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AFP can be regarded as a problem of the large-scale multi-label classification where a protein can be associated with multiple gene ontology terms as its labels. Based on our GOLabeler\u2014a state-of-the-art method for the third critical assessment of functional annotation (CAFA3), in this paper we propose NetGO, a web server that is able to further improve the performance of the large-scale AFP by incorporating massive protein-protein network information. Specifically, the advantages of NetGO are threefold in using network information: (i) NetGO relies on a powerful learning to rank framework from machine learning to effectively integrate both sequence and network information of proteins; (ii) NetGO uses the massive network information of all species (&gt;2000) in STRING (other than only some specific species) and (iii) NetGO still can use network information to annotate a protein by homology transfer, even if it is not contained in STRING. Separating training and testing data with the same time-delayed settings of CAFA, we comprehensively examined the performance of NetGO. Experimental results have clearly demonstrated that NetGO significantly outperforms GOLabeler and other competing methods. The NetGO web server is freely available at http:\/\/issubmission.sjtu.edu.cn\/netgo\/.<\/jats:p>","DOI":"10.1093\/nar\/gkz388","type":"journal-article","created":{"date-parts":[[2019,5,1]],"date-time":"2019-05-01T15:13:01Z","timestamp":1556723581000},"page":"W379-W387","source":"Crossref","is-referenced-by-count":125,"title":["NetGO: improving large-scale protein function prediction with massive network information"],"prefix":"10.1093","volume":"47","author":[{"given":"Ronghui","family":"You","sequence":"first","affiliation":[{"name":"School of Computer Science and Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai 200433, China"},{"name":"Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China"},{"name":"Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China"}]},{"given":"Shuwei","family":"Yao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai 200433, China"},{"name":"Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China"},{"name":"Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China"}]},{"given":"Yi","family":"Xiong","sequence":"additional","affiliation":[{"name":"Department of Bioinformatics and Biostatistics, Shanghai Jiao Tong University"}]},{"given":"Xiaodi","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computing and Mathematics, Charles Sturt University, Albury, NSW 2640, Australia"}]},{"given":"Fengzhu","family":"Sun","sequence":"additional","affiliation":[{"name":"Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China"},{"name":"Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China"},{"name":"Quantitative and Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA"}]},{"given":"Hiroshi","family":"Mamitsuka","sequence":"additional","affiliation":[{"name":"Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji 611-0011, Japan"},{"name":"Department of Computer Science, Aalto University, Espoo and Helsinki, Finland"}]},{"given":"Shanfeng","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai 200433, China"},{"name":"Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China"},{"name":"Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China"}]}],"member":"286","published-online":{"date-parts":[[2019,5,20]]},"reference":[{"key":"2019062808224122600_B1","volume-title":"Molecular Biology (WCB Cell & Molecular Biology)","author":"Weaver","year":"2011","edition":"5"},{"key":"2019062808224122600_B2","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1038\/75556","article-title":"Gene Ontology: tool for the unification of biology","volume":"25","author":"Ashburner","year":"2000","journal-title":"Nat. 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