NetGO 2.0: improving large-scale protein function prediction with massive sequence, text, domain, family and network information.
NetGO 2.0: improving large-scale protein function prediction with massive sequence, text, domain, family and network information.
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NetGO 2.0：利用海量序列、文本、域、家族和网络信息改进大规模蛋白质功能预测
DOI：
10.1093/nar/gkab398
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发表时间：
2021-07-02
影响因子：
14.9
通讯作者：
Zhu S
中科院分区：
文献类型：
--
作者：
Yao S;You R;Wang S;Xiong Y;Huang X;Zhu S
Abstract With the explosive growth of protein sequences, large-scale automated protein function prediction (AFP) is becoming challenging. A protein is usually associated with dozens of gene ontology (GO) terms. Therefore, AFP is regarded as a problem of large-scale multi-label classification. Under the learning to rank (LTR) framework, our previous NetGO tool integrated massive networks and multi-type information about protein sequences to achieve good performance by dealing with all possible GO terms (>44 000). In this work, we propose the updated version as NetGO 2.0, which further improves the performance of large-scale AFP. NetGO 2.0 also incorporates literature information by logistic regression and deep sequence information by recurrent neural network (RNN) into the framework. We generate datasets following the critical assessment of functional annotation (CAFA) protocol. Experiment results show that NetGO 2.0 outperformed NetGO significantly in biological process ontology (BPO) and cellular component ontology (CCO). In particular, NetGO 2.0 achieved a 12.6% improvement over NetGO in terms of area under precision-recall curve (AUPR) in BPO and around 2.6% in terms of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$\mathbf {F_{max}}$\end{document} in CCO. These results demonstrate the benefits of incorporating text and deep sequence information for the functional annotation of BPO and CCO. The NetGO 2.0 web server is freely available at http://issubmission.sjtu.edu.cn/ng2/.
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影响因子：
12.3
作者：
Jiang Y;Oron TR;Clark WT;Bankapur AR;D'Andrea D;Lepore R;Funk CS;Kahanda I;Verspoor KM;Ben-Hur A;Koo da CE;Penfold-Brown D;Shasha D;Youngs N;Bonneau R;Lin A;Sahraeian SM;Martelli PL;Profiti G;Casadio R;Cao R;Zhong Z;Cheng J;Altenhoff A;Skunca N;Dessimoz C;Dogan T;Hakala K;Kaewphan S;Mehryary F;Salakoski T;Ginter F;Fang H;Smithers B;Oates M;Gough J;Törönen P;Koskinen P;Holm L;Chen CT;Hsu WL;Bryson K;Cozzetto D;Minneci F;Jones DT;Chapman S;Bkc D;Khan IK;Kihara D;Ofer D;Rappoport N;Stern A;Cibrian-Uhalte E;Denny P;Foulger RE;Hieta R;Legge D;Lovering RC;Magrane M;Melidoni AN;Mutowo-Meullenet P;Pichler K;Shypitsyna A;Li B;Zakeri P;ElShal S;Tranchevent LC;Das S;Dawson NL;Lee D;Lees JG;Sillitoe I;Bhat P;Nepusz T;Romero AE;Sasidharan R;Yang H;Paccanaro A;Gillis J;Sedeño-Cortés AE;Pavlidis P;Feng S;Cejuela JM;Goldberg T;Hamp T;Richter L;Salamov A;Gabaldon T;Marcet-Houben M;Supek F;Gong Q;Ning W;Zhou Y;Tian W;Falda M;Fontana P;Lavezzo E;Toppo S;Ferrari C;Giollo M;Piovesan D;Tosatto SC;Del Pozo A;Fernández JM;Maietta P;Valencia A;Tress ML;Benso A;Di Carlo S;Politano G;Savino A;Rehman HU;Re M;Mesiti M;Valentini G;Bargsten JW;van Dijk AD;Gemovic B;Glisic S;Perovic V;Veljkovic V;Veljkovic N;Almeida-E-Silva DC;Vencio RZ;Sharan M;Vogel J;Kansakar L;Zhang S;Vucetic S;Wang Z;Sternberg MJ;Wass MN;Huntley RP;Martin MJ;O'Donovan C;Robinson PN;Moreau Y;Tramontano A;Babbitt PC;Brenner SE;Linial M;Orengo CA;Rost B;Greene CS;Mooney SD;Friedberg I;Radivojac P
通讯作者：
Radivojac P
影响因子：
14.9
作者：
Szklarczyk D;Morris JH;Cook H;Kuhn M;Wyder S;Simonovic M;Santos A;Doncheva NT;Roth A;Bork P;Jensen LJ;von Mering C
通讯作者：
von Mering C
DOI：
10.1093/bioinformatics/btu031
发表时间：
2014-05-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Jones P;Binns D;Chang HY;Fraser M;Li W;McAnulla C;McWilliam H;Maslen J;Mitchell A;Nuka G;Pesseat S;Quinn AF;Sangrador-Vegas A;Scheremetjew M;Yong SY;Lopez R;Hunter S
通讯作者：
Hunter S
影响因子：
12.3
作者：
Zhou, Naihui;Jiang, Yuxiang;Friedberg, Iddo
通讯作者：
Friedberg, Iddo
DOI：
10.1007/978-1-4939-3167-5_2
发表时间：
2016-01-01
期刊：
PLANT BIOINFORMATICS: METHODS AND PROTOCOLS, 2ND EDITION
影响因子：
--
作者：
Boutet, Emmanuel;Lieberherr, Damien;Xenarios, Ioannis
通讯作者：
Xenarios, Ioannis