A large-scale evaluation of computational protein function prediction.
Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment. Fifty-four methods representing the state of the art for protein function prediction were evaluated on a target set of 866 proteins from 11 organisms. Two findings stand out: (i) today's best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is considerable need for improvement of currently available tools.
School of Informatics and Computing, Indiana University, Bloomington, Indiana, USA.
Predrag
P
Radivojac
Wyatt T
WT
Clark
Tal Ronnen
TR
Oron
Alexandra M
AM
Schnoes
Tobias
T
Wittkop
Artem
A
Sokolov
Kiley
K
Graim
Christopher
C
Funk
Karin
K
Verspoor
Asa
A
Ben-Hur
Gaurav
G
Pandey
Jeffrey M
JM
Yunes
Ameet S
AS
Talwalkar
Susanna
S
Repo
Michael L
ML
Souza
Damiano
D
Piovesan
Rita
R
Casadio
Zheng
Z
Wang
Jianlin
J
Cheng
Hai
H
Fang
Julian
J
Gough
Patrik
P
Koskinen
Petri
P
Törönen
Jussi
J
Nokso-Koivisto
Liisa
L
Holm
Domenico
D
Cozzetto
Daniel W A
DW
Buchan
Kevin
K
Bryson
David T
DT
Jones
Bhakti
B
Limaye
Harshal
H
Inamdar
Avik
A
Datta
Sunitha K
SK
Manjari
Rajendra
R
Joshi
Meghana
M
Chitale
Daisuke
D
Kihara
Andreas M
AM
Lisewski
Serkan
S
Erdin
Eric
E
Venner
Olivier
O
Lichtarge
Robert
R
Rentzsch
Haixuan
H
Yang
Alfonso E
AE
Romero
Prajwal
P
Bhat
Alberto
A
Paccanaro
Tobias
T
Hamp
Rebecca
R
Kaßner
Stefan
S
Seemayer
Esmeralda
E
Vicedo
Christian
C
Schaefer
Dominik
D
Achten
Florian
F
Auer
Ariane
A
Boehm
Tatjana
T
Braun
Maximilian
M
Hecht
Mark
M
Heron
Peter
P
Hönigschmid
Thomas A
TA
Hopf
Stefanie
S
Kaufmann
Michael
M
Kiening
Denis
D
Krompass
Cedric
C
Landerer
Yannick
Y
Mahlich
Manfred
M
Roos
Jari
J
Björne
Tapio
T
Salakoski
Andrew
A
Wong
Hagit
H
Shatkay
Fanny
F
Gatzmann
Ingolf
I
Sommer
Mark N
MN
Wass
Michael J E
MJ
Sternberg
Nives
N
Škunca
Fran
F
Supek
Matko
M
Bošnjak
Panče
P
Panov
Sašo
S
Džeroski
Tomislav
T
Šmuc
Yiannis A I
YA
Kourmpetis
Aalt D J
AD
van Dijk
Cajo J F
CJ
ter Braak
Yuanpeng
Y
Zhou
Qingtian
Q
Gong
Xinran
X
Dong
Weidong
W
Tian
Marco
M
Falda
Paolo
P
Fontana
Enrico
E
Lavezzo
Barbara
B
Di Camillo
Stefano
S
Toppo
Liang
L
Lan
Nemanja
N
Djuric
Yuhong
Y
Guo
Slobodan
S
Vucetic
Amos
A
Bairoch
Michal
M
Linial
Patricia C
PC
Babbitt
Steven E
SE
Brenner
Christine
C
Orengo
Burkhard
B
Rost
Sean D
SD
Mooney
Iddo
I
Friedberg
D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D005095:Exoribonucleases / Q000145:classification / Q000235:genetics / Q000502:physiology; D005544:Forecasting; D006801:Humans; D008967:Molecular Biology / Q000379:methods*; D058977:Molecular Sequence Annotation; D011506:Proteins / Q000737:chemistry / Q000145:classification / Q000235:genetics / Q000502:physiology*; D013045:Species Specificity; D024101:Mitochondrial Proteins
D005095:Exoribonucleases; D011506:Proteins; C476417:PNPT1 protein, human; D024101:Mitochondrial Proteins