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

Y Jiang; TR Oron; WT Clark; AR Bankapur; D D'Andrea; R Lepore; CS Funk; I Kahanda; KM Verspoor; A Ben-Hur; DCE Koo; D Penfold-Brown; D Shasha; N Youngs; R Bonneau; A Lin; SME Sahraeian; PL Martelli; G Profiti; R Casadio; R Cao; Z Zhong; J Cheng; A Altenhoff; N Skunca; C Dessimoz; T Dogan; K Hakala; S Kaewphan; F Mehryary; T Salakoski; F Ginter; H Fang; B Smithers; M Oates; J Gough; P Törönen; P Koskinen; L Holm; CT Chen; WL Hsu; K Bryson; D Cozzetto; F Minneci; DT Jones; S Chapman; D Bkc; IK Khan; D Kihara; D Ofer; N Rappoport; A Stern; E Cibrian-Uhalte; P Denny; RE Foulger; R Hieta; D Legge; RC Lovering; M Magrane; AN Melidoni; P Mutowo-Meullenet; K Pichler; A Shypitsyna; B Li; P Zakeri; S ElShal; LC Tranchevent; S Das; NL Dawson; D Lee; JG Lees; I Sillitoe; P Bhat; T Nepusz; AE Romero; R Sasidharan; H Yang; A Paccanaro; J Gillis; AE Sedeño-Cortés; P Pavlidis; S Feng; JM Cejuela; T Goldberg; T Hamp; L Richter; A Salamov; T Gabaldon; M Marcet-Houben; F Supek; Q Gong; W Ning; Y Zhou; W Tian; M Falda; P Fontana; E Lavezzo; S Toppo; C Ferrari; M Giollo

Journal article

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

Y Jiang, TR Oron, WT Clark, AR Bankapur, D D'Andrea, R Lepore, CS Funk, I Kahanda, KM Verspoor, A Ben-Hur, DCE Koo, D Penfold-Brown, D Shasha, N Youngs, R Bonneau, A Lin, SME Sahraeian, PL Martelli, G Profiti, R Casadio Show all

Genome Biology | BIOMED CENTRAL LTD | Published : 2016

DOI: 10.1186/s13059-016-1037-6

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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..

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University of Melbourne Researchers

Karin Verspoor Author

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Funding Acknowledgements

We acknowledge the contributions of Maximilian Hecht, Alexander Grun, Julia Krumhoff, My Nguyen Ly, Jonathan Boidol, Rene Schoeffel, Yann Spori, Jessika Binder, Christoph Hamm and Karolina Worf. This work was partially supported by the following grants: National Science Foundation grants DBI-1458477 (PR), DBI-1458443 (SDM), DBI-1458390 (CSG), DBI-1458359 (IF), IIS-1319551 (DK), DBI-1262189 (DK), and DBI-1149224 (JC); National Institutes of Health grants R01GM093123 (JC), R01GM097528 (DK), R01GM076990 (PP), R01GM071749 (SEB), R01LM009722 (SDM), and UL1TR000423 (SDM); the National Natural Science Foundation of China grants 3147124 (WT) and 91231116 (WT); the National Basic Research Program of China grant 2012CB316505 (WT); NSERC grant RGPIN 371348-11 (PP); FP7 infrastructure project TransPLANT Award 283496 (ADJvD); Microsoft Research/FAPESP grant 2009/53161-6 and FAPESP fellowship 2010/50491-1 (DCAeS); Biotechnology and Biological Sciences Research Council grants BB/L020505/1 (DTJ), BB/F020481/1 (MJES), BB/K004131/1 (AP), BB/F00964X/1 (AP), and BB/L018241/1 (CD); the Spanish Ministry of Economics and Competitiveness grant BIO2012-40205 (MT); KU Leuven CoE PFV/10/016 SymBioSys (YM); the Newton International Fellowship Scheme of the Royal Society grant NF080750 (TN). CSG was supported in part by the Gordon and Betty Moore Foundation's Data-Driven Discovery Initiative grant GBMF4552. Computational resources were provided by CSC - IT Center for Science Ltd., Espoo, Finland (TS). This work was supported by the Academy of Finland (TS). RCL and ANM were supported by British Heart Foundation grant RG/13/5/30112. PD, RCL, and REF were supported by Parkinson's UK grant G-1307, the Alexander von Humboldt Foundation through the German Federal Ministry for Education and Research, Ernst Ludwig Ehrlich Studienwerk, and the Ministry of Education, Science and Technological Development of the Republic of Serbia grant 173001. This work was a Technology Development effort for ENIGMA - Ecosystems and Networks Integrated with Genes and Molecular Assemblies (http://enigma.lbl.gov), a Scientific Focus Area Program at Lawrence Berkeley National Laboratory, which is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Biological & Environmental Research grant DE-AC02-05CH11231. ENIGMA only covers the application of this work to microbial proteins. NSF DBI-0965616 and Australian Research Council grant DP150101550 (KMV). NSF DBI-0965768 (ABH). NIH T15 LM00945102 (training grant for CSF). FP7 FET grant MAESTRA ICT-2013-612944 and FP7 REGPOT grant InnoMol (FS). NIH R01 GM60595 (PCB). University of Padova grants CPDA138081/13 (ST) and GRIC13AAI9 (EL). Swiss National Science Foundation grant 150654 and UK BBSRC grant BB/M015009/1 (COD). PRB2 IPT13/0001 - ISCIII-SGEFI / FEDER (JMF).