Authors

Yuxiang Jiang, Indiana University
Tal Ronnen Oron, Buck Institute for Research On Agin
Wyatt T. Clark, Yale University
Asma R. Bankapur, Miami University
Daniel D'Andrea, University of Rome
Rosalba Lepore, University of Rome
Christopher S. Funk, University of Colorado
Indika Kahanda, Colorado State University
Karin M. Verspoor, University of Melbourne
Asa Ben-Hur, Colorado State University
Da Chen Emily Koo, New York University
Duncan Penfold-Brown, New York University
Dennis Shasha, New York University
Noah Youngs, New York University
Richard Bonneau, New York University
Alexandra Lin, University of California Berkeley
Sayed M.E. Sahraeian, University of California Berkeley
Pier Luigi Martelli, University of Bologna
Giuseppe Profiti, University of Bologna
Rita Casadio, University of Bologna
Renzhi Cao, University of Missouri
Zhaolong Zhong, University of Missouri
Jianlin Cheng, University of Missouri
Adrian Altenhoff, Swiss Institute of Bioinformatics
Nives Skunca, Swiss Instittue of Bioinformatics
Christophe Dessimoz, University College London
Tunca Dogan, European Bioinformatics Institute
Kai Hakala, University of Turku
Suwisa Kaewphan, University of Turku
Farrokh Mehryar, University of Turku
Tapio Salakoski, University of Turku
Filip Ginter, University of Turku
Hai Fang, University of Bristol
Ben Smithers, University of Bristol
Matt Oates, University of Bristol
Julian Gough, University of Bristol
Petri Törönen, University of Helsinki
Patrik Koskinen, University of Helsinki
Liisa Holm, University of Helsinki
Ching-Tai Chen, Academia Sinica
Wen-Lian Hsu, Academia Sinica
Kevin Bryson, University College London
Domenico Cozzetto, University College London
Federico Minneci, University College London
David T. Jones, University College London
Samuel Chapan, North Carolina AT&T State University
Dukka BKC, North Carolina AT&T State University
Ishita K. Khan, Purdue University
Daisuke Kihara, Purdue University
Dan Ofer, The Hebrew University of Jerusalem
Nadav Rappoport, The Hebrew University of Jerusalem
Amos Stern, The Hebrew University of Jerusalem
Elenia Cibrian-Uhalte, European Bioinformatics Institute
Paul Denny, University College London
Rebecca E. Foulger, University College London
Reija Hieta, European Bioinformatics Institute
Duncan Legge, European Bioinformatics Institute
Ruth C. Lovering, University College London
Michele Magrane, European Bioinformatics Institute
Anna N. Melidoni, University College London
Prudence Mutowo-Meullenet, European Bioinformatics Institute
Klemens Pichler, European Bioinformatics Institute
Aleksandra Shypitsyna, European Bioinformatics Institute
Biao Li, Buck Institute for Research On Aging
Pooya Zakeri, STADIUS Center for Dynamical Systems
Sarah ElShal, STADIUS Center for Dynamical Systems
Léon-Charles Tranchevent, Université de Lyon
Sayoni Das, University College London
Natalie L. Dawson, University College London
David Lee, University College London
Jonathan G. Lees, University College London
Ian Stilltoe, University College London
Prajwal Bhat, Cerenode Inc.
Tamás Nepusz, Molde University College
Alfonso E. Romero, Royal Holloway University of London
Rajkumar Sasidharan, University of California at Los Angeles
Haixuan Yang, National University of Ireland, Galway
Alberto Paccanaro, Royal Holloway University of London
Jesse Gillis, Stanley Institute for Cognitive Genomics Cold Spring Harbor Laboratory
Adriana E. Sedeño-Cortés, University of British Columbia
Paul Pavlidis, University of British Columbia
Shou Feng, Indiana University - Bloomington
Juan M. Cejuela, Technische Universität München
Tatyana Goldberg, Technische Universität München
Tobias Hamp, Technische Universität München
Lothar Richter, Technische Universität München
Asaf Salamov, DOE Joint Genome Institute
Toni Gabaldon, Centre for Genomic Regulation
Marina Marcet-Houben, Centre for Genomic Regulation
Fran Supek, Universitat Pompeu Fabra
Qingtian Gong, Fudan University
Wei Ning, Fudan University
Yuanpeng Zhou, Fudan University
Weidong Tian, Fudan University
Marco Falda, University of Padua
Paolo Fontana, Edmund Mach Foundation
Enrico Lavezzo, University of Padua
Stefano Toppo, University of Padua
Carlo Ferrari, University of Padua
Manuel Giollo, University of Padua
Damiano Piovesan, University of Padua
Silvio C.E. Tosatto, University of Padua
Angela del Pozo, Institute de Genetica Medica y Molecular
José M. Fernández, Spanish National Bioinformatics Institute
Paolo Maietta, Spanish National Cancer Research Institute
Alfonso Valencia, Spanish National Cancer Research Institute
Michael L. Tress, Spanish National Cancer Research Institute
Alfredo Benso, Politecnico di Torino
Stefano Di Carlo, Politecnico di Torino
Gianfranco Politano, Politecnico di Torino
Alessandro Savino, Politecnico di Torino
Hafeez Ur Rehman, National University of Computer & Emerging Sciences
Matteo Re, Università degli Studi di Milano
Marco Mesiti, Università degli Studi di Milano
Giorgio Valentini, Università degli Studi di Milano
Joachim W. Bargsten, Wageningen University and Research Centre
Aalt D.J. van Dijk, Wageningen University and Research Centre
Branislava Gemovic, University of Belgrade
Sanja Glisic, University of Belgrade
Vladmir Perovic, University of Belgrade
Veljko Veljkovic, University of Belgrade
Nevena Veljkovic, University of Belgrade
Danillo C. Almeida-e-Silva, University of Sao Paulo, Brazil
Ricardo Z.N. Vencio, University of Sao Paulo, Brazil
Malvika Sharan, University of Würzburg
Jörg Vogel, University of Würzburg
Lakesh Kansakar, Temple University
Shanshan Zhang, Temple University
Slobodan Vucetic, Temple University
Zheng Wang, University of Southern Mississippi
Michael J.E. Sternberg, Imperial College London
Mark N. Wass, University of Kent at Canterbury - U.K.
Rachael P. Huntley, European Bioinformatics Institute
Maria J. Martin, European Bioinformatics Institute
Claire O'Donovan, European Bioinformatics Institute
Peter N. Robinson, Institut für Medizinische Genetik und Humangenetik, Charité - Universitätsmedizin Berlin
Yves Moreau, Katholieke Universiteit Leuven
Anna Tramontano, University of Rome La Sapienza
Patricia C. Babbitt, University of California, San Francisco
Steven E. Brenner, University of California - Berkeley
Michal Linial, The Hebrew University of Jerusalem
Christine A. Orengo, University College London
Burkhard Rost, Technische Universität München
Casey S. Greene, University of Pennsylvania
Sean D. Mooney, University of Washington
Iddo Friedberg, Miami University - Oxford
Predrag Radivojac, Indiana University - Bloomington

Document Type

Article

Publication Date

9-7-2016

School

Computing Sciences and Computer Engineering

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.

Publication Title

Genome Biology

Volume

17

First Page

1

Last Page

19

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