The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens.
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Authors
Zhou, NaihuiJiang, 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
Gemovic, Branislava
Perovic, Vladimir R
Davidović, Radoslav S
Sumonja, Neven
Veljkovic, Nevena
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
Issue Date
2019-11-19
Metadata
Show full item recordAbstract
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.Citation
Genome Biol. 2019 Nov 19;20(1):244. doi: 10.1186/s13059-019-1835-8.Affiliation
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.Publisher
BMCJournal
Genome BiologyPubMed ID
31744546Type
ArticleLanguage
enISSN
1474-760Xae974a485f413a2113503eed53cd6c53
10.1186/s13059-019-1835-8
Scopus Count
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- Creative Commons
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 4.0 International
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