[1] ANFINSEN C B, HABER E, SELA M, et al. The kinetics of formation of native ribonuclease during oxidation of the reduced polypeptide chain[J]. Proceedings of the National Academy of Sciences of the United States of America, 1961, 47(9):1309-1314.

[2] ALTSCHUL S F, GISH W, MILLER W, et al. Basic local alignment search tool[J]. Journal of Molecular Biology, 1990, 215(3):403-410.

[3] ALTSCHUL S F, MADDEN T L, SCHÄFFER A A, et al. Gapped BLAST and PSI-BLAST:a new generation of protein database search programs[J]. Nucleic Acids Research, 1997, 25(17):3389-3402.

[4] GILKS W R, AUDIT B, de ANGELIS D, et al. Percolation of annotation errors through hierarchically structured protein sequence databases[J]. Mathematical Biosciences, 2005, 193(2):223-234.

[5] YE Y, GODZIK A. FATCAT:a Web server for flexible structure comparison and structure similarity searching[J]. Nucleic Acids Research, 2004, 32(Web Server issue):W582-W585.

[6] TÄUBIG H, BUCHNER A, GRIEBSCH J. PAST:fast structure-based searching in the PDB[J]. Nucleic Acids Research, 2006, 34(Web Server issue):W20-W23.

[7] LASKOWSKI R A, WATSON J D, THORNTON J M. From protein structure to biochemical function?[J]. Journal of Structural & Functional Genomics, 2003, 4(2/3):167-177.

[8] WATSON J D, LASKOWSKI R A, THORNTON J M. Predicting protein function from sequence and structural data[J]. Current Opinion in Structural Biology, 2005, 15(3):275-284.

[9] YOU Z H, LEI Y K, ZHU L, et al. Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis[J]. BMC Bioinformatics, 2013, 14(S8):1-11.

[10] WEI L, XING P, ZENG J, et al. Improved prediction of protein-protein interactions using novel negative samples, features, and an ensemble classifier[J]. Artificial Intelligence in Medicine, 2017,83:67-74.

[11] OLIVER S. Proteomics:guilt-by-association goes global[J]. Nature, 2000, 403(6770):601-603.

[12] CHI X, HOU J. An iterative approach of protein function prediction[J]. BMC Bioinformatics, 2011, 12(1):437-445.

[13] XIONG W, XIE L, GUAN J, et al. Active learning for protein function prediction in protein-protein interaction networks[C]//Proceedings of the 8th IAPR International Conference on Pattern Recognition in Bioinformatics. Berlin:Springer, 2014:172-183.

[14] WANG H, HUANG H, DING C. Function-function correlated multi-label protein function prediction over interaction networks[C]//Proceedings of the 16th Annual International Conference on Research in Computational Molecular Biology. Berlin:Springer, 2012:302-313.

[15] TENG Z, GUO M, LIU X, et al. Revealing protein functions based on relationships of interacting proteins and GO terms[J]. Journal of Computational Biology, 2013,20(4):322-343.

[16] YU G, WANG J, LIU J. Protein function prediction by random walks on a hybrid graph[J]. Current Proteomics, 2016, 13(2):130-142.

[17] HARTWELL L H, HOPFIELD J J, LEIBLER S, et al. From molecular to modular cell biology[J]. Nature, 1999, 402(6761 Suppl):47-52.

[18] RIVES A W, GALITSKI T. Modular organization of cellular networks[J]. Proceedings of the National Academy of Sciences of the United States of America, 2003, 100(3):1128-1133.

[19] ARNAU V, MARS S, MARÍN I. Iterative cluster analysis of protein interaction data[J]. Bioinformatics, 2005, 21(3):364-378.

[20] CLAUSET A, NEWMAN M E J, MOORE C. Finding community structure in very large networks[J]. Physical Review E:Statistical, Nonlinear, and Soft Matter Physics, 2004, 70(6):066111.

[21] NEWMAN M E J, GIRVAN M. Finding and evaluating community structure in networks[J]. Physical Review E:Statistical, Nonlinear, and Soft Matter Physics, 2004, 69(2):026113.

[22] ABDI H, WILLIAMS L J. Principal component analysis[J]. Wiley Interdisciplinary Reviews Computational Statistics, 2010, 2(4):433-459.

[23] GILLIS J, PAVLIDIS P. The impact of multifunctional genes on "guilt by association" analysis[J]. PLOS ONE, 2011, 6(2):e17258.

[24] CARPENTER G A, GROSSBERG S. Self-organizing neural networks for supervised and unsupervised learning and prediction[M]//From Statistics to Neural Networks, NATO ASI Series 136. Berlin:Springer, 1994:319-348.

[25] GLOROT X, BORDES A, BENGIO Y. Deep sparse rectifier neural networks[EB/OL].[2017-03-01]. http://proceedings.mlr.press/v15/glorot11a/glorot11a.pdf.

[26] 刘威,刘尚,周璇.BP神经网络子批量学习方法研究[J].智能系统学报,2016,11(2):226-232.(LIU W, LIU S, ZHOU X. Subbatch learning method for BP neural networks[J]. CAAI Transactions on Intelligent Systems, 2016, 11(2):226-232.)

[27] XENARIOS I, RICE D W, SALWINSKI L, et al. DIP:the database of interacting proteins[J]. Nucleic Acids Research, 2000, 28(1):289-291.

[28] ASHBURNER M, BALL C A, BLAKE J A, et al. Gene ontology:tool for the unification of biology[J]. Nature Genetics, 2000, 25(1):25-29.

[29] MULDER N J, APWEILER R, ATTWOOD T K, et al. InterPro, progress and status in 2005[J]. Nucleic Acids Research, 2005, 33(Database issue):D201-D205.

[30] CONSORTIUM U P. The Universal Protein resource (UniProt) in 2010[J]. Nucleic Acids Research, 2010, 38(Database issue):142-148.

[31] DURINCK S, SPELLMAN P T, BIRNEY E, et al. Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt[J]. Nature Protocols, 2009, 4(8):1184-1191.

[32] RADIVOJAC P, CLARK W T, ORON T R, et al. A large-scale evaluation of computational protein function prediction[J]. Nature Methods, 2013, 10(3):221-227.