data Visualization is a diverse and dynamic discipline that combines knowledge from different fields, is tailored to suit diverse audiences and contexts, and frequently incorporates tacit knowledge. This complex nature leads to a series of interrelated challenges for data visualization education. Driven by a lack of consolidated knowledge, overview, and orientation for visualization education, the 21 authors of this paper - educators and researchers in data visualization - identify and describe 19 challenges informed by our collective practical experience. We organize these challenges around seven themes People, Goals & Assessment, Environment, Motivation, Methods, Materials, and Change. Across these themes, we formulate 43 research questions to address these challenges. As part of our call to action, we then conclude with 5 cross-cutting opportunities and respective action items: embrace DIVERSITY+INCLUSION, build COMMUNITIES, conduct RESEARCH, act AGILE, and relish RESPONSIBILITY. We aim to inspire researchers, educators and learners to drive visualization education forward and discuss why, how, who and where we educate, as we learn to use visualization to address challenges across many scales and many domains in a rapidly changing world: viseducationchallenges.github.io.

Published
2024

13. Assessing transmissibility of HIV-1 drug resistance mutations from treated and from drug-naive individuals

Author

Winand, Raf, Theys, Kristof, Eusébio, Mónica, Aerts, Jan, Camacho, Ricardo J, Gomes, Perpetua, Suchard, Marc A, Vandamme, Anne-Mieke, and Abecasis, Ana B

Subjects
Infectious Diseases, Antimicrobial Resistance, HIV/AIDS, Clinical Research, 5.1 Pharmaceuticals, Evaluation of treatments and therapeutic interventions, Development of treatments and therapeutic interventions, 6.1 Pharmaceuticals, Infection, Adult, Disease Transmission, Infectious, Drug Resistance, Viral, Epidemiological Monitoring, Female, Genotyping Techniques, HIV Infections, HIV-1, Human Immunodeficiency Virus Proteins, Humans, Incidence, Male, Middle Aged, Mutation, Missense, Portugal, Prevalence, Retrospective Studies, antiretroviral therapy, HIV drug resistance, mutation, protease inhibitors, reverse transcriptase inhibitors, transmission, Portuguese HIV-1 Resistance Study Group, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Virology
Abstract

ObjectivesSurveillance drug resistance mutations (SDRMs) in drug-naive patients are typically used to survey HIV-1-transmitted drug resistance (TDR). We test here how SDRMs in patients failing treatment, the original source of TDR, contribute to assessing TDR, transmissibility and transmission source of SDRMs.DesignThis is a retrospective observational study analyzing a Portuguese cohort of HIV-1-infected patients.MethodsThe prevalence of SDRMs to protease inhibitors, nucleoside reverse transcriptase inhibitors (NRTIs) and nonnucleoside reverse transcriptase inhibitors (NNRTIs) in drug-naive and treatment-failing patients was measured for 3554 HIV-1 subtype B patients. Transmission ratio (prevalence in drug-naive/prevalence in treatment-failing patients), average viral load and robust linear regression with outlier detection (prevalence in drug-naive versus in treatment-failing patients) were analyzed and used to interpret transmissibility.ResultsPrevalence of SDRMs in drug-naive and treatment-failing patients were linearly correlated, but some SDRMs were classified as outliers - above (PRO: D30N, N88D/S, L90 M, RT: G190A/S/E) or below (RT: M184I/V) expectations. The normalized regression slope was 0.073 for protease inhibitors, 0.084 for NRTIs and 0.116 for NNRTIs. Differences between SDRMs transmission ratios were not associated with differences in viral loads.ConclusionThe significant linear correlation between prevalence of SDRMs in drug-naive and in treatment-failing patients indicates that the prevalence in treatment-failing patients can be useful to predict levels of TDR. The slope is a cohort-dependent estimate of rate of TDR per drug class and outlier detection reveals comparative persistence of SDRMs. Outlier SDRMs with higher transmissibility are more persistent and more likely to have been acquired from drug-naive patients. Those with lower transmissibility have faster reversion dynamics after transmission and are associated with acquisition from treatment-failing patients.

Published
2015

15. The 3rd DBCLS BioHackathon: improving life science data integration with Semantic Web technologies

Author

Katayama, Toshiaki, Wilkinson, Mark D, Micklem, Gos, Kawashima, Shuichi, Yamaguchi, Atsuko, Nakao, Mitsuteru, Yamamoto, Yasunori, Okamoto, Shinobu, Oouchida, Kenta, Chun, Hong-Woo, Aerts, Jan, Afzal, Hammad, Antezana, Erick, Arakawa, Kazuharu, Aranda, Bruno, Belleau, Francois, Bolleman, Jerven, Bonnal, Raoul JP, Chapman, Brad, Cock, Peter JA, Eriksson, Tore, Gordon, Paul MK, Goto, Naohisa, Hayashi, Kazuhiro, Horn, Heiko, Ishiwata, Ryosuke, Kaminuma, Eli, Kasprzyk, Arek, Kawaji, Hideya, Kido, Nobuhiro, Kim, Young Joo, Kinjo, Akira R, Konishi, Fumikazu, Kwon, Kyung-Hoon, Labarga, Alberto, Lamprecht, Anna-Lena, Lin, Yu, Lindenbaum, Pierre, McCarthy, Luke, Morita, Hideyuki, Murakami, Katsuhiko, Nagao, Koji, Nishida, Kozo, Nishimura, Kunihiro, Nishizawa, Tatsuya, Ogishima, Soichi, Ono, Keiichiro, Oshita, Kazuki, Park, Keun-Joon, Prins, Pjotr, Saito, Taro L, Samwald, Matthias, Satagopam, Venkata P, Shigemoto, Yasumasa, Smith, Richard, Splendiani, Andrea, Sugawara, Hideaki, Taylor, James, Vos, Rutger A, Withers, David, Yamasaki, Chisato, Zmasek, Christian M, Kawamoto, Shoko, Okubo, Kosaku, Asai, Kiyoshi, and Takagi, Toshihisa

Abstract

Abstract Background BioHackathon 2010 was the third in a series of meetings hosted by the Database Center for Life Sciences (DBCLS) in Tokyo, Japan. The overall goal of the BioHackathon series is to improve the quality and accessibility of life science research data on the Web by bringing together representatives from public databases, analytical tool providers, and cyber-infrastructure researchers to jointly tackle important challenges in the area of in silico biological research. Results The theme of BioHackathon 2010 was the 'Semantic Web', and all attendees gathered with the shared goal of producing Semantic Web data from their respective resources, and/or consuming or interacting those data using their tools and interfaces. We discussed on topics including guidelines for designing semantic data and interoperability of resources. We consequently developed tools and clients for analysis and visualization. Conclusion We provide a meeting report from BioHackathon 2010, in which we describe the discussions, decisions, and breakthroughs made as we moved towards compliance with Semantic Web technologies - from source provider, through middleware, to the end-consumer.

Published
2013

16. Changing computational research. The challenges ahead.

Author

Neylon, Cameron, Aerts, Jan, Brown, C, Coles, Simon J, Hatton, Les, Lemire, Daniel, Millman, K, Murray-Rust, Peter, Perez, Fernando, Saunders, Neil, Shah, Nigam, Smith, Arfon, Varoquaux, Gaël, and Willighagen, Egon

Abstract

AbstractNo abstract - Editorial

Published
2012

17. The 2nd DBCLS BioHackathon: interoperable bioinformatics Web services for integrated applications

Author

Katayama, Toshiaki, Wilkinson, Mark D, Vos, Rutger, Kawashima, Takeshi, Kawashima, Shuichi, Nakao, Mitsuteru, Yamamoto, Yasunori, Chun, Hong-Woo, Yamaguchi, Atsuko, Kawano, Shin, Aerts, Jan, Aoki-Kinoshita, Kiyoko F, Arakawa, Kazuharu, Aranda, Bruno, Bonnal, Raoul JP, Fernández, José M, Fujisawa, Takatomo, Gordon, Paul MK, Goto, Naohisa, Haider, Syed, Harris, Todd, Hatakeyama, Takashi, Ho, Isaac, Itoh, Masumi, Kasprzyk, Arek, Kido, Nobuhiro, Kim, Young-Joo, Kinjo, Akira R, Konishi, Fumikazu, Kovarskaya, Yulia, von Kuster, Greg, Labarga, Alberto, Limviphuvadh, Vachiranee, McCarthy, Luke, Nakamura, Yasukazu, Nam, Yunsun, Nishida, Kozo, Nishimura, Kunihiro, Nishizawa, Tatsuya, Ogishima, Soichi, Oinn, Tom, Okamoto, Shinobu, Okuda, Shujiro, Ono, Keiichiro, Oshita, Kazuki, Park, Keun-Joon, Putnam, Nicholas, Senger, Martin, Severin, Jessica, Shigemoto, Yasumasa, Sugawara, Hideaki, Taylor, James, Trelles, Oswaldo, Yamasaki, Chisato, Yamashita, Riu, Satoh, Noriyuki, and Takagi, Toshihisa

Abstract

Abstract Background The interaction between biological researchers and the bioinformatics tools they use is still hampered by incomplete interoperability between such tools. To ensure interoperability initiatives are effectively deployed, end-user applications need to be aware of, and support, best practices and standards. Here, we report on an initiative in which software developers and genome biologists came together to explore and raise awareness of these issues: BioHackathon 2009. Results Developers in attendance came from diverse backgrounds, with experts in Web services, workflow tools, text mining and visualization. Genome biologists provided expertise and exemplar data from the domains of sequence and pathway analysis and glyco-informatics. One goal of the meeting was to evaluate the ability to address real world use cases in these domains using the tools that the developers represented. This resulted in i) a workflow to annotate 100,000 sequences from an invertebrate species; ii) an integrated system for analysis of the transcription factor binding sites (TFBSs) enriched based on differential gene expression data obtained from a microarray experiment; iii) a workflow to enumerate putative physical protein interactions among enzymes in a metabolic pathway using protein structure data; iv) a workflow to analyze glyco-gene-related diseases by searching for human homologs of glyco-genes in other species, such as fruit flies, and retrieving their phenotype-annotated SNPs. Conclusions Beyond deriving prototype solutions for each use-case, a second major purpose of the BioHackathon was to highlight areas of insufficiency. We discuss the issues raised by our exploration of the problem/solution space, concluding that there are still problems with the way Web services are modeled and annotated, including: i) the absence of several useful data or analysis functions in the Web service "space"; ii) the lack of documentation of methods; iii) lack of compliance with the SOAP/WSDL specification among and between various programming-language libraries; and iv) incompatibility between various bioinformatics data formats. Although it was still difficult to solve real world problems posed to the developers by the biological researchers in attendance because of these problems, we note the promise of addressing these issues within a semantic framework.

Published
2011

18. The DBCLS BioHackathon: standardization and interoperability for bioinformatics web services and workflows

Author

Katayama, Toshiaki, Arakawa, Kazuharu, Nakao, Mitsuteru, Ono, Keiichiro, Aoki-Kinoshita, Kiyoko F, Yamamoto, Yasunori, Yamaguchi, Atsuko, Kawashima, Shuichi, Chun, Hong-Woo, Aerts, Jan, Aranda, Bruno, Barboza, Lord, Bonnal, Raoul JP, Bruskiewich, Richard, Bryne, Jan C, Fernández, José M, Funahashi, Akira, Gordon, Paul MK, Goto, Naohisa, Groscurth, Andreas, Gutteridge, Alex, Holland, Richard, Kano, Yoshinobu, Kawas, Edward A, Kerhornou, Arnaud, Kibukawa, Eri, Kinjo, Akira R, Kuhn, Michael, Lapp, Hilmar, Lehvaslaiho, Heikki, Nakamura, Hiroyuki, Nakamura, Yasukazu, Nishizawa, Tatsuya, Nobata, Chikashi, Noguchi, Tamotsu, Oinn, Thomas M, Okamoto, Shinobu, Owen, Stuart, Pafilis, Evangelos, Pocock, Matthew, Prins, Pjotr, Ranzinger, René, Reisinger, Florian, Salwinski, Lukasz, Schreiber, Mark, Senger, Martin, Shigemoto, Yasumasa, Standley, Daron M, Sugawara, Hideaki, Tashiro, Toshiyuki, Trelles, Oswaldo, Vos, Rutger A, Wilkinson, Mark D, York, William, Zmasek, Christian M, Asai, Kiyoshi, and Takagi, Toshihisa

Abstract

Abstract Web services have become a key technology for bioinformatics, since life science databases are globally decentralized and the exponential increase in the amount of available data demands for efficient systems without the need to transfer entire databases for every step of an analysis. However, various incompatibilities among database resources and analysis services make it difficult to connect and integrate these into interoperable workflows. To resolve this situation, we invited domain specialists from web service providers, client software developers, Open Bio* projects, the BioMoby project and researchers of emerging areas where a standard exchange data format is not well established, for an intensive collaboration entitled the BioHackathon 2008. The meeting was hosted by the Database Center for Life Science (DBCLS) and Computational Biology Research Center (CBRC) and was held in Tokyo from February 11th to 15th, 2008. In this report we highlight the work accomplished and the common issues arisen from this event, including the standardization of data exchange formats and services in the emerging fields of glycoinformatics, biological interaction networks, text mining, and phyloinformatics. In addition, common shared object development based on BioSQL, as well as technical challenges in large data management, asynchronous services, and security are discussed. Consequently, we improved interoperability of web services in several fields, however, further cooperation among major database centers and continued collaborative efforts between service providers and software developers are still necessary for an effective advance in bioinformatics web service technologies.

Published
2010

21. A Method to Exploit the Structure of Genetic Ancestry Space to Enhance Case-Control Studies

Author

Barclay, Murray, Peyrin-Biroulet, Laurent, Chamaillard, Mathias, Colombel, Jean-Frederick, Cottone, Mario, Croft, Anthony, D’Incà, Renata, Halfvarson, Jonas, Hanigan, Katherine, Henderson, Paul, Hugot, Jean-Pierre, Karban, Amir, Kennedy, Nicholas A., Khan, Mohammed Azam, Lémann, Marc, Levine, Arie, Massey, Dunecan, Milla, Monica, Montgomery, Grant W., Ng, Sok Meng Evelyn, Oikonomou, Ioannis, Peeters, Harald, Proctor, Deborah D., Rahier, Jean-Francois, Roberts, Rebecca, Rutgeerts, Paul, Seibold, Frank, Stronati, Laura, Taylor, Kirstin M., Törkvist, Leif, Ublick, Kullak, Van Limbergen, Johan, Van Gossum, Andre, Vatn, Morten H., Zhang, Hu, Zhang, Wei, Andrews, Jane M., Bampton, Peter A., Florin, Timothy H., Gearry, Richard, Krishnaprasad, Krupa, Lawrance, Ian C., Mahy, Gillian, Radford-Smith, Graham, Roberts, Rebecca L., Simms, Lisa A., Amininijad, Leila, Cleynen, Isabelle, Dewit, Olivier, Franchimont, Denis, Georges, Michel, Laukens, Debby, Theatre, Emilie, Van Gossum, André, Vermeire, Severine, Aumais, Guy, Baidoo, Leonard, Barrie, Arthur M., III, Beck, Karen, Bernard, Edmond-Jean, Binion, David G., Bitton, Alain, Brant, Steve R., Cho, Judy H., Cohen, Albert, Croitoru, Kenneth, Daly, Mark J., Datta, Lisa W., Deslandres, Colette, Duerr, Richard H., Dutridge, Debra, Ferguson, John, Fultz, Joann, Goyette, Philippe, Greenberg, Gordon R., Haritunians, Talin, Jobin, Gilles, Katz, Seymour, Lahaie, Raymond G., McGovern, Dermot P., Nelson, Linda, Ng, Sok Meng, Ning, Kaida, Paré, Pierre, Regueiro, Miguel D., Rioux, John D., Ruggiero, Elizabeth, Schumm, L. Philip, Schwartz, Marc, Scott, Regan, Sharma, Yashoda, Silverberg, Mark S., Spears, Denise, Steinhart, A. Hillary, Stempak, Joanne M., Swoger, Jason M., Tsagarelis, Constantina, Zhang, Clarence, Zhao, Hongyu, Aerts, Jan, Ahmad, Tariq, Arbury, Hazel, Attwood, Anthony, Auton, Adam, Ball, Stephen G., Balmforth, Anthony J., Barnes, Chris, Barrett, Jeffrey C., Barroso, Inês, Barton, Anne, Bennett, Amanda J., Bhaskar, Sanjeev, Blaszczyk, Katarzyna, Bowes, John, Brand, Oliver J., Braund, Peter S., Bredin, Francesca, Breen, Gerome, Brown, Morris J., Bruce, Ian N., Bull, Jaswinder, Burren, Oliver S., Burton, John, Byrnes, Jake, Caesar, Sian, Cardin, Niall, Clee, Chris M., Coffey, Alison J., Connell, John M.C., Conrad, Donald F., Cooper, Jason D., Dominiczak, Anna F., Downes, Kate, Drummond, Hazel E., Dudakia, Darshna, Dunham, Andrew, Ebbs, Bernadette, Eccles, Diana, Edkins, Sarah, Edwards, Cathryn, Elliot, Anna, Emery, Paul, Evans, David M., Evans, Gareth, Eyre, Steve, Farmer, Anne, I, Ferrier, Nicol, Flynn, Edward, Forbes, Alistair, Forty, Liz, Franklyn, Jayne A., Frayling, Timothy M., Freathy, Rachel M., Giannoulatou, Eleni, Gibbs, Polly, Gilbert, Paul, Gordon-Smith, Katherine, Gray, Emma, Green, Elaine, Groves, Chris J., Grozeva, Detelina, Gwilliam, Rhian, Hall, Anita, Hammond, Naomi, Hardy, Matt, Harrison, Pile, Hassanali, Neelam, Hebaishi, Husam, Hines, Sarah, Hinks, Anne, Hitman, Graham A., Hocking, Lynne, Holmes, Chris, Howard, Eleanor, Howard, Philip, Howson, Joanna M.M., Hughes, Debbie, Hunt, Sarah, Isaacs, John D., Jain, Mahim, Jewell, Derek P., Johnson, Toby, Jolley, Jennifer D., Jones, Ian R., Jones, Lisa A., Kirov, George, Langford, Cordelia F., Lango-Allen, Hana, Lathrop, G. Mark, Lee, James, Lee, Kate L., Lees, Charlie, Lewis, Kevin, Lindgren, Cecilia M., Maisuria-Armer, Meeta, Maller, Julian, Mansfield, John, Marchini, Jonathan L., Martin, Paul, Massey, Dunecan C.O., McArdle, Wendy L., McGuffin, Peter, McLay, Kirsten E., McVean, Gil, Mentzer, Alex, Mimmack, Michael L., Morgan, Ann E., Morris, Andrew P., Mowat, Craig, Munroe, Patricia B., Myers, Simon, Newman, William, Nimmo, Elaine R., O’Donovan, Michael C., Onipinla, Abiodun, Ovington, Nigel R., Owen, Michael J., Palin, Kimmo, Palotie, Aarno, Parnell, Kirstie, Pearson, Richard, Pernet, David, Perry, John R.B., Phillips, Anne, Plagnol, Vincent, Prescott, Natalie J., Prokopenko, Inga, Quail, Michael A., Rafelt, Suzanne, Rayner, Nigel W., Reid, David M., Renwick, Anthony, Ring, Susan M., Robertson, Neil, Robson, Samuel, Russell, Ellie, St Clair, David, Sambrook, Jennifer G., Sanderson, Jeremy D., Sawcer, Stephen J., Schuilenburg, Helen, Scott, Carol E., Scott, Richard, Seal, Sheila, Shaw-Hawkins, Sue, Shields, Beverley M., Simmonds, Matthew J., Smyth, Debbie J., Somaskantharajah, Elilan, Spanova, Katarina, Steer, Sophia, Stephens, Jonathan, Stevens, Helen E., Stirrups, Kathy, Stone, Millicent A., Strachan, David P., Su, Zhan, Symmons, Deborah P.M., Thompson, John R., Thomson, Wendy, Tobin, Martin D., Travers, Mary E., Turnbull, Clare, Vukcevic, Damjan, Wain, Louise V., Walker, Mark, Walker, Neil M., Wallace, Chris, Warren-Perry, Margaret, Watkins, Nicholas A., Webster, John, Weedon, Michael N., Wilson, Anthony G., Woodburn, Matthew, Wordsworth, B. Paul, Yau, Chris, Young, Allan H., Zeggini, Eleftheria, Brown, Matthew A., Burton, Paul R., Caulfield, Mark J., Compston, Alastair, Farrall, Martin, Gough, Stephen C.L., Hall, Alistair S., Hattersley, Andrew T., Hill, Adrian V.S., Mathew, Christopher G., Pembrey, Marcus, Satsangi, Jack, Stratton, Michael R., Worthington, Jane, Hurles, Matthew E., Duncanson, Audrey, Ouwehand, Willem H., Parkes, Miles, Rahman, Nazneen, Todd, John A., Samani, Nilesh J., Kwiatkowski, Dominic P., McCarthy, Mark I., Craddock, Nick, Deloukas, Panos, Donnelly, Peter, Blackwell, Jenefer M., Bramon, Elvira, Casas, Juan P., Corvin, Aiden, Jankowski, Janusz, Markus, Hugh S., Palmer, Colin N.A., Plomin, Robert, Rautanen, Anna, Trembath, Richard C., Viswanathan, Ananth C., Wood, Nicholas W., Spencer, Chris C.A., Band, Gavin, Bellenguez, Céline, Freeman, Colin, Hellenthal, Garrett, Pirinen, Matti, Strange, Amy, Blackburn, Hannah, Bumpstead, Suzannah J., Dronov, Serge, Gillman, Matthew, Jayakumar, Alagurevathi, McCann, Owen T., Liddle, Jennifer, Potter, Simon C., Ravindrarajah, Radhi, Ricketts, Michelle, Waller, Matthew, Weston, Paul, Widaa, Sara, Whittaker, Pamela, Bodea, Corneliu A., Neale, Benjamin M., Ripke, Stephan, Devlin, Bernie, and Roeder, Kathryn

Published
2016
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22. A spatial model to jointly analyze self-reported survey data of COVID-19 symptoms and official COVID-19 incidence data

Author

Vranckx, Maren, Faes, Christel, Molenberghs, Geert, Hens, Niel, Beutels, Philippe, Van Damme, Pierre, Aerts, Jan, Petrof, Oana, Pepermans, Koen, Neyens, Thomas, Beutels, Philippe/0000-0001-5034-3595, Neyens, Thomas/0000-0003-2364-7555, Pepermans, Koen/0000-0001-7294-9491, Petrof, Oana/0000-0002-1802-9640, HENS, Niel, Beutels, Philippe, Pepermans, Koen, MOLENBERGHS, Geert, Van Damme , Pierre, NEYENS, Thomas, VRANCKX, Maren, PETROF, Oana, FAES, Christel, and AERTS, Jan

Subjects
Statistics and Probability, Computer. Automation, preferential sampling, disease mapping, COVID-19, General Medicine, Statistics, Probability and Uncertainty, Biology, bivariate conditional autoregressive random effect, survey data, Mathematics
Abstract

This work presents a joint spatial modeling framework to improve estimation of the spatial distribution of the latent COVID-19 incidence in Belgium, based on test-confirmed COVID-19 cases and crowd-sourced symptoms data as reported in a large-scale online survey. Correction is envisioned for stochastic dependence between the survey's response rate and spatial COVID-19 incidence, commonly known as preferential sampling, but not found significant. Results show that an online survey can provide valuable auxiliary data to optimize spatial COVID-19 incidence estimation based on confirmed cases in situations with limited testing capacity. Furthermore, it is shown that an online survey on COVID-19 symptoms with a sufficiently large sample size per spatial entity is capable of pinpointing the same locations that appear as test-confirmed clusters, approximately 1 week earlier. We conclude that a large-scale online study provides an inexpensive and flexible method to collect timely information of an epidemic during its early phase, which can be used by policy makers in an early phase of an epidemic and in conjunction with other monitoring systems. The resources and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation - Flanders (FWO) and the Flemish Government. The data used in this manuscript were provided by the Belgian public health institute (Sciensano). This research received funding from the Flemish Government (AI Research Program). Authors Beutels, Faes, and Hens acknowledge funding from the European Union’s Horizon 2020 research and innovation programme - project EpiPose (No. 101003688). Authors Beutels, Hens, Neyens, and Van Damme acknowledge funding from the Research Foundation Flanders (No. G0G1920N). Authors Faes and Neyens acknowledge funding from the Research Foundation Flanders (No. G0G9820N). Author Neyens acknowledges funding by the Internal Funds KU Leuven (project number 3M190682).

Published
2023

23. Challenges and Opportunities in Data Visualization Education: A Call to Action

Author

Bach, Benjamin, primary, Keck, Mandy, additional, Rajabiyazdi, Fateme, additional, Losev, Tatiana, additional, Meirelles, Isabel, additional, Dykes, Jason, additional, Laramee, Robert S., additional, AlKadi, Mashael, additional, Stoiber, Christina, additional, Huron, Samuel, additional, Perin, Charles, additional, Morais, Luiz, additional, Aigner, Wolfgang, additional, Kosminsky, Doris, additional, Boucher, Magdalena, additional, Knudsen, Søren, additional, Manataki, Areti, additional, Aerts, Jan, additional, Hinrichs, Uta, additional, Roberts, Jonathan C., additional, and Carpendale, Sheelagh, additional

Published
2023
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24. Introducing evolutionary biologists to the analysis of big data: guidelines to organize extended bioinformatics training courses

Author

Faria, Rui, Triant, Deborah, Perdomo-Sabogal, Alvaro, Overduin, Bert, Bleidorn, Christoph, Santana, Clara Isabel Bermudez, Langenberger, David, Dall’Olio, Giovanni Marco, Indrischek, Henrike, Aerts, Jan, Engelhardt, Jan, Engelken, Johannes, Liebal, Katja, Fasold, Mario, Robb, Sofia, Grath, Sonja, Kolora, Sree Rohit Raj, Carvalho, Tiago, Salzburger, Walter, Jovanovic, Vladimir, and Nowick, Katja

Published
2018
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25. Challenges and Opportunities in Data Visualization Education: A Call to Action

Author

Bach, Benjamin, Keck, Mandy, Rajabiyazdi, Fateme, Losev, Tatiana, Meirelles, Isabel, Dykes, Jason, Laramee, Robert S., AlKadi, Mashael, Stoiber, Christina, Huron, Samuel, Perin, Charles, Morais, Luiz, Aigner, Wolfgang, Kosminsky, Doris, Boucher, Magdalena, Knudsen, Soren, Manataki, Areti, Aerts, Jan, Hinrichs, Uta, Roberts, Jonathan C., and Carpendale, Sheelagh

Abstract

This paper is a call to action for research and discussion on data visualization education. As visualization evolves and spreads through our professional and personal lives, we need to understand how to support and empower a broad and diverse community of learners in visualization. Data Visualization is a diverse and dynamic discipline that combines knowledge from different fields, is tailored to suit diverse audiences and contexts, and frequently incorporates tacit knowledge. This complex nature leads to a series of interrelated challenges for data visualization education. Driven by a lack of consolidated knowledge, overview, and orientation for visualization education, the 21 authors of this paper—educators and researchers in data visualization—identify and describe 19 challenges informed by our collective practical experience. We organize these challenges around seven themes People, Goals & Assessment, Environment, Motivation, Methods, Materials, and Change. Across these themes, we formulate 43 research questions to address these challenges. As part of our call to action, we then conclude with 5 cross-cutting opportunities and respective action items: embrace DIVERSITY+INCLUSION, build COMMUNITIES, conduct RESEARCH, act AGILE, and relish RESPONSIBILITY. We aim to inspire researchers, educators and learners to drive visualization education forward and discuss why, how, who and where we educate, as we learn to use visualization to address challenges across many scales and many domains in a rapidly changing world: viseducationchallenges.github.io.

Published
2024
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27. A joint spatial model to analyse self-reported survey data of COVID-19 symptoms and lagged surveillance-based COVID-19 incidence data

Author

Vranckx, Maren, Faes, Christel, Molenberghs, Geert, Niel Hens, Beutels, Philippe, Van Damme, Pierre, Aerts, Jan, Petrof, Oana, Pepermans, Koen, and Neyens, Thomas

Subjects
Preferential sampling, COVID-19, Disease mapping, Bivariate conditional autoregressive random effect, survey data
Abstract

These datasets contain model results based on a synthetic data analysis and can be downloaded to be used in the supplementary material code of thispaper,with the following abstract: This work presents a joint spatial modelling framework to improve estimation of the spatial distribution of the latent COVID-19 incidence in Belgium, based on test-confirmed COVID-19 cases and crowd-sourced symptoms data as reported in a large-scale online survey. Correction is envisioned for stochastic dependence between the survey's response rate and spatial COVID-19 incidence, commonly known as preferential sampling, but not found significant. Results show that an online survey can provide valuable auxiliary data to optimise spatial COVID-19 incidence estimation based on confirmed cases in situations with limited testing capacity. Furthermore, it is shown that an online survey on COVID-19 symptoms with a sufficiently large sample size per spatial entity is capable of pinpointing the same locations that appear as test-confirmed clusters, approximately one week earlier. We conclude that a large-scale online study provides an inexpensive and flexible method to collect timely information of an epidemic during its early phase, which can be used by policy makers in an early phase of an epidemic and in conjunction with other monitoring systems.

Published
2022
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28. MOBS - Multi-Omics Brush for Subgraph Visualisation

Author

Heylen, Dries, Peeters, Jannes, Ertaylan, Gökhan, Hooyberghs, Jef, and Aerts, Jan

Subjects
Visualization toolkits, Human centered computing, +Visualization+toolkits%22">CCS Concepts: Human-centered computing --> Visualization toolkits, Graph drawings
Abstract

One of the big opportunities in multi-omics analysis is the identification of interactions between molecular entities and their association with diseases. In analyzing and expressing these interactions in the search for new hypotheses, multi-omics data is often either translated into matrices containing pairwise correlations and distances, or visualized as node-link diagrams. A major problem when visualizing large networks however is the occurrence of hairball-like graphs, from which little to none information can be extracted. It is of interest to investigate subgroups of markers that are closely associated with each other, rather than just looking at the overload of all interactions. Hence, we propose MOBS (Multi-Omics Brush for Subgraph visualisation), a web-based visualisation interface that can provide both an overview and detailed views on the data. By means of a two dimensional brush on a heatmap that includes hierarchical clustering, relationships of interest can be extracted from a fully connected graph, to enable detailed analysis of the subgraph of interest., Posters, Dries Heylen, Jannes Peeters, Gökhan Ertaylan, Jef Hooyberghs, and Jan Aerts

Published
2022
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30. Exploring the Microbiome Analysis and Visualization Landscape

Author

PEETERS, Jannes, THAS, Olivier, SHKEDY, Ziv, KODALCI, Leyla, MUSISI, Connie, OWOKOTOMO, Olajumoke Evangelina, DYCZKO, Aleksandra, HAMAD, Ibrahim, VANGRONSVELD, Jaco, KLEINEWIETFELD, Markus, THIJS, Sofie, AERTS, Jan, PEETERS, Jannes, THAS, Olivier, SHKEDY, Ziv, KODALCI, Leyla, MUSISI, Connie, OWOKOTOMO, Olajumoke Evangelina, DYCZKO, Aleksandra, HAMAD, Ibrahim, VANGRONSVELD, Jaco, KLEINEWIETFELD, Markus, THIJS, Sofie, and AERTS, Jan

Subjects
data analysis, microbiome, data visualization, biostatistics, visual analytics, bioinformatcs
Abstract

Research on the microbiome has boomed recently, which resulted in a wide range of tools, packages, and algorithms to analyze microbiome data. Here we investigate and map currently existing tools that can be used to perform visual analysis on the microbiome, and associate the including methods, visual representations and data features to the research objectives currently of interest in microbiome research. The analysis is based on a combination of a literature review and workshops including a group of domain experts. Both the reviewing process and workshops are based on domain characterization methods to facilitate communication and collaboration between researchers from different disciplines. We identify several research questions related to microbiomes, and describe how different analysis methods and visualizations help in tackling them.

Published
2021

31. De integratie van artistiek en ontwerpend onderzoek binnen een academische context

Author

BESSEMANS, Ann, PINT, Kris, AERTS, Jan, BESSEMANS, Ann, PINT, Kris, and AERTS, Jan

Abstract

De koppeling van architectuur-en kunstopleidingen aan een universitaire partner, een neveneffect van de Bologna-verklaring uit 1999, maakte een nieuw onderzoeksdomein mogelijk: het onderzoek in de kunsten. Onder dit nieuwe domein vallen een hele reeks aan uiteenlopende disciplines, zoals architectuur, beeldende en audiovisuele kunsten, muziek en podiumkunsten. Een opvallende uitzondering is literatuur: creative writing is hier, in tegenstelling tot het buitenland, geen volwaardige masteropleiding. Op zich was dit nieuwe domein een logische consequentie van het nieuwe Europese onderwijsmodel: een professionele bachelor richt zich rechtstreeks tot de arbeidsmarkt, een academische master heeft de ambitie om studenten een bredere horizon aan te bieden en hen in staat te stellen hun eigen vakgebied verder te onderzoeken. Wie een masterdiploma heeft, kan ook een derde cyclus starten en voor een doctoraatstitel gaan. Dat maakte dan weer de uitbouw van een actieve onderzoeksomgeving nodig. Voor architectuur is die integratie in de Vlaamse universiteiten ondertussen gebeurd. Voor de kunstopleidingen zit enkel het deel dat zich richt op fundamenteel onderzoek binnen de universiteit, wat uiteraard een wat vreemde constructie blijft. In principe kreeg artistiek en ontwerpend onderzoek zo een gelijkwaardige plaats naast de humane wetenschappen, de sociale wetenschappen en de natuur-en exacte wetenschappen. Het biedt een aanvullend kader om de complexiteit van de werkelijkheid te verkennen, in een pluralistische academische context waarin zowel godsdienstwetenschappen als deeltjesfysica hun plaats hebben. Het probleem was en is uiteraard de concrete vertaling van dit onderzoek naar de geijkte kanalen van wetenschappelijke output, vooral dan doctoraten en peer-reviewed publicaties. Dat was zeker in het begin niet evident, omdat er aanvankelijk in Vlaanderen weinig tot geen peers waren. Kunstenaars en ontwerpers konden zich haast uitsluitend laten begeleiden en beoordelen door mensen uit een ander vakgebied. Ondertussen zijn die Vlaamse collega's er wel. Zo kregen ondertussen enkele doctores in de kunsten een deeltijdse aanstelling aan de Universiteit Hasselt, wat hen in staat stelt als promotor op te treden voor artistiek en ontwerpmatig onderzoek. Hierdoor kunnen doctoraatsjury's en evaluatiecommissies evenwichtiger worden samengesteld en zijn er de afgelopen jaren ook academische tijdschriften opgericht voor artistiek onderzoek en artistieke onderzoeksmethodes, zoals het Journal of Artistic Research en in ons land, Forum+ en COLLATERAL-Online Journal for Cross-Cultural Close Reading.

Published
2021

33. COVID-19 mortality, excess mortality, deaths per million and infection fatality ratio, Belgium, 9 March 2020 to 28 June 2020

Author

Molenberghs, Geert, primary, Faes, Christel, additional, Verbeeck, Johan, additional, Deboosere, Patrick, additional, Abrams, Steven, additional, Willem, Lander, additional, Aerts, Jan, additional, Theeten, Heidi, additional, Devleesschauwer, Brecht, additional, Bustos Sierra, Natalia, additional, Renard, Françoise, additional, Herzog, Sereina, additional, Lusyne, Patrick, additional, Van der Heyden, Johan, additional, Van Oyen, Herman, additional, Van Damme, Pierre, additional, and Hens, Niel, additional

Published
2022
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34. Exploring the Microbiome Analysis and Visualization Landscape

Author

Peeters, Jannes, primary, Thas, Olivier, additional, Shkedy, Ziv, additional, Kodalci, Leyla, additional, Musisi, Connie, additional, Owokotomo, Olajumoke Evangelina, additional, Dyczko, Aleksandra, additional, Hamad, Ibrahim, additional, Vangronsveld, Jaco, additional, Kleinewietfeld, Markus, additional, Thijs, Sofie, additional, and Aerts, Jan, additional

Published
2021
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38. The Genome Sequence of Taurine Cattle: A Window to Ruminant Biology and Evolution

Author

Elsik, Christine G., Tellam, Ross L., Worley, Kim C., Gibbs, Richard A., Elsik, Christine G., Tellam, Ross L, Gibbs, Richard A., Muzny, Donna M., Weinstock, George M., Adelson, David L, Eichler, Evan E., Elnitski, Laura, Elsik, Christine G., Guigó, Roderic, Hamernik, Debora L., Kappes, Steve M., Lewin, Harris A, Lynn, David J., Nicholas, Frank W., Reymond, Alexandre, Rijnkels, Monique, Skow, Loren C., Tellam, Ross L, Worley, Kim C., Zdobnov, Evgeny M., Gibbs, Richard A., Kappes, Steve M., Schook, Lawrence, Skow, Loren C., Weinstock, George M., Womack, James, Alioto, Tyler, Antonarakis, Stylianos E., Astashyn, Alex, Chapple, Charles E., Chen, Hsiu-Chuan, Chrast, Jacqueline, Câmara, Francisco, Elsik, Christine G., Ermolaeva, Olga, Guigó, Roderic, Henrichsen, Charlotte N., Hlavina, Wratko, Kapustin, Yuri, Kiryutin, Boris, Kitts, Paul, Kokocinski, Felix, Landrum, Melissa, Maglott, Donna, Pruitt, Kim, Reymond, Alexandre, Sapojnikov, Victor, Searle, Stephen M., Solovyev, Victor, Souvorov, Alexandre, Ucla, Catherine, Weinstock, George M., Wyss, Carine, Alioto, Tyler, Antonarakis, Stylianos E., Chapple, Charles E., Chrast, Jacqueline, Câmara, Francisco, Guigó, Roderic, Henrichsen, Charlotte N., Reymond, Alexandre, Ucla, Catherine, Wyss, Carine, Anzola, Juan M., Gerlach, Daniel, Zdobnov, Evgeny M., Elhaik, Eran, Elsik, Christine G., Graur, Dan, Reese, Justin T., Adelson, David L., Edgar, Robert C., McEwan, John C., Payne, Gemma M., Raison, Joy M., Junier, Thomas, Kriventseva, Evgenia V., Zdobnov, Evgeny M., Chrast, Jacqueline, Eyras, Eduardo, Henrichsen, Charlotte N., Plass, Mireya, Reymond, Alexandre, Donthu, Ravikiran, Larkin, Denis M., Lewin, Harris A., Nicholas, Frank W., Elnitski, Laura, Larkin, Denis M., Lewin, Harris A., Reecy, James, Yang, Mary Q., Adelson, David L, Chen, Lin, Cheng, Ze, Chitko-McKown, Carol G., Eichler, Evan E., Elnitski, Laura, Elsik, Christine G., Liu, George E., Matukumalli, Lakshmi K., Song, Jiuzhou, Zhu, Bin, Elsik, Christine G., Lynn, David J., Reese, Justin T., Bradley, Daniel G., Brinkman, Fiona S.L, Lau, Lilian P.L., Lynn, David J., Whiteside, Matthew D., Tellam, Ross L, Walker, Angela, Wheeler, Thomas T., Casey, Theresa, German, Bruce J., Lemay, Danielle G., Lynn, David J., Maqbool, Nauman J., Molenaar, Adrian J., Rijnkels, Monique, Lewin, Harris A., Seo, Seongwon, Stothard, Paul, Baldwin, Cynthia L., Baxter, Rebecca, Brinkmeyer-Langford, Candice L., Brown, Wendy C., Childers, Christopher P., Connelley, Timothy, Ellis, Shirley A., Fritz, Krista, Glass, Elizabeth J., Herzig, Carolyn T.A., livanainen, Antti, Lahmers, Kevin K., Skow, Loren C., Bennett, Anna K., Childers, Christopher P., Dickens, Michael C., Elsik, Christine G., Gilbert, James G.R., Hagen, Darren E., Reese, Justin T., Salih, Hanni, Aerts, Jan, Caetano, Alexandre R., Dalrymple, Brian, Elsik, Christine G., Fernando Garcia, Jose, Gibbs, Richard A., Gill, Clare A., Hamernik, Debora L, Hiendleder, Stefan G., Memili, Erdogan, Nicholas, Frank W., Reecy, James, Rijnkels, Monique, Skow, Loren C., Spurlock, Diane, Stothard, Paul, Tellam, Ross L, Weinstock, George M., Williams, John L, Worley, Kim C., Alexander, Lee, Brownstein, Michael J., Guan, Leluo, Holt, Robert A., Jones, Steven J.M., Marra, Marco A., Moore, Richard, Moore, Stephen S., Roberts, Andy, Taniguchi, Masaaki, Waterman, Richard C., Chacko, Joseph, Chandrabose, Mimi M., Cree, Andy, Diep Dao, Marvin, Dinh, Huyen H., Ayiesha Gabisi, Ramatu, Hines, Sandra, Hume, Jennifer, Jhangiani, Shalini N., Joshi, Vandita, Kovar, Christie L., Lewis, Lora R., Liu, Yih-shin, Lopez, John, Morgan, Margaret B., Muzny, Donna M., Bich Nguyen, Ngoc, Okwuonu, Geoffrey O., Ruiz, San Juana, Santibanez, Jireh, Wright, Rita A., Buhay, Christian, Ding, Yan, Dugan-Rocha, Shannon, Herdandez, Judith, Holder, Michael, Sabo, Aniko, Egan, Amy, Goodell, Jason, Wilczek-Boney, Katarzyna, Fowler, Gerald R., Edward Hitchens, Matthew, Lozado, Ryan J., Moen, Charles, Steffen, David, Warren, James T., Zhang, Jingkun, Chiu, Readman, Jones, Steven J.M., Marra, Marco A., Schein, Jacqueline E., James Durbin, K., Havlak, Paul, Jiang, Huaiyang, Liu, Yue, Qin, Xiang, Ren, Yanru, Shen, Yufeng, Song, Henry, Weinstock, George M., Worley, Kim C., Nicole Bell, Stephanie, Davis, Clay, Jolivet Johnson, Angela, Lee, Sandra, Nazareth, Lynne V., Patel, Bella Mayurkumar, Pu, Ling-Ling, Vattathil, Selina, Williams, Rex Lee, Jr., Curry, Stacey, Hamilton, Cerissa, Sodergren, Erica, Nazareth, Lynne V., Wheeler, David A., Adelson, David L, Aerts, Jan, Barris, Wes, Bennett, Gary L, Dalrymple, Brian, Eggen, André, Gill, Clare A., Green, Ronnie D., Harhay, Gregory P., Hobbs, Matthew, Jann, Oliver, Kappes, Steve M., Keele, John W., Kent, Matthew P., Larkin, Denis M., Lewin, Harris A., Lien, Sigbjørn, McEwan, John C., McKay, Stephanie D., McWilliam, Sean, Moore, Stephen S., Nicholas, Frank W., Payne, Gemma M., Ratnakumar, Abhirami, Salih, Hanni, Schnabel, Robert D., Smith, Timothy, Snelling, Warren M., Sonstegard, Tad S., Stone, Roger T., Sugimoto, Yoshikazu, Takasuga, Akiko, Taylor, Jeremy F., Tellam, Ross L., Van Tassell, Curtis P., Williams, John L, MacNeil, Michael D., Abatepaulo, Antonio R.R., Abbey, Colette A., Aerts, Jan, Ahola, Virpi, Almeida, Iassudara G., Amadio, Ariel F., Anatriello, Elen, Bahadue, Suria M., Baldwin, Cynthia L., Baxter, Rebecca, Bennett, Anna K., Biase, Fernando H., Boldt, Clayton R., Brinkmeyer-Langford, Candice L, Brown, Wendy C., Caetano, Alexandre R., Carroll, Jeffery A., Carvalho, Wanessa A, Casey, Theresa, Cervelatti, Eliane P., Chacko, Elsa, Chapin, Jennifer E., Cheng, Ye, Childers, Christopher P., Choi, Jungwoo, Colley, Adam J., Connelley, Timothy, de Campos, Tatiana A., De Donato, Marcos, de Miranda Santos, Isabel K.F., de Oliveira, Carlo J.F., Deobald, Heather, Devinoy, Eve, Dickens, Michael C., Donohue, Kaitlin E., Dovc, Peter, Eberlein, Annett, Ellis, Shirley A., Fitzsimmons, Carolyn J., Franzin, Alessandra M., Fritz, Krista, Garcia, Gustavo R., Fernando Garcia, Jose, Genini, Sem, German, Bruce J., Gilbert, James G.R., Gill, Clare A., Gladney, Cody J., Glass, Elizabeth J., Grant, Jason R., Greaser, Marion L., Green, Jonathan A., Hadsell, Darryl L., Hagen, Darren E., Hakimov, Hatam A., Halgren, Rob, Harrow, Jennifer L, Hart, Elizabeth A., Hastings, Nicola, Hernandez, Marta, Herzig, Carolyn T.A., Hiendleder, Stefan G., Hobbs, Matthew, Hu, Zhi-Liang, livanainen, Antti, Ingham, Aaron, Iso-Touru, Terhi, Jamis, Catherine, Jann, Oliver, Jensen, Kirsty, Kapetis, Dimos, Kerr, Tovah, Khalil, Sari S., Khatib, Hasan, Kolbehdari, Davood, Kumar, Charu G., Kumar, Dinesh, Leach, Richard, Lee, Justin C-M, Lemay, Danielle G., Li, Changxi, Liu, George E., Logan, Krystin M., Malinverni, Roberto, Maqbool, Nauman J., Marques, Elisa, Martin, William F., Martins, Natalia F., Maruyama, Sandra R., Mazza, Raffaele, McLean, Kim L, Medrano, Juan F., Memili, Erdogan, Molenaar, Adrian J., Moreno, Barbara T., Moré, Daniela D., Muntean, Carl T., Nandakumar, Hari P., Nogueira, Marcelo F.G., Olsaker, Ingrid, Pant, Sameer D., Panzitta, Francesca, Pastor, Rosemeire C.P., Poli, Mario A., Poslusny, Nathan, Rachagani, Satyanarayana, Ranganathan, Shoba, Razpet, Andrej, Reecy, James, Riggs, Penny K., Rijnkels, Monique, Rincon, Gonzalo, Rodriguez-Osorio, Nelida, Rodriguez-Zas, Sandra L., Romero, Natasha E., Rosenwald, Anne, Sando, Lillian, Schmutz, Sheila M., Seo, Seongwon, Shen, Libing, Sherman, Laura, Skow, Loren C., Southey, Bruce R., Spurlock, Diane, Strandberg Lutzow, Ylva, Sweedler, Jonathan V., Tammen, Imke, Taniguchi, Masaaki, Tellam, Ross L, Telugu, Bhanu Prakash V.L, Urbanski, Jennifer M., Utsunomiya, Yuri T., Verschoor, Chris P., Waardenberg, Ashley J., Walker, Angela, Wang, Zhiquan, Ward, Robert, Weikard, Rosemarie, Welsh, Thomas H., Jr., Wheeler, Thomas T., White, Stephen N., Williams, John L, Wilming, Laurens G., Wunderlich, Kris R., Yang, Jianqi, and Zhao, Feng-Qi

Published
2009

39. Origins and functional impact of copy number variation in the human genome

Author

Conrad, Donald F., Pinto, Dalila, Redon, Richard, Feuk, Lars, Gokcumen, Omer, Zhang, Yujun, Aerts, Jan, Andrews, T. Daniel, Barnes, Chris, Campbell, Peter, Fitzgerald, Tomas, Hu, Min, Ihm, Chun Hwa, Kristiansson, Kati, MacArthur, Daniel G., MacDonald, Jeffrey R., Onyiah, Ifejinelo, Pang, Andy Wing Chun, Robson, Sam, Stirrups, Kathy, Valsesia, Armand, Walter, Klaudia, Wei, John, Tyler-Smith, Chris, Carter, Nigel P., Lee, Charles, Scherer, Stephen W., and Hurles, Matthew E.

Subjects
Research, Human genome -- Research, Genetic variation -- Research
Abstract

Genomes vary from one another in multifarious ways, and the totality of this genetic variation underpins the heritability of human traits. Over the past two years, the human reference sequence [...], Structural variations of DNA greater than 1 kilobase in size account for most bases that vary among human genomes, but are still relatively under-ascertained. Here we use tiling oligonucleotide microarrays, comprising 42 million probes, to generate a comprehensive map of 11,700 copy number variations (CNVs) greater than 443 base pairs, of which most (8,599) have been validated independently. For 4,978 of these CNVs, we generated reference genotypes from 450 individuals of European, African or East Asian ancestry. The predominant mutational mechanisms differ among CNV size classes. Retrotransposition has duplicated and inserted some coding and non-coding DNA segments randomly around the genome. Furthermore, by correlation with known trait-associated single nucleotide polymorphisms (SNPs), we identified 30 loci with CNVs that are candidates for influencing disease susceptibility. Despite this, having assessed the completeness of our map and the patterns of linkage disequilibrium between CNVs and SNPs, we conclude that, for complex traits, the heritability void left by genome-wide association studies will not be accounted for by common CNVs.

Published
2010
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41. Towards Building a Quantitative Proteomics Toolbox in Precision Medicine: A Mini-Review

Author

CORREA ROJO, Alejandro, HEYLEN, Dries, AERTS, Jan, THAS, Olivier, HOOYBERGHS, Jef, Ertaylan, Gokhan, VALKENBORG, Dirk, Aerts, Jan/0000-0002-6416-2717, and VALKENBORG, Dirk/0000-0002-1877-3496

Subjects
precision medicine, quantitative proteomics, targeted techniques, bioinformatics, biomarker discovery, clinical diagnostics, protein, quantitative trait loci
Abstract

Precision medicine as a framework for disease diagnosis, treatment, and prevention at the molecular level has entered clinical practice. From the start, genetics has been an indispensable tool to understand and stratify the biology of chronic and complex diseases in precision medicine. However, with the advances in biomedical and omics technologies, quantitative proteomics is emerging as a powerful technology complementing genetics. Quantitative proteomics provide insight about the dynamic behaviour of proteins as they represent intermediate phenotypes. They provide direct biological insights into physiological patterns, while genetics accounting for baseline characteristics. Additionally, it opens a wide range of applications in clinical diagnostics, treatment stratification, and drug discovery. In this mini-review, we discuss the current status of quantitative proteomics in precision medicine including the available technologies and common methods to analyze quantitative proteomics data. Furthermore, we highlight the current challenges to put quantitative proteomics into clinical settings and provide a perspective to integrate proteomics data with genomics data for future applications in precision medicine.

Published
2021

45. A physical map of the chicken genome

Author

Wallis, John W., Aerts, Jan, Groenen, Martien A. M., Crooijmans, Richard P. M. A., Layman, Dan, Graves, Tina A., Scheer, Debra E., Kremitzki, Colin, Fedele, Mary J., Mudd, Nancy K., Cardenas, Marco, Higginbotham, Jamey, Carter, Jason, McGrane, Rebecca, Gaige, Tony, Mead, Kelly, Walker, Jason, Albracht, Derek, Davito, Jonathan, Yang, Shiaw-Pyng, Leong, Shin, Chinwalla, Asif, Sekhon, Mandeep, Wylie, Kristine, Dodgson, Jerry, Romanov, Michael N., Cheng, Hans, de Jong, Pieter J., Osoegawa, Kazutoyo, Nefedov, Mikhail, Zhang, Hongbin, McPherson, John D., Krzywinski, Martin, Schein, Jacquie, Hillier, LaDeana, Mardis, Elaine R., Wilson, Richard K., and Warren, Wesley C.

Published
2004
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50. Belgian COVID-19 Mortality, Excess Deaths, Number of Deaths per Million, and Infection Fatality Rates (8 March - 9 May 2020)

Author

Molenberghs, Geert, primary, Faes, Christel, additional, Aerts, Jan, additional, Theeten, Heidi, additional, Devleesschauwer, Brecht, additional, Sierra, Natalia Bustos, additional, Braeye, Toon, additional, Renard, Françoise, additional, Herzog, Sereina, additional, Lusyne, Patrick, additional, Van der Heyden, Johan, additional, Van Oyen, Herman, additional, Van Damme, Pierre, additional, and Hens, Niel, additional

Published
2020
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