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1. The Quest for Orthologs orthology benchmark service in 2022

Author

Nevers, Yannis, Jones, Tamsin E. M., Jyothi, Dushyanth, Yates, Bethan, Ferret, Meritxell, Portell-Silva, Laura, Codo, Laia, Cosentino, Salvatore, Marcet-Houben, Marina, Vlasova, Anna, Poidevin, Laetitia, Kress, Arnaud, Hickman, Mark, Persson, Emma, Piližota, Ivana, Guijarro-Clarke, Cristina, Iwasaki, Wataru, Lecompte, Odile, Sonnhammer, Erik, Roos, David S., Gabaldón, Toni, Thybert, David, Thomas, Paul D., Hu, Yanhui, Emms, David M., Bruford, Elspeth, Capella-Gutierrez, Salvador, Martin, Maria J., Dessimoz, Christophe, Altenhoff, Adrian, Nevers, Yannis, Jones, Tamsin E. M., Jyothi, Dushyanth, Yates, Bethan, Ferret, Meritxell, Portell-Silva, Laura, Codo, Laia, Cosentino, Salvatore, Marcet-Houben, Marina, Vlasova, Anna, Poidevin, Laetitia, Kress, Arnaud, Hickman, Mark, Persson, Emma, Piližota, Ivana, Guijarro-Clarke, Cristina, Iwasaki, Wataru, Lecompte, Odile, Sonnhammer, Erik, Roos, David S., Gabaldón, Toni, Thybert, David, Thomas, Paul D., Hu, Yanhui, Emms, David M., Bruford, Elspeth, Capella-Gutierrez, Salvador, Martin, Maria J., Dessimoz, Christophe, and Altenhoff, Adrian

Abstract

The Orthology Benchmark Service (https://orthology.benchmarkservice.org) is the gold standard for orthology inference evaluation, supported and maintained by the Quest for Orthologs consortium. It is an essential resource to compare existing and new methods of orthology inference (the bedrock for many comparative genomics and phylogenetic analysis) over a standard dataset and through common procedures. The Quest for Orthologs Consortium is dedicated to maintaining the resource up to date, through regular updates of the Reference Proteomes and increasingly accessible data through the OpenEBench platform. For this update, we have added a new benchmark based on curated orthology assertion from the Vertebrate Gene Nomenclature Committee, and provided an example meta-analysis of the public predictions present on the platform.

Published
2022
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2. A GO catalogue of human DNA-binding transcription factors

Author

Lovering, Ruth C., Gaudet, Pascale, Acencio, Marcio L., Ignatchenko, Alex, Jolma, Arttu, Fornes, Oriol, Martin, Maria J., Logie, C., Lovering, Ruth C., Gaudet, Pascale, Acencio, Marcio L., Ignatchenko, Alex, Jolma, Arttu, Fornes, Oriol, Martin, Maria J., and Logie, C.

Abstract

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Published
2021

3. Application of the health belief model to explain public perceptions, travel intentions and actions during COVID-19: a sequential transformative design

Author

Bremser, Kerstin, Crowley-Cyr, Lynda, Abraham, Villy, Moreno-Martin, Maria J., Carreno, Mercedes, Bremser, Kerstin, Crowley-Cyr, Lynda, Abraham, Villy, Moreno-Martin, Maria J., and Carreno, Mercedes

Abstract

Purpose: This paper uses a supplemented health belief model (HBM) to explain the risk perception of COVID-19 coronavirus infection by potential and actual domestic and international travelers (from primarily European countries) in the early pre-vaccine phase of the pandemic and its influence on their travel intentions, decisions, and actions. With a health crisis of this magnitude, it is vital to understand the effect of COVID-19-associated containment measures and safety industry strategies in abating public fear and apprehension associated with non-essential travel. Design/methodology/approach: The authors used a sequential transformative design consisting of a (QUAN + Qual) survey to explore the HBM dimensions. The questions in the quantitative part of the survey were disseminated online examine perceptions of the severity and susceptibility of the disease, travel risks and willingness to travel. The questions in the qualitative face-to-face survey examined, how international/cross-border travelers (from Spain and Germany) perceive the benefits and barriers of personal protective behavior and the potential influence of cues to action. Findings: Results suggest that despite potential fear arousal and confusion associated with this infectious disease, people were willing to travel during periodic on-and-off travel restrictions and perceive the benefits of such travel as outweighing barriers like wearing masks, social distancing and other containment measures. Research limitations/implications: The conceptual model enabled the capture of real-time traveler's feelings about the benefits of traveling in the presence of the coronavirus and their perceptions of COVID-19 safety strategies used at destinations. This study adds to the lack of existing knowledge about potential psychological factors influencing travel decisions and behavior, including self-protective behavior. As borders reopen and we progress towards tourism and hospitality recovery, the results of this st

Published
2021

4. A GO catalogue of human DNA-binding transcription factors

Author

Lovering, Ruth C., Gaudet, Pascale, Acencio, Marcio L., Ignatchenko, Alex, Jolma, Arttu, Fornes, Oriol, Martin, Maria J., Logie, C., Lovering, Ruth C., Gaudet, Pascale, Acencio, Marcio L., Ignatchenko, Alex, Jolma, Arttu, Fornes, Oriol, Martin, Maria J., and Logie, C.

Abstract

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Published
2021

5. A GO catalogue of human DNA-binding transcription factors

Author

Lovering, Ruth C., Gaudet, Pascale, Acencio, Marcio L., Ignatchenko, Alex, Jolma, Arttu, Fornes, Oriol, Martin, Maria J., Logie, C., Lovering, Ruth C., Gaudet, Pascale, Acencio, Marcio L., Ignatchenko, Alex, Jolma, Arttu, Fornes, Oriol, Martin, Maria J., and Logie, C.

Abstract

Contains fulltext : 240813.pdf (Publisher’s version ) (Closed access)

Published
2021

6. Computational strategies to combat COVID-19:useful tools to accelerate SARS-CoV-2 and coronavirus research

Author

Hufsky, Franziska, Lamkiewicz, Kevin, Almeida, Alexandre, Aouacheria, Abdel, Arighi, Cecilia, Bateman, Alex, Baumbach, Jan, Beerenwinkel, Niko, Brandt, Christian, Cacciabue, Marco, Chuguransky, Sara, Drechsel, Oliver, Finn, Robert D., Fritz, Adrian, Fuchs, Stephan, Hattab, Georges, Hauschild, Anne-Christin, Heider, Dominik, Hoffmann, Marie, Hölzer, Martin, Hoops, Stefan, Kaderali, Lars, Kalvari, Ioanna, von Kleist, Max, Kmiecinski, Renó, Kühnert, Denise, Lasso, Gorka, Libin, Pieter, List, Markus, Löchel, Hannah F., Martin, Maria J., Martin, Roman, Matschinske, Julian, McHardy, Alice C., Mendes, Pedro, Mistry, Jaina, Navratil, Vincent, Nawrocki, Eric P., O'Toole, Aíne Niamh, Ontiveros-Palacios, Nancy, Petrov, Anton I., Rangel-Pineros, Guillermo, Redaschi, Nicole, Reimering, Susanne, Reinert, Knut, Reyes, Alejandro, Richardson, Lorna, Robertson, David L., Sadegh, Sepideh, Singer, Joshua B., Theys, Kristof, Upton, Chris, Welzel, Marius, Williams, Lowri, Marz, Manja, Hufsky, Franziska, Lamkiewicz, Kevin, Almeida, Alexandre, Aouacheria, Abdel, Arighi, Cecilia, Bateman, Alex, Baumbach, Jan, Beerenwinkel, Niko, Brandt, Christian, Cacciabue, Marco, Chuguransky, Sara, Drechsel, Oliver, Finn, Robert D., Fritz, Adrian, Fuchs, Stephan, Hattab, Georges, Hauschild, Anne-Christin, Heider, Dominik, Hoffmann, Marie, Hölzer, Martin, Hoops, Stefan, Kaderali, Lars, Kalvari, Ioanna, von Kleist, Max, Kmiecinski, Renó, Kühnert, Denise, Lasso, Gorka, Libin, Pieter, List, Markus, Löchel, Hannah F., Martin, Maria J., Martin, Roman, Matschinske, Julian, McHardy, Alice C., Mendes, Pedro, Mistry, Jaina, Navratil, Vincent, Nawrocki, Eric P., O'Toole, Aíne Niamh, Ontiveros-Palacios, Nancy, Petrov, Anton I., Rangel-Pineros, Guillermo, Redaschi, Nicole, Reimering, Susanne, Reinert, Knut, Reyes, Alejandro, Richardson, Lorna, Robertson, David L., Sadegh, Sepideh, Singer, Joshua B., Theys, Kristof, Upton, Chris, Welzel, Marius, Williams, Lowri, and Marz, Manja

Abstract

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are free to use and available online, either through web applications or public code repositories. Contact:evbc@unj-jena.de

Published
2021

7. Computational strategies to combat COVID-19:useful tools to accelerate SARS-CoV-2 and coronavirus research

Author

Hufsky, Franziska, Lamkiewicz, Kevin, Almeida, Alexandre, Aouacheria, Abdel, Arighi, Cecilia, Bateman, Alex, Baumbach, Jan, Beerenwinkel, Niko, Brandt, Christian, Cacciabue, Marco, Chuguransky, Sara, Drechsel, Oliver, Finn, Robert D., Fritz, Adrian, Fuchs, Stephan, Hattab, Georges, Hauschild, Anne-Christin, Heider, Dominik, Hoffmann, Marie, Hölzer, Martin, Hoops, Stefan, Kaderali, Lars, Kalvari, Ioanna, von Kleist, Max, Kmiecinski, Renó, Kühnert, Denise, Lasso, Gorka, Libin, Pieter, List, Markus, Löchel, Hannah F., Martin, Maria J., Martin, Roman, Matschinske, Julian, McHardy, Alice C., Mendes, Pedro, Mistry, Jaina, Navratil, Vincent, Nawrocki, Eric P., O'Toole, Aíne Niamh, Ontiveros-Palacios, Nancy, Petrov, Anton I., Rangel-Pineros, Guillermo, Redaschi, Nicole, Reimering, Susanne, Reinert, Knut, Reyes, Alejandro, Richardson, Lorna, Robertson, David L., Sadegh, Sepideh, Singer, Joshua B., Theys, Kristof, Upton, Chris, Welzel, Marius, Williams, Lowri, Marz, Manja, Hufsky, Franziska, Lamkiewicz, Kevin, Almeida, Alexandre, Aouacheria, Abdel, Arighi, Cecilia, Bateman, Alex, Baumbach, Jan, Beerenwinkel, Niko, Brandt, Christian, Cacciabue, Marco, Chuguransky, Sara, Drechsel, Oliver, Finn, Robert D., Fritz, Adrian, Fuchs, Stephan, Hattab, Georges, Hauschild, Anne-Christin, Heider, Dominik, Hoffmann, Marie, Hölzer, Martin, Hoops, Stefan, Kaderali, Lars, Kalvari, Ioanna, von Kleist, Max, Kmiecinski, Renó, Kühnert, Denise, Lasso, Gorka, Libin, Pieter, List, Markus, Löchel, Hannah F., Martin, Maria J., Martin, Roman, Matschinske, Julian, McHardy, Alice C., Mendes, Pedro, Mistry, Jaina, Navratil, Vincent, Nawrocki, Eric P., O'Toole, Aíne Niamh, Ontiveros-Palacios, Nancy, Petrov, Anton I., Rangel-Pineros, Guillermo, Redaschi, Nicole, Reimering, Susanne, Reinert, Knut, Reyes, Alejandro, Richardson, Lorna, Robertson, David L., Sadegh, Sepideh, Singer, Joshua B., Theys, Kristof, Upton, Chris, Welzel, Marius, Williams, Lowri, and Marz, Manja

Abstract

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are free to use and available online, either through web applications or public code repositories. Contact:evbc@unj-jena.de

Published
2021

8. The Quest for Orthologs benchmark service and consensus calls in 2020

Author

Altenhoff, Adrian M., Garrayo-Ventas, Javier, Cosentino, Salvatore, Emms, David, Glover, Natasha M., Hernández-Plaza, Ana, Nevers, Yannis, Sundesha, Vicky, Szklarczyk, Damian, Fernández, José M., Codó, Laia, Li Gelpi, Josep, Huerta-Cepas, Jaime, Iwasaki, Wataru, Kelly, Steven, Lecompte, Odile, Muffato, Matthieu, Martin, Maria J., Capella-Gutierrez, Salvador, Thomas, Paul D., Sonnhammer, Erik, Dessimoz, Christophe, Altenhoff, Adrian M., Garrayo-Ventas, Javier, Cosentino, Salvatore, Emms, David, Glover, Natasha M., Hernández-Plaza, Ana, Nevers, Yannis, Sundesha, Vicky, Szklarczyk, Damian, Fernández, José M., Codó, Laia, Li Gelpi, Josep, Huerta-Cepas, Jaime, Iwasaki, Wataru, Kelly, Steven, Lecompte, Odile, Muffato, Matthieu, Martin, Maria J., Capella-Gutierrez, Salvador, Thomas, Paul D., Sonnhammer, Erik, and Dessimoz, Christophe

Abstract

The identification of orthologs-genes in different species which descended from the same gene in their last common ancestor-is a prerequisite for many analyses in comparative genomics and molecular evolution. Numerous algorithms and resources have been conceived to address this problem, but benchmarking and interpreting them is fraught with difficulties (need to compare them on a common input dataset, absence of ground truth, computational cost of calling orthologs). To address this, the Quest for Orthologs consortium maintains a reference set of proteomes and provides a web server for continuous orthology benchmarking (http://orthology.benchmarkservice.org). Furthermore, consensus ortholog calls derived from public benchmark submissions are provided on the Alliance of Genome Resources website, the joint portal of NIH-funded model organism databases.

Published
2020
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9. The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Author

Zhou, Naihui, Jiang, Yuxiang, Bergquist, Timothy R, Lee, Alexandra J, Kacsoh, Balint Z, Crocker, Alex W, Lewis, Kimberley A, Georghiou, George, Nguyen, Huy N, Hamid, Md Nafiz, Davis, Larry, Dogan, Tunca, Atalay, Volkan, Rifaioglu, Ahmet S, Dalkıran, Alperen, Cetin Atalay, Rengul, Zhang, Chengxin, Hurto, Rebecca L, Freddolino, Peter L, Zhang, Yang, Bhat, Prajwal, Supek, Fran, Fernández, José M, Gemović, Branislava S., Perović, Vladimir R., Davidović, Radoslav S., Šumonja, Neven, Veljković, Nevena V., Asgari, Ehsaneddin, Mofrad, Mohammad R.K., Profiti, Giuseppe, Savojardo, Castrense, Martelli, Pier Luigi, Casadio, Rita, Boecker, Florian, Schoof, Heiko, Kahanda, Indika, Thurlby, Natalie, McHardy, Alice C, Renaux, Alexandre, Saidi, Rabie, Gough, Julian, Freitas, Alex A, Antczak, Magdalena, Fabris, Fabio, Wass, Mark N, Hou, Jie, Cheng, Jianlin, Wang, Zheng, Romero, Alfonso E, Paccanaro, Alberto, Yang, Haixuan, Goldberg, Tatyana, Zhao, Chenguang, Holm, Liisa, Törönen, Petri, Medlar, Alan J, Zosa, Elaine, Borukhov, Itamar, Novikov, Ilya, Wilkins, Angela, Lichtarge, Olivier, Chi, Po-Han, Tseng, Wei-Cheng, Linial, Michal, Rose, Peter W, Dessimoz, Christophe, Vidulin, Vedrana, Dzeroski, Saso, Sillitoe, Ian, Das, Sayoni, Lees, Jonathan Gill, Jones, David T, Wan, Cen, Cozzetto, Domenico, Fa, Rui, Torres, Mateo, Warwick Vesztrocy, Alex, Rodriguez, Jose Manuel, Tress, Michael L, Frasca, Marco, Notaro, Marco, Grossi, Giuliano, Petrini, Alessandro, Re, Matteo, Valentini, Giorgio, Mesiti, Marco, Roche, Daniel B, Reeb, Jonas, Ritchie, David W, Aridhi, Sabeur, Alborzi, Seyed Ziaeddin, Devignes, Marie-Dominique, Koo, Da Chen Emily, Bonneau, Richard, Gligorijević, Vladimir, Barot, Meet, Fang, Hai, Toppo, Stefano, Lavezzo, Enrico, Falda, Marco, Berselli, Michele, Tosatto, Silvio C.E., Carraro, Marco, Piovesan, Damiano, Ur Rehman, Hafeez, Mao, Qizhong, Zhang, Shanshan, Vucetic, Slobodan, Black, Gage S, Jo, Dane, Suh, Erica, Dayton, Jonathan B, Larsen, Dallas J, Omdahl, Ashton R, McGuffin, Liam J, Brackenridge, Danielle A, Babbitt, Patricia C, Yunes, Jeffrey M, Fontana, Paolo, Zhang, Feng, Zhu, Shanfeng, You, Ronghui, Zhang, Zihan, Dai, Suyang, Yao, Shuwei, Tian, Weidong, Cao, Renzhi, Chandler, Caleb, Amezola, Miguel, Johnson, Devon, Chang, Jia-Ming, Liao, Wen-Hung, Liu, Yi-Wei, Pascarelli, Stefano, Frank, Yotam, Hoehndorf, Robert, Kulmanov, Maxat, Boudellioua, Imane, Politano, Gianfranco, Di Carlo, Stefano, Benso, Alfredo, Hakala, Kai, Ginter, Filip, Mehryary, Farrokh, Kaewphan, Suwisa, Björne, Jari, Moen, Hans, Tolvanen, Martti E.E., Salakoski, Tapio, Kihara, Daisuke, Jain, Aashish, Šmuc, Tomislav, Altenhoff, Adrian, Ben-Hur, Asa, Rost, Burkhard, Brenner, Steven E, Orengo, Christine A, Jeffery, Constance J, Bosco, Giovanni, Hogan, Deborah A, Martin, Maria J, O’Donovan, Claire, Mooney, Sean D, Greene, Casey S, Radivojac, Predrag, Friedberg, Iddo, Zhou, Naihui, Jiang, Yuxiang, Bergquist, Timothy R, Lee, Alexandra J, Kacsoh, Balint Z, Crocker, Alex W, Lewis, Kimberley A, Georghiou, George, Nguyen, Huy N, Hamid, Md Nafiz, Davis, Larry, Dogan, Tunca, Atalay, Volkan, Rifaioglu, Ahmet S, Dalkıran, Alperen, Cetin Atalay, Rengul, Zhang, Chengxin, Hurto, Rebecca L, Freddolino, Peter L, Zhang, Yang, Bhat, Prajwal, Supek, Fran, Fernández, José M, Gemović, Branislava S., Perović, Vladimir R., Davidović, Radoslav S., Šumonja, Neven, Veljković, Nevena V., Asgari, Ehsaneddin, Mofrad, Mohammad R.K., Profiti, Giuseppe, Savojardo, Castrense, Martelli, Pier Luigi, Casadio, Rita, Boecker, Florian, Schoof, Heiko, Kahanda, Indika, Thurlby, Natalie, McHardy, Alice C, Renaux, Alexandre, Saidi, Rabie, Gough, Julian, Freitas, Alex A, Antczak, Magdalena, Fabris, Fabio, Wass, Mark N, Hou, Jie, Cheng, Jianlin, Wang, Zheng, Romero, Alfonso E, Paccanaro, Alberto, Yang, Haixuan, Goldberg, Tatyana, Zhao, Chenguang, Holm, Liisa, Törönen, Petri, Medlar, Alan J, Zosa, Elaine, Borukhov, Itamar, Novikov, Ilya, Wilkins, Angela, Lichtarge, Olivier, Chi, Po-Han, Tseng, Wei-Cheng, Linial, Michal, Rose, Peter W, Dessimoz, Christophe, Vidulin, Vedrana, Dzeroski, Saso, Sillitoe, Ian, Das, Sayoni, Lees, Jonathan Gill, Jones, David T, Wan, Cen, Cozzetto, Domenico, Fa, Rui, Torres, Mateo, Warwick Vesztrocy, Alex, Rodriguez, Jose Manuel, Tress, Michael L, Frasca, Marco, Notaro, Marco, Grossi, Giuliano, Petrini, Alessandro, Re, Matteo, Valentini, Giorgio, Mesiti, Marco, Roche, Daniel B, Reeb, Jonas, Ritchie, David W, Aridhi, Sabeur, Alborzi, Seyed Ziaeddin, Devignes, Marie-Dominique, Koo, Da Chen Emily, Bonneau, Richard, Gligorijević, Vladimir, Barot, Meet, Fang, Hai, Toppo, Stefano, Lavezzo, Enrico, Falda, Marco, Berselli, Michele, Tosatto, Silvio C.E., Carraro, Marco, Piovesan, Damiano, Ur Rehman, Hafeez, Mao, Qizhong, Zhang, Shanshan, Vucetic, Slobodan, Black, Gage S, Jo, Dane, Suh, Erica, Dayton, Jonathan B, Larsen, Dallas J, Omdahl, Ashton R, McGuffin, Liam J, Brackenridge, Danielle A, Babbitt, Patricia C, Yunes, Jeffrey M, Fontana, Paolo, Zhang, Feng, Zhu, Shanfeng, You, Ronghui, Zhang, Zihan, Dai, Suyang, Yao, Shuwei, Tian, Weidong, Cao, Renzhi, Chandler, Caleb, Amezola, Miguel, Johnson, Devon, Chang, Jia-Ming, Liao, Wen-Hung, Liu, Yi-Wei, Pascarelli, Stefano, Frank, Yotam, Hoehndorf, Robert, Kulmanov, Maxat, Boudellioua, Imane, Politano, Gianfranco, Di Carlo, Stefano, Benso, Alfredo, Hakala, Kai, Ginter, Filip, Mehryary, Farrokh, Kaewphan, Suwisa, Björne, Jari, Moen, Hans, Tolvanen, Martti E.E., Salakoski, Tapio, Kihara, Daisuke, Jain, Aashish, Šmuc, Tomislav, Altenhoff, Adrian, Ben-Hur, Asa, Rost, Burkhard, Brenner, Steven E, Orengo, Christine A, Jeffery, Constance J, Bosco, Giovanni, Hogan, Deborah A, Martin, Maria J, O’Donovan, Claire, Mooney, Sean D, Greene, Casey S, Radivojac, Predrag, and Friedberg, Iddo

Abstract

Background: The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results: Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-Term memory. Conclusion: We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens. © 2019 The Author(s).

Published
2019

10. The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Author

Zhou, Naihui, Jiang, Yuxiang, Bergquist, Timothy R, Lee, Alexandra J, Kacsoh, Balint Z, Crocker, Alex W, Lewis, Kimberley A, Georghiou, George, Nguyen, Huy N, Hamid, Md Nafiz, Davis, Larry, Dogan, Tunca, Atalay, Volkan, Rifaioglu, Ahmet S, Dalkıran, Alperen, Cetin Atalay, Rengul, Zhang, Chengxin, Hurto, Rebecca L, Freddolino, Peter L, Zhang, Yang, Bhat, Prajwal, Supek, Fran, Fernández, José M, Gemović, Branislava S., Perović, Vladimir R., Davidović, Radoslav S., Šumonja, Neven, Veljković, Nevena V., Asgari, Ehsaneddin, Mofrad, Mohammad R.K., Profiti, Giuseppe, Savojardo, Castrense, Martelli, Pier Luigi, Casadio, Rita, Boecker, Florian, Schoof, Heiko, Kahanda, Indika, Thurlby, Natalie, McHardy, Alice C, Renaux, Alexandre, Saidi, Rabie, Gough, Julian, Freitas, Alex A, Antczak, Magdalena, Fabris, Fabio, Wass, Mark N, Hou, Jie, Cheng, Jianlin, Wang, Zheng, Romero, Alfonso E, Paccanaro, Alberto, Yang, Haixuan, Goldberg, Tatyana, Zhao, Chenguang, Holm, Liisa, Törönen, Petri, Medlar, Alan J, Zosa, Elaine, Borukhov, Itamar, Novikov, Ilya, Wilkins, Angela, Lichtarge, Olivier, Chi, Po-Han, Tseng, Wei-Cheng, Linial, Michal, Rose, Peter W, Dessimoz, Christophe, Vidulin, Vedrana, Dzeroski, Saso, Sillitoe, Ian, Das, Sayoni, Lees, Jonathan Gill, Jones, David T, Wan, Cen, Cozzetto, Domenico, Fa, Rui, Torres, Mateo, Warwick Vesztrocy, Alex, Rodriguez, Jose Manuel, Tress, Michael L, Frasca, Marco, Notaro, Marco, Grossi, Giuliano, Petrini, Alessandro, Re, Matteo, Valentini, Giorgio, Mesiti, Marco, Roche, Daniel B, Reeb, Jonas, Ritchie, David W, Aridhi, Sabeur, Alborzi, Seyed Ziaeddin, Devignes, Marie-Dominique, Koo, Da Chen Emily, Bonneau, Richard, Gligorijević, Vladimir, Barot, Meet, Fang, Hai, Toppo, Stefano, Lavezzo, Enrico, Falda, Marco, Berselli, Michele, Tosatto, Silvio C.E., Carraro, Marco, Piovesan, Damiano, Ur Rehman, Hafeez, Mao, Qizhong, Zhang, Shanshan, Vucetic, Slobodan, Black, Gage S, Jo, Dane, Suh, Erica, Dayton, Jonathan B, Larsen, Dallas J, Omdahl, Ashton R, McGuffin, Liam J, Brackenridge, Danielle A, Babbitt, Patricia C, Yunes, Jeffrey M, Fontana, Paolo, Zhang, Feng, Zhu, Shanfeng, You, Ronghui, Zhang, Zihan, Dai, Suyang, Yao, Shuwei, Tian, Weidong, Cao, Renzhi, Chandler, Caleb, Amezola, Miguel, Johnson, Devon, Chang, Jia-Ming, Liao, Wen-Hung, Liu, Yi-Wei, Pascarelli, Stefano, Frank, Yotam, Hoehndorf, Robert, Kulmanov, Maxat, Boudellioua, Imane, Politano, Gianfranco, Di Carlo, Stefano, Benso, Alfredo, Hakala, Kai, Ginter, Filip, Mehryary, Farrokh, Kaewphan, Suwisa, Björne, Jari, Moen, Hans, Tolvanen, Martti E.E., Salakoski, Tapio, Kihara, Daisuke, Jain, Aashish, Šmuc, Tomislav, Altenhoff, Adrian, Ben-Hur, Asa, Rost, Burkhard, Brenner, Steven E, Orengo, Christine A, Jeffery, Constance J, Bosco, Giovanni, Hogan, Deborah A, Martin, Maria J, O’Donovan, Claire, Mooney, Sean D, Greene, Casey S, Radivojac, Predrag, Friedberg, Iddo, Zhou, Naihui, Jiang, Yuxiang, Bergquist, Timothy R, Lee, Alexandra J, Kacsoh, Balint Z, Crocker, Alex W, Lewis, Kimberley A, Georghiou, George, Nguyen, Huy N, Hamid, Md Nafiz, Davis, Larry, Dogan, Tunca, Atalay, Volkan, Rifaioglu, Ahmet S, Dalkıran, Alperen, Cetin Atalay, Rengul, Zhang, Chengxin, Hurto, Rebecca L, Freddolino, Peter L, Zhang, Yang, Bhat, Prajwal, Supek, Fran, Fernández, José M, Gemović, Branislava S., Perović, Vladimir R., Davidović, Radoslav S., Šumonja, Neven, Veljković, Nevena V., Asgari, Ehsaneddin, Mofrad, Mohammad R.K., Profiti, Giuseppe, Savojardo, Castrense, Martelli, Pier Luigi, Casadio, Rita, Boecker, Florian, Schoof, Heiko, Kahanda, Indika, Thurlby, Natalie, McHardy, Alice C, Renaux, Alexandre, Saidi, Rabie, Gough, Julian, Freitas, Alex A, Antczak, Magdalena, Fabris, Fabio, Wass, Mark N, Hou, Jie, Cheng, Jianlin, Wang, Zheng, Romero, Alfonso E, Paccanaro, Alberto, Yang, Haixuan, Goldberg, Tatyana, Zhao, Chenguang, Holm, Liisa, Törönen, Petri, Medlar, Alan J, Zosa, Elaine, Borukhov, Itamar, Novikov, Ilya, Wilkins, Angela, Lichtarge, Olivier, Chi, Po-Han, Tseng, Wei-Cheng, Linial, Michal, Rose, Peter W, Dessimoz, Christophe, Vidulin, Vedrana, Dzeroski, Saso, Sillitoe, Ian, Das, Sayoni, Lees, Jonathan Gill, Jones, David T, Wan, Cen, Cozzetto, Domenico, Fa, Rui, Torres, Mateo, Warwick Vesztrocy, Alex, Rodriguez, Jose Manuel, Tress, Michael L, Frasca, Marco, Notaro, Marco, Grossi, Giuliano, Petrini, Alessandro, Re, Matteo, Valentini, Giorgio, Mesiti, Marco, Roche, Daniel B, Reeb, Jonas, Ritchie, David W, Aridhi, Sabeur, Alborzi, Seyed Ziaeddin, Devignes, Marie-Dominique, Koo, Da Chen Emily, Bonneau, Richard, Gligorijević, Vladimir, Barot, Meet, Fang, Hai, Toppo, Stefano, Lavezzo, Enrico, Falda, Marco, Berselli, Michele, Tosatto, Silvio C.E., Carraro, Marco, Piovesan, Damiano, Ur Rehman, Hafeez, Mao, Qizhong, Zhang, Shanshan, Vucetic, Slobodan, Black, Gage S, Jo, Dane, Suh, Erica, Dayton, Jonathan B, Larsen, Dallas J, Omdahl, Ashton R, McGuffin, Liam J, Brackenridge, Danielle A, Babbitt, Patricia C, Yunes, Jeffrey M, Fontana, Paolo, Zhang, Feng, Zhu, Shanfeng, You, Ronghui, Zhang, Zihan, Dai, Suyang, Yao, Shuwei, Tian, Weidong, Cao, Renzhi, Chandler, Caleb, Amezola, Miguel, Johnson, Devon, Chang, Jia-Ming, Liao, Wen-Hung, Liu, Yi-Wei, Pascarelli, Stefano, Frank, Yotam, Hoehndorf, Robert, Kulmanov, Maxat, Boudellioua, Imane, Politano, Gianfranco, Di Carlo, Stefano, Benso, Alfredo, Hakala, Kai, Ginter, Filip, Mehryary, Farrokh, Kaewphan, Suwisa, Björne, Jari, Moen, Hans, Tolvanen, Martti E.E., Salakoski, Tapio, Kihara, Daisuke, Jain, Aashish, Šmuc, Tomislav, Altenhoff, Adrian, Ben-Hur, Asa, Rost, Burkhard, Brenner, Steven E, Orengo, Christine A, Jeffery, Constance J, Bosco, Giovanni, Hogan, Deborah A, Martin, Maria J, O’Donovan, Claire, Mooney, Sean D, Greene, Casey S, Radivojac, Predrag, and Friedberg, Iddo

Abstract

Background: The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results: Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-Term memory. Conclusion: We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens. © 2019 The Author(s).

Published
2019

11. ProForma: A Standard Proteoform Notation.

Author

LeDuc, Richard D, LeDuc, Richard D, Schwämmle, Veit, Shortreed, Michael R, Cesnik, Anthony J, Solntsev, Stefan K, Shaw, Jared B, Martin, Maria J, Vizcaino, Juan A, Alpi, Emanuele, Danis, Paul, Kelleher, Neil L, Smith, Lloyd M, Ge, Ying, Agar, Jeffrey N, Chamot-Rooke, Julia, Loo, Joseph A, Pasa-Tolic, Ljiljana, Tsybin, Yury O, LeDuc, Richard D, LeDuc, Richard D, Schwämmle, Veit, Shortreed, Michael R, Cesnik, Anthony J, Solntsev, Stefan K, Shaw, Jared B, Martin, Maria J, Vizcaino, Juan A, Alpi, Emanuele, Danis, Paul, Kelleher, Neil L, Smith, Lloyd M, Ge, Ying, Agar, Jeffrey N, Chamot-Rooke, Julia, Loo, Joseph A, Pasa-Tolic, Ljiljana, and Tsybin, Yury O

Abstract

The Consortium for Top-Down Proteomics (CTDP) proposes a standardized notation, ProForma, for writing the sequence of fully characterized proteoforms. ProForma provides a means to communicate any proteoform by writing the amino acid sequence using standard one-letter notation and specifying modifications or unidentified mass shifts within brackets following certain amino acids. The notation is unambiguous, human-readable, and can easily be parsed and written by bioinformatic tools. This system uses seven rules and supports a wide range of possible use cases, ensuring compatibility and reproducibility of proteoform annotations. Standardizing proteoform sequences will simplify storage, comparison, and reanalysis of proteomic studies, and the Consortium welcomes input and contributions from the research community on the continued design and maintenance of this standard.

Published
2018

12. The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003

Author

Boeckmann, Brigitte, Bairoch, Amos, Apweiler, Rolf, Blatter, Marie-Claude, Estreicher, Anne, Gasteiger, Elisabeth, Martin, Maria J., Michoud, Karine, O'Donovan, Claire, Phan, Isabelle, Pilbout, Sandrine, Schneider, Michel, Boeckmann, Brigitte, Bairoch, Amos, Apweiler, Rolf, Blatter, Marie-Claude, Estreicher, Anne, Gasteiger, Elisabeth, Martin, Maria J., Michoud, Karine, O'Donovan, Claire, Phan, Isabelle, Pilbout, Sandrine, and Schneider, Michel

Abstract

The SWISS-PROT protein knowledgebase (http://www.expasy.org/sprot/ and http://www.ebi.ac.uk/swissprot/) connects amino acid sequences with the current knowledge in the Life Sciences. Each protein entry provides an interdisciplinary overview of relevant information by bringing together experimental results, computed features and sometimes even contradictory conclusions. Detailed expertise that goes beyond the scope of SWISS-PROT is made available via direct links to specialised databases. SWISS-PROT provides annotated entries for all species, but concentrates on the annotation of entries from human (the HPI project) and other model organisms to ensure the presence of high quality annotation for representative members of all protein families. Part of the annotation can be transferred to other family members, as is already done for microbes by the High-quality Automated and Manual Annotation of microbial Proteomes (HAMAP) project. Protein families and groups of proteins are regularly reviewed to keep up with current scientific findings. Complementarily, TrEMBL strives to comprise all protein sequences that are not yet represented in SWISS-PROT, by incorporating a perpetually increasing level of mostly automated annotation. Researchers are welcome to contribute their knowledge to the scientific community by submitting relevant findings to SWISS-PROT at swiss-prot@expasy.org

Published
2017

13. The Universal Protein Resource (UniProt)

Author

Bairoch, Amos, Apweiler, Rolf, Wu, Cathy H., Barker, Winona C., Boeckmann, Brigitte, Ferro, Serenella, Gasteiger, Elisabeth, Huang, Hongzhan, Lopez, Rodrigo, Magrane, Michele, Martin, Maria J., Natale, Darren A., O'Donovan, Claire, Redaschi, Nicole, Yeh, Lai-Su L., Bairoch, Amos, Apweiler, Rolf, Wu, Cathy H., Barker, Winona C., Boeckmann, Brigitte, Ferro, Serenella, Gasteiger, Elisabeth, Huang, Hongzhan, Lopez, Rodrigo, Magrane, Michele, Martin, Maria J., Natale, Darren A., O'Donovan, Claire, Redaschi, Nicole, and Yeh, Lai-Su L.

Abstract

The Universal Protein Resource (UniProt) provides the scientific community with a single, centralized, authoritative resource for protein sequences and functional information. Formed by uniting the Swiss-Prot, TrEMBL and PIR protein database activities, the UniProt consortium produces three layers of protein sequence databases: the UniProt Archive (UniParc), the UniProt Knowledgebase (UniProt) and the UniProt Reference (UniRef) databases. The UniProt Knowledgebase is a comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase with extensive cross-references. This centrepiece consists of two sections: UniProt/Swiss-Prot, with fully, manually curated entries; and UniProt/TrEMBL, enriched with automated classification and annotation. During 2004, tens of thousands of Knowledgebase records got manually annotated or updated; we introduced a new comment line topic: TOXIC DOSE to store information on the acute toxicity of a toxin; the UniProt keyword list got augmented by additional keywords; we improved the documentation of the keywords and are continuously overhauling and standardizing the annotation of post-translational modifications. Furthermore, we introduced a new documentation file of the strains and their synonyms. Many new database cross-references were introduced and we started to make use of Digital Object Identifiers. We also achieved in collaboration with the Macromolecular Structure Database group at EBI an improved integration with structural databases by residue level mapping of sequences from the Protein Data Bank entries onto corresponding UniProt entries. For convenient sequence searches we provide the UniRef non-redundant sequence databases. The comprehensive UniParc database stores the complete body of publicly available protein sequence data. The UniProt databases can be accessed online (http://www.uniprot.org) or downloaded in several formats (ftp://ftp.uniprot.org/pub). New releases are published every two week

Published
2017

14. The Universal Protein Resource (UniProt): an expanding universe of protein information

Author

Wu, Cathy H., Apweiler, Rolf, Bairoch, Amos, Natale, Darren A., Barker, Winona C., Boeckmann, Brigitte, Ferro, Serenella, Gasteiger, Elisabeth, Huang, Hongzhan, Lopez, Rodrigo, Magrane, Michele, Martin, Maria J., Mazumder, Raja, O'Donovan, Claire, Redaschi, Nicole, Suzek, Baris, Wu, Cathy H., Apweiler, Rolf, Bairoch, Amos, Natale, Darren A., Barker, Winona C., Boeckmann, Brigitte, Ferro, Serenella, Gasteiger, Elisabeth, Huang, Hongzhan, Lopez, Rodrigo, Magrane, Michele, Martin, Maria J., Mazumder, Raja, O'Donovan, Claire, Redaschi, Nicole, and Suzek, Baris

Abstract

The Universal Protein Resource (UniProt) provides a central resource on protein sequences and functional annotation with three database components, each addressing a key need in protein bioinformatics. The UniProt Knowledgebase (UniProtKB), comprising the manually annotated UniProtKB/Swiss-Prot section and the automatically annotated UniProtKB/TrEMBL section, is the preeminent storehouse of protein annotation. The extensive cross-references, functional and feature annotations and literature-based evidence attribution enable scientists to analyse proteins and query across databases. The UniProt Reference Clusters (UniRef) speed similarity searches via sequence space compression by merging sequences that are 100% (UniRef100), 90% (UniRef90) or 50% (UniRef50) identical. Finally, the UniProt Archive (UniParc) stores all publicly available protein sequences, containing the history of sequence data with links to the source databases. UniProt databases continue to grow in size and in availability of information. Recent and upcoming changes to database contents, formats, controlled vocabularies and services are described. New download availability includes all major releases of UniProtKB, sequence collections by taxonomic division and complete proteomes. A bibliography mapping service has been added, and an ID mapping service will be available soon. UniProt databases can be accessed online at http://www.uniprot.org or downloaded at ftp://ftp.uniprot.org/pub/databases

Published
2017

15. The UniProt-GO Annotation database in 2011

Author

Dimmer, Emily C., Huntley, Rachael P., Alam-Faruque, Yasmin, Sawford, Tony, O'Donovan, Claire, Martin, Maria J., Bely, Benoit, Browne, Paul, Mun Chan, Wei, Eberhardt, Ruth, Gardner, Michael, Laiho, Kati, Legge, Duncan, Magrane, Michele, Pichler, Klemens, Poggioli, Diego, Sehra, Harminder, Auchincloss, Andrea, Axelsen, Kristian, Blatter, Marie-Claude, Boutet, Emmanuel, Braconi-Quintaje, Silvia, Breuza, Lionel, Bridge, Alan, Coudert, Elizabeth, Estreicher, Anne, Famiglietti, Livia, Ferro-Rojas, Serenella, Feuermann, Marc, Gos, Arnaud, Gruaz-Gumowski, Nadine, Hinz, Ursula, Hulo, Chantal, James, Janet, Jimenez, Silvia, Jungo, Florence, Keller, Guillaume, Lemercier, Phillippe, Lieberherr, Damien, Masson, Patrick, Moinat, Madelaine, Pedruzzi, Ivo, Poux, Sylvain, Rivoire, Catherine, Roechert, Bernd, Schneider, Michael, Stutz, Andre, Sundaram, Shyamala, Tognolli, Michael, Bougueleret, Lydie, Argoud-Puy, Ghislaine, Cusin, Isabelle, Duek- Roggli, Paula, Xenarios, Ioannis, Apweiler, Rolf, Dimmer, Emily C., Huntley, Rachael P., Alam-Faruque, Yasmin, Sawford, Tony, O'Donovan, Claire, Martin, Maria J., Bely, Benoit, Browne, Paul, Mun Chan, Wei, Eberhardt, Ruth, Gardner, Michael, Laiho, Kati, Legge, Duncan, Magrane, Michele, Pichler, Klemens, Poggioli, Diego, Sehra, Harminder, Auchincloss, Andrea, Axelsen, Kristian, Blatter, Marie-Claude, Boutet, Emmanuel, Braconi-Quintaje, Silvia, Breuza, Lionel, Bridge, Alan, Coudert, Elizabeth, Estreicher, Anne, Famiglietti, Livia, Ferro-Rojas, Serenella, Feuermann, Marc, Gos, Arnaud, Gruaz-Gumowski, Nadine, Hinz, Ursula, Hulo, Chantal, James, Janet, Jimenez, Silvia, Jungo, Florence, Keller, Guillaume, Lemercier, Phillippe, Lieberherr, Damien, Masson, Patrick, Moinat, Madelaine, Pedruzzi, Ivo, Poux, Sylvain, Rivoire, Catherine, Roechert, Bernd, Schneider, Michael, Stutz, Andre, Sundaram, Shyamala, Tognolli, Michael, Bougueleret, Lydie, Argoud-Puy, Ghislaine, Cusin, Isabelle, Duek- Roggli, Paula, Xenarios, Ioannis, and Apweiler, Rolf

Abstract

The GO annotation dataset provided by the UniProt Consortium (GOA: http://www.ebi.ac.uk/GOA) is a comprehensive set of evidenced-based associations between terms from the Gene Ontology resource and UniProtKB proteins. Currently supplying over 100 million annotations to 11 million proteins in more than 360 000 taxa, this resource has increased 2-fold over the last 2 years and has benefited from a wealth of checks to improve annotation correctness and consistency as well as now supplying a greater information content enabled by GO Consortium annotation format developments. Detailed, manual GO annotations obtained from the curation of peer-reviewed papers are directly contributed by all UniProt curators and supplemented with manual and electronic annotations from 36 model organism and domain-focused scientific resources. The inclusion of high-quality, automatic annotation predictions ensures the UniProt GO annotation dataset supplies functional information to a wide range of proteins, including those from poorly characterized, non-model organism species. UniProt GO annotations are freely available in a range of formats accessible by both file downloads and web-based views. In addition, the introduction of a new, normalized file format in 2010 has made for easier handling of the complete UniProt-GOA data set

Published
2017

16. UniProt: the Universal Protein knowledgebase

Author

Apweiler, Rolf, Bairoch, Amos, Wu, Cathy H., Barker, Winona C., Boeckmann, Brigitte, Ferro, Serenella, Gasteiger, Elisabeth, Huang, Hongzhan, Lopez, Rodrigo, Magrane, Michele, Martin, Maria J., Natale, Darren A., O'Donovan, Claire, Redaschi, Nicole, Yeh, Lai‐Su L., Apweiler, Rolf, Bairoch, Amos, Wu, Cathy H., Barker, Winona C., Boeckmann, Brigitte, Ferro, Serenella, Gasteiger, Elisabeth, Huang, Hongzhan, Lopez, Rodrigo, Magrane, Michele, Martin, Maria J., Natale, Darren A., O'Donovan, Claire, Redaschi, Nicole, and Yeh, Lai‐Su L.

Abstract

To provide the scientific community with a single, centralized, authoritative resource for protein sequences and functional information, the Swiss‐Prot, TrEMBL and PIR protein database activities have united to form the Universal Protein Knowledgebase (UniProt) consortium. Our mission is to provide a comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross‐references and query interfaces. The central database will have two sections, corresponding to the familiar Swiss‐Prot (fully manually curated entries) and TrEMBL (enriched with automated classification, annotation and extensive cross‐references). For convenient sequence searches, UniProt also provides several non‐redundant sequence databases. The UniProt NREF (UniRef) databases provide representative subsets of the knowledgebase suitable for efficient searching. The comprehensive UniProt Archive (UniParc) is updated daily from many public source databases. The UniProt databases can be accessed online (http://www.uniprot.org) or downloaded in several formats (ftp://ftp.uniprot.org/pub). The scientific community is encouraged to submit data for inclusion in UniProt

Published
2017

17. Standardized benchmarking in the quest for orthologs.

Author

Altenhoff, Adrian M, Altenhoff, Adrian M, Boeckmann, Brigitte, Capella-Gutierrez, Salvador, Dalquen, Daniel A, DeLuca, Todd, Forslund, Kristoffer, Huerta-Cepas, Jaime, Linard, Benjamin, Pereira, Cécile, Pryszcz, Leszek P, Schreiber, Fabian, da Silva, Alan Sousa, Szklarczyk, Damian, Train, Clément-Marie, Bork, Peer, Lecompte, Odile, von Mering, Christian, Xenarios, Ioannis, Sjölander, Kimmen, Jensen, Lars Juhl, Martin, Maria J, Muffato, Matthieu, Quest for Orthologs consortium, Gabaldón, Toni, Lewis, Suzanna E, Thomas, Paul D, Sonnhammer, Erik, Dessimoz, Christophe, Altenhoff, Adrian M, Altenhoff, Adrian M, Boeckmann, Brigitte, Capella-Gutierrez, Salvador, Dalquen, Daniel A, DeLuca, Todd, Forslund, Kristoffer, Huerta-Cepas, Jaime, Linard, Benjamin, Pereira, Cécile, Pryszcz, Leszek P, Schreiber, Fabian, da Silva, Alan Sousa, Szklarczyk, Damian, Train, Clément-Marie, Bork, Peer, Lecompte, Odile, von Mering, Christian, Xenarios, Ioannis, Sjölander, Kimmen, Jensen, Lars Juhl, Martin, Maria J, Muffato, Matthieu, Quest for Orthologs consortium, Gabaldón, Toni, Lewis, Suzanna E, Thomas, Paul D, Sonnhammer, Erik, and Dessimoz, Christophe

Abstract

Achieving high accuracy in orthology inference is essential for many comparative, evolutionary and functional genomic analyses, yet the true evolutionary history of genes is generally unknown and orthologs are used for very different applications across phyla, requiring different precision-recall trade-offs. As a result, it is difficult to assess the performance of orthology inference methods. Here, we present a community effort to establish standards and an automated web-based service to facilitate orthology benchmarking. Using this service, we characterize 15 well-established inference methods and resources on a battery of 20 different benchmarks. Standardized benchmarking provides a way for users to identify the most effective methods for the problem at hand, sets a minimum requirement for new tools and resources, and guides the development of more accurate orthology inference methods.

Published
2016

18. Standardized benchmarking in the quest for orthologs

Author

Altenhoff, Adrian M., Boeckmann, Brigitte, Capella-Gutierrez, Salvador, Dalquen, Daniel A., DeLuca, Todd, Forslund, Kristoffer, Huerta-Cepas, Jaime, Linard, Benjamin, Pereira, Cecile, Pryszcz, Leszek P., Schreiber, Fabian, da Silva, Alan Sousa, Szklarczyk, Damian, Train, Clement-Marie, Bork, Peer, Lecompte, Odile, von Mering, Christian, Xenarios, Ioannis, Sjölander, Kimmen, Juhl Jensen, Lars, Martin, Maria J., Muffato, Matthieu, Gabaldon, Toni, Lewis, Suzanna E., Thomas, Paul D., Sonnhammer, Erik, Dessimoz, Christophe, Altenhoff, Adrian M., Boeckmann, Brigitte, Capella-Gutierrez, Salvador, Dalquen, Daniel A., DeLuca, Todd, Forslund, Kristoffer, Huerta-Cepas, Jaime, Linard, Benjamin, Pereira, Cecile, Pryszcz, Leszek P., Schreiber, Fabian, da Silva, Alan Sousa, Szklarczyk, Damian, Train, Clement-Marie, Bork, Peer, Lecompte, Odile, von Mering, Christian, Xenarios, Ioannis, Sjölander, Kimmen, Juhl Jensen, Lars, Martin, Maria J., Muffato, Matthieu, Gabaldon, Toni, Lewis, Suzanna E., Thomas, Paul D., Sonnhammer, Erik, and Dessimoz, Christophe

Abstract

Achieving high accuracy in orthology inference is essential for many comparative, evolutionary and functional genomic analyses, yet the true evolutionary history of genes is generally unknown and orthologs are used for very different applications across phyla, requiring different precision-recall trade-offs. As a result, it is difficult to assess the performance of orthology inference methods. Here, we present a community effort to establish standards and an automated web-based service to facilitate orthology benchmarking. Using this service, we characterize 15 well-established inference methods and resources on a battery of 20 different benchmarks. Standardized benchmarking provides a way for users to identify the most effective methods for the problem at hand, sets a minimum requirement for new tools and resources, and guides the development of more accurate orthology inference methods.

Published
2016
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19. Standardized benchmarking in the quest for orthologs.

Author

Altenhoff, Adrian M, Altenhoff, Adrian M, Boeckmann, Brigitte, Capella-Gutierrez, Salvador, Dalquen, Daniel A, DeLuca, Todd, Forslund, Kristoffer, Huerta-Cepas, Jaime, Linard, Benjamin, Pereira, Cécile, Pryszcz, Leszek P, Schreiber, Fabian, da Silva, Alan Sousa, Szklarczyk, Damian, Train, Clément-Marie, Bork, Peer, Lecompte, Odile, von Mering, Christian, Xenarios, Ioannis, Sjölander, Kimmen, Jensen, Lars Juhl, Martin, Maria J, Muffato, Matthieu, Quest for Orthologs consortium, Gabaldón, Toni, Lewis, Suzanna E, Thomas, Paul D, Sonnhammer, Erik, Dessimoz, Christophe, Altenhoff, Adrian M, Altenhoff, Adrian M, Boeckmann, Brigitte, Capella-Gutierrez, Salvador, Dalquen, Daniel A, DeLuca, Todd, Forslund, Kristoffer, Huerta-Cepas, Jaime, Linard, Benjamin, Pereira, Cécile, Pryszcz, Leszek P, Schreiber, Fabian, da Silva, Alan Sousa, Szklarczyk, Damian, Train, Clément-Marie, Bork, Peer, Lecompte, Odile, von Mering, Christian, Xenarios, Ioannis, Sjölander, Kimmen, Jensen, Lars Juhl, Martin, Maria J, Muffato, Matthieu, Quest for Orthologs consortium, Gabaldón, Toni, Lewis, Suzanna E, Thomas, Paul D, Sonnhammer, Erik, and Dessimoz, Christophe

Abstract

Achieving high accuracy in orthology inference is essential for many comparative, evolutionary and functional genomic analyses, yet the true evolutionary history of genes is generally unknown and orthologs are used for very different applications across phyla, requiring different precision-recall trade-offs. As a result, it is difficult to assess the performance of orthology inference methods. Here, we present a community effort to establish standards and an automated web-based service to facilitate orthology benchmarking. Using this service, we characterize 15 well-established inference methods and resources on a battery of 20 different benchmarks. Standardized benchmarking provides a way for users to identify the most effective methods for the problem at hand, sets a minimum requirement for new tools and resources, and guides the development of more accurate orthology inference methods.

Published
2016

20. Standardized benchmarking in the quest for orthologs

Author

Altenhoff, Adrian M, Boeckmann, Brigitte, Capella-Gutierrez, Salvador, Dalquen, Daniel A, DeLuca, Todd, Forslund, Kristoffer, Huerta-Cepas, Jaime, Linard, Benjamin, Pereira, Cécile, Pryszcz, Leszek P, Schreiber, Fabian, da Silva, Alan Sousa, Szklarczyk, Damian, Train, Clément-Marie, Bork, Peer, Lecompte, Odile, von Mering, Christian, Xenarios, Ioannis, Sjölander, Kimmen, Jensen, Lars Juhl, Martin, Maria J, Muffato, Matthieu, Gabaldón, Toni, Lewis, Suzanna E, Thomas, Paul D, Sonnhammer, Erik, Dessimoz, Christophe, Altenhoff, Adrian M, Boeckmann, Brigitte, Capella-Gutierrez, Salvador, Dalquen, Daniel A, DeLuca, Todd, Forslund, Kristoffer, Huerta-Cepas, Jaime, Linard, Benjamin, Pereira, Cécile, Pryszcz, Leszek P, Schreiber, Fabian, da Silva, Alan Sousa, Szklarczyk, Damian, Train, Clément-Marie, Bork, Peer, Lecompte, Odile, von Mering, Christian, Xenarios, Ioannis, Sjölander, Kimmen, Jensen, Lars Juhl, Martin, Maria J, Muffato, Matthieu, Gabaldón, Toni, Lewis, Suzanna E, Thomas, Paul D, Sonnhammer, Erik, and Dessimoz, Christophe

Abstract

Achieving high accuracy in orthology inference is essential for many comparative, evolutionary and functional genomic analyses, yet the true evolutionary history of genes is generally unknown and orthologs are used for very different applications across phyla, requiring different precision-recall trade-offs. As a result, it is difficult to assess the performance of orthology inference methods. Here, we present a community effort to establish standards and an automated web-based service to facilitate orthology benchmarking. Using this service, we characterize 15 well-established inference methods and resources on a battery of 20 different benchmarks. Standardized benchmarking provides a way for users to identify the most effective methods for the problem at hand, sets a minimum requirement for new tools and resources, and guides the development of more accurate orthology inference methods.

Published
2016

21. An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Author

Jiang, Yuxiang, Oron, Tal Ronnen, Clark, Wyatt T., Bankapur, Asma R., D'Andrea, Daniel, Lepore, Rosalba, Funk, Christopher S., Kahanda, Indika, Verspoor, Karin M., Ben-Hur, Asa, Koo, Da Chen Emily, Penfold-Brown, Duncan, Shasha, Dennis, Youngs, Noah, Bonneau, Richard, Lin, Alexandra, Sahraeian, Sayed M.E., Martelli, Pier Luigi, Profiti, Giuseppe, Casadio, Rita, Cao, Renzhi, Zhong, Zhaolong, Cheng, Jianlin, Altenhoff, Adrian, Skunca, Nives, Dessimoz, Christophe, Dogan, Tunca, Hakala, Kai, Kaewphan, Suwisa, Mehryary, Farrokh, Salakoski, Tapio, Ginter, Filip, Fang, Hai, Smithers, Ben, Oates, Matt, Gough, Julian, Törönen, Petri, Koskinen, Patrik, Holm, Liisa, Chen, Ching Tai, Hsu, Wen Lian, Bryson, Kevin, Cozzetto, Domenico, Minneci, Federico, Jones, David T., Chapman, Samuel, BKC, Dukka, Khan, Ishita K., Kihara, Daisuke, Ofer, Dan, Rappoport, Nadav, Stern, Amos, Cibrian-Uhalte, Elena, Denny, Paul, Foulger, Rebecca E., Hieta, Reija, Legge, Duncan, Lovering, Ruth C., Magrane, Michele, Melidoni, Anna N., Mutowo-Meullenet, Prudence, Pichler, Klemens, Shypitsyna, Aleksandra, Li, Biao, Zakeri, Pooya, ElShal, Sarah, Tranchevent, Léon Charles, Das, Sayoni, Dawson, Natalie L., Lee, David, Lees, Jonathan G., Sillitoe, Ian, Bhat, Prajwal, Nepusz, Tamás, Romero, Alfonso E., Sasidharan, Rajkumar, Yang, Haixuan, Paccanaro, Alberto, Gillis, Jesse, Sedeño-Cortés, Adriana E., Pavlidis, Paul, Feng, Shou, Cejuela, Juan M., Goldberg, Tatyana, Hamp, Tobias, Richter, Lothar, Salamov, Asaf, Gabaldon, Toni, Marcet-Houben, Marina, Supek, Fran, Gong, Qingtian, Ning, Wei, Zhou, Yuanpeng, Tian, Weidong, Falda, Marco, Fontana, Paolo, Lavezzo, Enrico, Toppo, Stefano, Ferrari, Carlo, Giollo, Manuel, Piovesan, Damiano, Tosatto, Silvio C.E., del Pozo, Angela, Fernández, José M., Maietta, Paolo, Valencia, Alfonso, Tress, Michael L., Benso, Alfredo, Di Carlo, Stefano, Politano, Gianfranco, Savino, Alessandro, Rehman, Hafeez Ur, Re, Matteo, Mesiti, Marco, Valentini, Giorgio, Bargsten, Joachim W., van Dijk, Aalt-Jan, Gemovic, Branislava, Glisic, Sanja, Perovic, Vladmir, Veljkovic, Veljko, Veljkovic, Nevena, Almeida-e-Silva, Danillo C., Vencio, Ricardo Z.N., Sharan, Malvika, Vogel, Jörg, Kansakar, Lakesh, Zhang, Shanshan, Vucetic, Slobodan, Wang, Zheng, Sternberg, Michael J.E., Wass, Mark N., Huntley, Rachael P., Martin, Maria J., O'Donovan, Claire, Robinson, Peter N., Moreau, Yves, Tramontano, Anna, Babbitt, Patricia C., Brenner, Steven E., Linial, Michal, Orengo, Christine A., Rost, Burkhard, Greene, Casey S., Mooney, Sean D., Friedberg, Iddo, Radivojac, Predrag, Jiang, Yuxiang, Oron, Tal Ronnen, Clark, Wyatt T., Bankapur, Asma R., D'Andrea, Daniel, Lepore, Rosalba, Funk, Christopher S., Kahanda, Indika, Verspoor, Karin M., Ben-Hur, Asa, Koo, Da Chen Emily, Penfold-Brown, Duncan, Shasha, Dennis, Youngs, Noah, Bonneau, Richard, Lin, Alexandra, Sahraeian, Sayed M.E., Martelli, Pier Luigi, Profiti, Giuseppe, Casadio, Rita, Cao, Renzhi, Zhong, Zhaolong, Cheng, Jianlin, Altenhoff, Adrian, Skunca, Nives, Dessimoz, Christophe, Dogan, Tunca, Hakala, Kai, Kaewphan, Suwisa, Mehryary, Farrokh, Salakoski, Tapio, Ginter, Filip, Fang, Hai, Smithers, Ben, Oates, Matt, Gough, Julian, Törönen, Petri, Koskinen, Patrik, Holm, Liisa, Chen, Ching Tai, Hsu, Wen Lian, Bryson, Kevin, Cozzetto, Domenico, Minneci, Federico, Jones, David T., Chapman, Samuel, BKC, Dukka, Khan, Ishita K., Kihara, Daisuke, Ofer, Dan, Rappoport, Nadav, Stern, Amos, Cibrian-Uhalte, Elena, Denny, Paul, Foulger, Rebecca E., Hieta, Reija, Legge, Duncan, Lovering, Ruth C., Magrane, Michele, Melidoni, Anna N., Mutowo-Meullenet, Prudence, Pichler, Klemens, Shypitsyna, Aleksandra, Li, Biao, Zakeri, Pooya, ElShal, Sarah, Tranchevent, Léon Charles, Das, Sayoni, Dawson, Natalie L., Lee, David, Lees, Jonathan G., Sillitoe, Ian, Bhat, Prajwal, Nepusz, Tamás, Romero, Alfonso E., Sasidharan, Rajkumar, Yang, Haixuan, Paccanaro, Alberto, Gillis, Jesse, Sedeño-Cortés, Adriana E., Pavlidis, Paul, Feng, Shou, Cejuela, Juan M., Goldberg, Tatyana, Hamp, Tobias, Richter, Lothar, Salamov, Asaf, Gabaldon, Toni, Marcet-Houben, Marina, Supek, Fran, Gong, Qingtian, Ning, Wei, Zhou, Yuanpeng, Tian, Weidong, Falda, Marco, Fontana, Paolo, Lavezzo, Enrico, Toppo, Stefano, Ferrari, Carlo, Giollo, Manuel, Piovesan, Damiano, Tosatto, Silvio C.E., del Pozo, Angela, Fernández, José M., Maietta, Paolo, Valencia, Alfonso, Tress, Michael L., Benso, Alfredo, Di Carlo, Stefano, Politano, Gianfranco, Savino, Alessandro, Rehman, Hafeez Ur, Re, Matteo, Mesiti, Marco, Valentini, Giorgio, Bargsten, Joachim W., van Dijk, Aalt-Jan, Gemovic, Branislava, Glisic, Sanja, Perovic, Vladmir, Veljkovic, Veljko, Veljkovic, Nevena, Almeida-e-Silva, Danillo C., Vencio, Ricardo Z.N., Sharan, Malvika, Vogel, Jörg, Kansakar, Lakesh, Zhang, Shanshan, Vucetic, Slobodan, Wang, Zheng, Sternberg, Michael J.E., Wass, Mark N., Huntley, Rachael P., Martin, Maria J., O'Donovan, Claire, Robinson, Peter N., Moreau, Yves, Tramontano, Anna, Babbitt, Patricia C., Brenner, Steven E., Linial, Michal, Orengo, Christine A., Rost, Burkhard, Greene, Casey S., Mooney, Sean D., Friedberg, Iddo, and Radivojac, Predrag

Abstract

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.

Published
2016

22. Standardized benchmarking in the quest for orthologs

Author

Altenhoff, Adrian M, Boeckmann, Brigitte, Capella-Gutierrez, Salvador, Dalquen, Daniel A, DeLuca, Todd, Forslund, Kristoffer, Huerta-Cepas, Jaime, Linard, Benjamin, Pereira, Cécile, Pryszcz, Leszek P, Schreiber, Fabian, da Silva, Alan Sousa, Szklarczyk, Damian, Train, Clément-Marie, Bork, Peer, Lecompte, Odile, von Mering, Christian, Xenarios, Ioannis, Sjölander, Kimmen, Jensen, Lars Juhl, Martin, Maria J, Muffato, Matthieu, Gabaldón, Toni, Lewis, Suzanna E, Thomas, Paul D, Sonnhammer, Erik, Dessimoz, Christophe, Altenhoff, Adrian M, Boeckmann, Brigitte, Capella-Gutierrez, Salvador, Dalquen, Daniel A, DeLuca, Todd, Forslund, Kristoffer, Huerta-Cepas, Jaime, Linard, Benjamin, Pereira, Cécile, Pryszcz, Leszek P, Schreiber, Fabian, da Silva, Alan Sousa, Szklarczyk, Damian, Train, Clément-Marie, Bork, Peer, Lecompte, Odile, von Mering, Christian, Xenarios, Ioannis, Sjölander, Kimmen, Jensen, Lars Juhl, Martin, Maria J, Muffato, Matthieu, Gabaldón, Toni, Lewis, Suzanna E, Thomas, Paul D, Sonnhammer, Erik, and Dessimoz, Christophe

Abstract

Achieving high accuracy in orthology inference is essential for many comparative, evolutionary and functional genomic analyses, yet the true evolutionary history of genes is generally unknown and orthologs are used for very different applications across phyla, requiring different precision-recall trade-offs. As a result, it is difficult to assess the performance of orthology inference methods. Here, we present a community effort to establish standards and an automated web-based service to facilitate orthology benchmarking. Using this service, we characterize 15 well-established inference methods and resources on a battery of 20 different benchmarks. Standardized benchmarking provides a way for users to identify the most effective methods for the problem at hand, sets a minimum requirement for new tools and resources, and guides the development of more accurate orthology inference methods.

Published
2016

23. The COMBREX project: design, methodology, and initial results

Author

Anton, Brian P., Chang, Yi-Chien, Brown, Peter, Choi, Han-Pil, Faller, Lina L., Guleria, Jyotsna, Hu, Zhenjun, Klitgord, Niels, Levy-Moonshine, Ami, Maksad, Almaz, Mazumdar, Varun, McGettrick, Mark, Osmani, Lais, Pokrzywa, Revonda, Rachlin, John, Swaminathan, Rajeswari, Allen, Benjamin, Housman, Genevieve, Monahan, Caitlin, Rochussen, Krista, Tao, Kevin, Bhagwat, Ashok S., Brenner, Steven E., Columbus, Linda, Crécy-Lagard, Valérie de, Ferguson, Donald, Fomenkov, Alexey, Gadda, Giovanni, Morgan, Richard D., Osterman, Andrei L., Rodionov, Dmitry A., Rodionova, Irina A., Rudd, Kenneth E., Söll, Dieter, Spain, James, Xu, Shuang-Yong, Bateman, Alex, Blumenthal, Robert M., Bollinger, J. Martin, Chang, Woo-Suk, Ferrer, Manuel, Friedberg, Iddo, Galperin, Michael Y., Gobeill, Julien, Haft, Daniel, Hunt, John, Karp, Peter, Klimke, William, Krebs, Carsten, Macelis, Dana, Madupu, Ramana, Martin, Maria J., Miller, Jeffrey H., O'Donovan, Claire, Palsson, Bernhard, Ruch, Patrick, Setterdahl, Aaron, Sutton, Granger, Tate, John, Yakunin, Alexander, Tchigvintsev, Dmitri, Plata, Germán, Hu, Jie, Greiner, Russell, Horn, David, Sjölander, Kimmen, Salzberg, Steven L., Vitkup, Dennis, Letovsky, Stanley, Segrè, Daniel, DeLisi, Charles, Roberts, Richard J., Steffen, Martin, Kasif, Simon, Anton, Brian P., Chang, Yi-Chien, Brown, Peter, Choi, Han-Pil, Faller, Lina L., Guleria, Jyotsna, Hu, Zhenjun, Klitgord, Niels, Levy-Moonshine, Ami, Maksad, Almaz, Mazumdar, Varun, McGettrick, Mark, Osmani, Lais, Pokrzywa, Revonda, Rachlin, John, Swaminathan, Rajeswari, Allen, Benjamin, Housman, Genevieve, Monahan, Caitlin, Rochussen, Krista, Tao, Kevin, Bhagwat, Ashok S., Brenner, Steven E., Columbus, Linda, Crécy-Lagard, Valérie de, Ferguson, Donald, Fomenkov, Alexey, Gadda, Giovanni, Morgan, Richard D., Osterman, Andrei L., Rodionov, Dmitry A., Rodionova, Irina A., Rudd, Kenneth E., Söll, Dieter, Spain, James, Xu, Shuang-Yong, Bateman, Alex, Blumenthal, Robert M., Bollinger, J. Martin, Chang, Woo-Suk, Ferrer, Manuel, Friedberg, Iddo, Galperin, Michael Y., Gobeill, Julien, Haft, Daniel, Hunt, John, Karp, Peter, Klimke, William, Krebs, Carsten, Macelis, Dana, Madupu, Ramana, Martin, Maria J., Miller, Jeffrey H., O'Donovan, Claire, Palsson, Bernhard, Ruch, Patrick, Setterdahl, Aaron, Sutton, Granger, Tate, John, Yakunin, Alexander, Tchigvintsev, Dmitri, Plata, Germán, Hu, Jie, Greiner, Russell, Horn, David, Sjölander, Kimmen, Salzberg, Steven L., Vitkup, Dennis, Letovsky, Stanley, Segrè, Daniel, DeLisi, Charles, Roberts, Richard J., Steffen, Martin, and Kasif, Simon

Abstract

Experimental data exists for only a vanishingly small fraction of sequenced microbial genes. This community page discusses the progress made by the COMBREX project to address this important issue using both computational and experimental resources.

Published
2014

24. The Universal Protein Resource (UniProt): an expanding universe of protein information

Author

Wu, Cathy H., Apweiler, Rolf, Bairoch, Amos, Natale, Darren A., Barker, Winona C., Boeckmann, Brigitte, Ferro, Serenella, Gasteiger, Elisabeth, Huang, Hongzhan, Lopez, Rodrigo, Magrane, Michele, Martin, Maria J., Mazumder, Raja, O'Donovan, Claire, Redaschi, Nicole, Suzek, Baris, Wu, Cathy H., Apweiler, Rolf, Bairoch, Amos, Natale, Darren A., Barker, Winona C., Boeckmann, Brigitte, Ferro, Serenella, Gasteiger, Elisabeth, Huang, Hongzhan, Lopez, Rodrigo, Magrane, Michele, Martin, Maria J., Mazumder, Raja, O'Donovan, Claire, Redaschi, Nicole, and Suzek, Baris

Abstract

The Universal Protein Resource (UniProt) provides a central resource on protein sequences and functional annotation with three database components, each addressing a key need in protein bioinformatics. The UniProt Knowledgebase (UniProtKB), comprising the manually annotated UniProtKB/Swiss-Prot section and the automatically annotated UniProtKB/TrEMBL section, is the preeminent storehouse of protein annotation. The extensive cross-references, functional and feature annotations and literature-based evidence attribution enable scientists to analyse proteins and query across databases. The UniProt Reference Clusters (UniRef) speed similarity searches via sequence space compression by merging sequences that are 100% (UniRef100), 90% (UniRef90) or 50% (UniRef50) identical. Finally, the UniProt Archive (UniParc) stores all publicly available protein sequences, containing the history of sequence data with links to the source databases. UniProt databases continue to grow in size and in availability of information. Recent and upcoming changes to database contents, formats, controlled vocabularies and services are described. New download availability includes all major releases of UniProtKB, sequence collections by taxonomic division and complete proteomes. A bibliography mapping service has been added, and an ID mapping service will be available soon. UniProt databases can be accessed online at http://www.uniprot.org or downloaded at ftp://ftp.uniprot.org/pub/databases

25. The COMBREX project: design, methodology, and initial results

Author

Anton, Brian P., Chang, Yi-Chien, Brown, Peter, Choi, Han-Pil, Faller, Lina L., Guleria, Jyotsna, Hu, Zhenjun, Klitgord, Niels, Levy-Moonshine, Ami, Maksad, Almaz, Mazumdar, Varun, McGettrick, Mark, Osmani, Lais, Pokrzywa, Revonda, Rachlin, John, Swaminathan, Rajeswari, Allen, Benjamin, Housman, Genevieve, Monahan, Caitlin, Rochussen, Krista, Tao, Kevin, Bhagwat, Ashok S., Brenner, Steven E., Columbus, Linda, Crécy-Lagard, Valérie de, Ferguson, Donald, Fomenkov, Alexey, Gadda, Giovanni, Morgan, Richard D., Osterman, Andrei L., Rodionov, Dmitry A., Rodionova, Irina A., Rudd, Kenneth E., Söll, Dieter, Spain, James, Xu, Shuang-Yong, Bateman, Alex, Blumenthal, Robert M., Bollinger, J. Martin, Chang, Woo-Suk, Ferrer, Manuel, Friedberg, Iddo, Galperin, Michael Y., Gobeill, Julien, Haft, Daniel, Hunt, John, Karp, Peter, Klimke, William, Krebs, Carsten, Macelis, Dana, Madupu, Ramana, Martin, Maria J., Miller, Jeffrey H., O'Donovan, Claire, Palsson, Bernhard, Ruch, Patrick, Setterdahl, Aaron, Sutton, Granger, Tate, John, Yakunin, Alexander, Tchigvintsev, Dmitri, Plata, Germán, Hu, Jie, Greiner, Russell, Horn, David, Sjölander, Kimmen, Salzberg, Steven L., Vitkup, Dennis, Letovsky, Stanley, Segrè, Daniel, DeLisi, Charles, Roberts, Richard J., Steffen, Martin, Kasif, Simon, Anton, Brian P., Chang, Yi-Chien, Brown, Peter, Choi, Han-Pil, Faller, Lina L., Guleria, Jyotsna, Hu, Zhenjun, Klitgord, Niels, Levy-Moonshine, Ami, Maksad, Almaz, Mazumdar, Varun, McGettrick, Mark, Osmani, Lais, Pokrzywa, Revonda, Rachlin, John, Swaminathan, Rajeswari, Allen, Benjamin, Housman, Genevieve, Monahan, Caitlin, Rochussen, Krista, Tao, Kevin, Bhagwat, Ashok S., Brenner, Steven E., Columbus, Linda, Crécy-Lagard, Valérie de, Ferguson, Donald, Fomenkov, Alexey, Gadda, Giovanni, Morgan, Richard D., Osterman, Andrei L., Rodionov, Dmitry A., Rodionova, Irina A., Rudd, Kenneth E., Söll, Dieter, Spain, James, Xu, Shuang-Yong, Bateman, Alex, Blumenthal, Robert M., Bollinger, J. Martin, Chang, Woo-Suk, Ferrer, Manuel, Friedberg, Iddo, Galperin, Michael Y., Gobeill, Julien, Haft, Daniel, Hunt, John, Karp, Peter, Klimke, William, Krebs, Carsten, Macelis, Dana, Madupu, Ramana, Martin, Maria J., Miller, Jeffrey H., O'Donovan, Claire, Palsson, Bernhard, Ruch, Patrick, Setterdahl, Aaron, Sutton, Granger, Tate, John, Yakunin, Alexander, Tchigvintsev, Dmitri, Plata, Germán, Hu, Jie, Greiner, Russell, Horn, David, Sjölander, Kimmen, Salzberg, Steven L., Vitkup, Dennis, Letovsky, Stanley, Segrè, Daniel, DeLisi, Charles, Roberts, Richard J., Steffen, Martin, and Kasif, Simon

Abstract

Experimental data exists for only a vanishingly small fraction of sequenced microbial genes. This community page discusses the progress made by the COMBREX project to address this important issue using both computational and experimental resources.

26. The Universal Protein Resource (UniProt): an expanding universe of protein information

Author

Wu, Cathy H., Apweiler, Rolf, Bairoch, Amos, Natale, Darren A., Barker, Winona C., Boeckmann, Brigitte, Ferro, Serenella, Gasteiger, Elisabeth, Huang, Hongzhan, Lopez, Rodrigo, Magrane, Michele, Martin, Maria J., Mazumder, Raja, O'Donovan, Claire, Redaschi, Nicole, Suzek, Baris, Wu, Cathy H., Apweiler, Rolf, Bairoch, Amos, Natale, Darren A., Barker, Winona C., Boeckmann, Brigitte, Ferro, Serenella, Gasteiger, Elisabeth, Huang, Hongzhan, Lopez, Rodrigo, Magrane, Michele, Martin, Maria J., Mazumder, Raja, O'Donovan, Claire, Redaschi, Nicole, and Suzek, Baris

Abstract

The Universal Protein Resource (UniProt) provides a central resource on protein sequences and functional annotation with three database components, each addressing a key need in protein bioinformatics. The UniProt Knowledgebase (UniProtKB), comprising the manually annotated UniProtKB/Swiss-Prot section and the automatically annotated UniProtKB/TrEMBL section, is the preeminent storehouse of protein annotation. The extensive cross-references, functional and feature annotations and literature-based evidence attribution enable scientists to analyse proteins and query across databases. The UniProt Reference Clusters (UniRef) speed similarity searches via sequence space compression by merging sequences that are 100% (UniRef100), 90% (UniRef90) or 50% (UniRef50) identical. Finally, the UniProt Archive (UniParc) stores all publicly available protein sequences, containing the history of sequence data with links to the source databases. UniProt databases continue to grow in size and in availability of information. Recent and upcoming changes to database contents, formats, controlled vocabularies and services are described. New download availability includes all major releases of UniProtKB, sequence collections by taxonomic division and complete proteomes. A bibliography mapping service has been added, and an ID mapping service will be available soon. UniProt databases can be accessed online at http://www.uniprot.org or downloaded at ftp://ftp.uniprot.org/pub/databases

27. The Universal Protein Resource (UniProt)

Author

Bairoch, Amos, Apweiler, Rolf, Wu, Cathy H., Barker, Winona C., Boeckmann, Brigitte, Ferro, Serenella, Gasteiger, Elisabeth, Huang, Hongzhan, Lopez, Rodrigo, Magrane, Michele, Martin, Maria J., Natale, Darren A., O'Donovan, Claire, Redaschi, Nicole, Yeh, Lai-Su L., Bairoch, Amos, Apweiler, Rolf, Wu, Cathy H., Barker, Winona C., Boeckmann, Brigitte, Ferro, Serenella, Gasteiger, Elisabeth, Huang, Hongzhan, Lopez, Rodrigo, Magrane, Michele, Martin, Maria J., Natale, Darren A., O'Donovan, Claire, Redaschi, Nicole, and Yeh, Lai-Su L.

Abstract

The Universal Protein Resource (UniProt) provides the scientific community with a single, centralized, authoritative resource for protein sequences and functional information. Formed by uniting the Swiss-Prot, TrEMBL and PIR protein database activities, the UniProt consortium produces three layers of protein sequence databases: the UniProt Archive (UniParc), the UniProt Knowledgebase (UniProt) and the UniProt Reference (UniRef) databases. The UniProt Knowledgebase is a comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase with extensive cross-references. This centrepiece consists of two sections: UniProt/Swiss-Prot, with fully, manually curated entries; and UniProt/TrEMBL, enriched with automated classification and annotation. During 2004, tens of thousands of Knowledgebase records got manually annotated or updated; we introduced a new comment line topic: TOXIC DOSE to store information on the acute toxicity of a toxin; the UniProt keyword list got augmented by additional keywords; we improved the documentation of the keywords and are continuously overhauling and standardizing the annotation of post-translational modifications. Furthermore, we introduced a new documentation file of the strains and their synonyms. Many new database cross-references were introduced and we started to make use of Digital Object Identifiers. We also achieved in collaboration with the Macromolecular Structure Database group at EBI an improved integration with structural databases by residue level mapping of sequences from the Protein Data Bank entries onto corresponding UniProt entries. For convenient sequence searches we provide the UniRef non-redundant sequence databases. The comprehensive UniParc database stores the complete body of publicly available protein sequence data. The UniProt databases can be accessed online (http://www.uniprot.org) or downloaded in several formats (ftp://ftp.uniprot.org/pub). New releases are published every two week

28. The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003

Author

Boeckmann, Brigitte, Bairoch, Amos, Apweiler, Rolf, Blatter, Marie-Claude, Estreicher, Anne, Gasteiger, Elisabeth, Martin, Maria J., Michoud, Karine, O'Donovan, Claire, Phan, Isabelle, Pilbout, Sandrine, Schneider, Michel, Boeckmann, Brigitte, Bairoch, Amos, Apweiler, Rolf, Blatter, Marie-Claude, Estreicher, Anne, Gasteiger, Elisabeth, Martin, Maria J., Michoud, Karine, O'Donovan, Claire, Phan, Isabelle, Pilbout, Sandrine, and Schneider, Michel

Abstract

The SWISS-PROT protein knowledgebase (http://www.expasy.org/sprot/ and http://www.ebi.ac.uk/swissprot/) connects amino acid sequences with the current knowledge in the Life Sciences. Each protein entry provides an interdisciplinary overview of relevant information by bringing together experimental results, computed features and sometimes even contradictory conclusions. Detailed expertise that goes beyond the scope of SWISS-PROT is made available via direct links to specialised databases. SWISS-PROT provides annotated entries for all species, but concentrates on the annotation of entries from human (the HPI project) and other model organisms to ensure the presence of high quality annotation for representative members of all protein families. Part of the annotation can be transferred to other family members, as is already done for microbes by the High-quality Automated and Manual Annotation of microbial Proteomes (HAMAP) project. Protein families and groups of proteins are regularly reviewed to keep up with current scientific findings. Complementarily, TrEMBL strives to comprise all protein sequences that are not yet represented in SWISS-PROT, by incorporating a perpetually increasing level of mostly automated annotation. Researchers are welcome to contribute their knowledge to the scientific community by submitting relevant findings to SWISS-PROT at swiss-prot@expasy.org

29. The UniProt-GO Annotation database in 2011

Author

Dimmer, Emily C., Huntley, Rachael P., Alam-Faruque, Yasmin, Sawford, Tony, O'Donovan, Claire, Martin, Maria J., Bely, Benoit, Browne, Paul, Mun Chan, Wei, Eberhardt, Ruth, Gardner, Michael, Laiho, Kati, Legge, Duncan, Magrane, Michele, Pichler, Klemens, Poggioli, Diego, Sehra, Harminder, Auchincloss, Andrea, Axelsen, Kristian, Blatter, Marie-Claude, Boutet, Emmanuel, Braconi-Quintaje, Silvia, Breuza, Lionel, Bridge, Alan, Coudert, Elizabeth, Estreicher, Anne, Famiglietti, Livia, Ferro-Rojas, Serenella, Feuermann, Marc, Gos, Arnaud, Gruaz-Gumowski, Nadine, Hinz, Ursula, Hulo, Chantal, James, Janet, Jimenez, Silvia, Jungo, Florence, Keller, Guillaume, Lemercier, Phillippe, Lieberherr, Damien, Masson, Patrick, Moinat, Madelaine, Pedruzzi, Ivo, Poux, Sylvain, Rivoire, Catherine, Roechert, Bernd, Schneider, Michael, Stutz, Andre, Sundaram, Shyamala, Tognolli, Michael, Bougueleret, Lydie, Argoud-Puy, Ghislaine, Cusin, Isabelle, Duek- Roggli, Paula, Xenarios, Ioannis, Apweiler, Rolf, Dimmer, Emily C., Huntley, Rachael P., Alam-Faruque, Yasmin, Sawford, Tony, O'Donovan, Claire, Martin, Maria J., Bely, Benoit, Browne, Paul, Mun Chan, Wei, Eberhardt, Ruth, Gardner, Michael, Laiho, Kati, Legge, Duncan, Magrane, Michele, Pichler, Klemens, Poggioli, Diego, Sehra, Harminder, Auchincloss, Andrea, Axelsen, Kristian, Blatter, Marie-Claude, Boutet, Emmanuel, Braconi-Quintaje, Silvia, Breuza, Lionel, Bridge, Alan, Coudert, Elizabeth, Estreicher, Anne, Famiglietti, Livia, Ferro-Rojas, Serenella, Feuermann, Marc, Gos, Arnaud, Gruaz-Gumowski, Nadine, Hinz, Ursula, Hulo, Chantal, James, Janet, Jimenez, Silvia, Jungo, Florence, Keller, Guillaume, Lemercier, Phillippe, Lieberherr, Damien, Masson, Patrick, Moinat, Madelaine, Pedruzzi, Ivo, Poux, Sylvain, Rivoire, Catherine, Roechert, Bernd, Schneider, Michael, Stutz, Andre, Sundaram, Shyamala, Tognolli, Michael, Bougueleret, Lydie, Argoud-Puy, Ghislaine, Cusin, Isabelle, Duek- Roggli, Paula, Xenarios, Ioannis, and Apweiler, Rolf

Abstract

The GO annotation dataset provided by the UniProt Consortium (GOA: http://www.ebi.ac.uk/GOA) is a comprehensive set of evidenced-based associations between terms from the Gene Ontology resource and UniProtKB proteins. Currently supplying over 100 million annotations to 11 million proteins in more than 360 000 taxa, this resource has increased 2-fold over the last 2 years and has benefited from a wealth of checks to improve annotation correctness and consistency as well as now supplying a greater information content enabled by GO Consortium annotation format developments. Detailed, manual GO annotations obtained from the curation of peer-reviewed papers are directly contributed by all UniProt curators and supplemented with manual and electronic annotations from 36 model organism and domain-focused scientific resources. The inclusion of high-quality, automatic annotation predictions ensures the UniProt GO annotation dataset supplies functional information to a wide range of proteins, including those from poorly characterized, non-model organism species. UniProt GO annotations are freely available in a range of formats accessible by both file downloads and web-based views. In addition, the introduction of a new, normalized file format in 2010 has made for easier handling of the complete UniProt-GOA data set

30. UniProt: the Universal Protein knowledgebase

Author

Apweiler, Rolf, Bairoch, Amos, Wu, Cathy H., Barker, Winona C., Boeckmann, Brigitte, Ferro, Serenella, Gasteiger, Elisabeth, Huang, Hongzhan, Lopez, Rodrigo, Magrane, Michele, Martin, Maria J., Natale, Darren A., O'Donovan, Claire, Redaschi, Nicole, Yeh, Lai‐Su L., Apweiler, Rolf, Bairoch, Amos, Wu, Cathy H., Barker, Winona C., Boeckmann, Brigitte, Ferro, Serenella, Gasteiger, Elisabeth, Huang, Hongzhan, Lopez, Rodrigo, Magrane, Michele, Martin, Maria J., Natale, Darren A., O'Donovan, Claire, Redaschi, Nicole, and Yeh, Lai‐Su L.

Abstract

To provide the scientific community with a single, centralized, authoritative resource for protein sequences and functional information, the Swiss‐Prot, TrEMBL and PIR protein database activities have united to form the Universal Protein Knowledgebase (UniProt) consortium. Our mission is to provide a comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross‐references and query interfaces. The central database will have two sections, corresponding to the familiar Swiss‐Prot (fully manually curated entries) and TrEMBL (enriched with automated classification, annotation and extensive cross‐references). For convenient sequence searches, UniProt also provides several non‐redundant sequence databases. The UniProt NREF (UniRef) databases provide representative subsets of the knowledgebase suitable for efficient searching. The comprehensive UniProt Archive (UniParc) is updated daily from many public source databases. The UniProt databases can be accessed online (http://www.uniprot.org) or downloaded in several formats (ftp://ftp.uniprot.org/pub). The scientific community is encouraged to submit data for inclusion in UniProt

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