Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12530/25307
Title: An expanded evaluation of protein function prediction methods shows an improvement in accuracy.
Authors: 
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
Brenner, Steven E
Bonneau, Richard
Linial, Michal
Orengo, Christine A
Rost, Burkhard
Greene, Casey S
Mooney, Sean D
Friedberg, Iddo
Radivojac, Predrag
Lin, Alexandra
Denny, Paul
Sahraeian, Sayed M E
Martelli, Pier Luigi
Profiti, Giuseppe
Casadio, Rita
Cao, Renzhi
Zhong, Zhaolong
Cheng, Jianlin
Altenhoff, Adrian
Skunca, Nives
Dessimoz, Christophe
Foulger, Rebecca E
Dogan, Tunca
Hakala, Kai
Kaewphan, Suwisa
Mehryary, Farrokh
Salakoski, Tapio
Ginter, Filip
Fang, Hai
Smithers, Ben
Oates, Matt
Gough, Julian
Hieta, Reija
Törönen, Petri
Koskinen, Patrik
Holm, Liisa
Chen, Ching-Tai
Hsu, Wen-Lian
Bryson, Kevin
Cozzetto, Domenico
Minneci, Federico
Jones, David T
Chapman, Samuel
Legge, Duncan
Bkc, Dukka
Khan, Ishita K
Kihara, Daisuke
Ofer, Dan
Rappoport, Nadav
Stern, Amos
Cibrian-Uhalte, Elena
Lovering, Ruth C
Magrane, Michele
Melidoni, Anna N
Mutowo-Meullenet, Prudence
Pichler, Klemens
Shypitsyna, Aleksandra
Piovesan, Damiano
Li, Biao
Zakeri, Pooya
ElShal, Sarah
Tranchevent, Léon-Charles
Das, Sayoni
Dawson, Natalie L
Lee, David
Lees, Jonathan G
Sillitoe, Ian
Bhat, Prajwal
Tosatto, Silvio C E
Nepusz, Tamás
Romero, Alfonso E
Sasidharan, Rajkumar
Yang, Haixuan
Paccanaro, Alberto
Gillis, Jesse
Sedeño-Cortés, Adriana E
Pavlidis, Paul
Feng, Shou
Cejuela, Juan M
Del Pozo, Angela
Goldberg, Tatyana
Hamp, Tobias
Richter, Lothar
Salamov, Asaf
Gabaldon, Toni
Marcet-Houben, Marina
Supek, Fran
Gong, Qingtian
Ning, Wei
Zhou, Yuanpeng
Fernández, José M
Tian, Weidong
Falda, Marco
Fontana, Paolo
Lavezzo, Enrico
Toppo, Stefano
Ferrari, Carlo
Giollo, Manuel
Maietta, Paolo
Valencia, Alfonso
Tress, Michael L
Benso, Alfredo
Di Carlo, Stefano
Politano, Gianfranco
Penfold-Brown, Duncan
Savino, Alessandro
Rehman, Hafeez Ur
Re, Matteo
Mesiti, Marco
Valentini, Giorgio
Bargsten, Joachim W
van Dijk, Aalt D J
Gemovic, Branislava
Glisic, Sanja
Perovic, Vladmir
Shasha, Dennis
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
Youngs, Noah
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
Keywords: Disease gene prioritization
Protein function prediction
Mesh: 
Issue Date: 2016
Citation: Genome Biol..2016 09;(17)1:184
Abstract: 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.
PMID: 27604469
URI: https://hdl.handle.net/20.500.12530/25307
Rights: openAccess
Appears in Collections:Fundaciones e Institutos de Investigación > IIS H. U. La Paz > Artículos
Hospitales > H. U. La Paz > Artículos

Files in This Item:
File Description SizeFormat 
PMC5015320.pdf3.06 MBAdobe PDFThumbnail
View/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.