메뉴 건너뛰기




Volumn 9, Issue , 2015, Pages

Integrating multiple networks for protein function prediction

Author keywords

[No Author keywords available]

Indexed keywords

FUNGAL PROTEIN; INSECT PROTEIN; PROTEIN;

EID: 84928711013     PISSN: None     EISSN: 17520509     Source Type: Journal    
DOI: 10.1186/1752-0509-9-S1-S3     Document Type: Article
Times cited : (31)

References (40)
  • 2
    • 84874663959 scopus 로고    scopus 로고
    • A large-scale evaluation of computational protein function prediction
    • Radivojac P, Clark WT, Oron TR, et al: A large-scale evaluation of computational protein function prediction. Nature Methods 2013, 10(3):221-227.
    • (2013) Nature Methods , vol.10 , Issue.3 , pp. 221-227
    • Radivojac, P.1    Clark, W.T.2    Oron, T.R.3
  • 3
    • 84926348418 scopus 로고    scopus 로고
    • Hierarchical ensemble methods for protein function prediction
    • Valentini G: Hierarchical ensemble methods for protein function prediction. ISRN Bioinformatics 2014, 2014.
    • (2014) ISRN Bioinformatics 2014
    • Valentini, G.1
  • 4
    • 0142059836 scopus 로고    scopus 로고
    • Protein complexes and functional modules in molecular networks
    • Spirin V, Mirny LA: Protein complexes and functional modules in molecular networks. Proceedings of the National Academy of Sciences 2003, 100(21):12123-12128.
    • (2003) Proceedings of the National Academy of Sciences , vol.100 , Issue.21 , pp. 12123-12128
    • Spirin, V.1    Mirny, L.A.2
  • 5
    • 8844263749 scopus 로고    scopus 로고
    • A statistical framework for genomic data fusion
    • Lanckriet GR, De Bie T, Cristianini N, et al: A statistical framework for genomic data fusion. Bioinformatics 2004, 20(16):2626-2635.
    • (2004) Bioinformatics , vol.20 , Issue.16 , pp. 2626-2635
    • Lanckriet, G.R.1    De Bie, T.2    Cristianini, N.3
  • 7
    • 84879477284 scopus 로고    scopus 로고
    • Ms-knn: protein function prediction by integrating multiple data sources
    • Lan L, Djuric N, Guo Y, Vucetic S: Ms-knn: protein function prediction by integrating multiple data sources. BMC Bioinformatics 2013, 14(S3):8.
    • (2013) BMC Bioinformatics , vol.14 , pp. 8
    • Lan, L.1    Djuric, N.2    Guo, Y.3    Vucetic, S.4
  • 8
    • 84878083062 scopus 로고    scopus 로고
    • Protein function prediction by massive integration of evolutionary analyses and multiple data sources
    • Cozzetto D, Buchan DW, Bryson K, Jones DT: Protein function prediction by massive integration of evolutionary analyses and multiple data sources. BMC Bioinformatics 2013, 14(S3):1.
    • (2013) BMC Bioinformatics , vol.14 , pp. 1
    • Cozzetto, D.1    Buchan, D.W.2    Bryson, K.3    Jones, D.T.4
  • 9
    • 84879298648 scopus 로고    scopus 로고
    • Combining heterogeneous data sources for accurate functional annotation of proteins
    • Sokolov A, Funk C, Graim K, et al: Combining heterogeneous data sources for accurate functional annotation of proteins. BMC Bioinformatics 2013, 14(S3):10.
    • (2013) BMC Bioinformatics , vol.14 , pp. 10
    • Sokolov, A.1    Funk, C.2    Graim, K.3
  • 10
    • 84902463639 scopus 로고    scopus 로고
    • New directions for diffusion-based network prediction of protein function: incorporating pathways with confidence
    • Cao M, Pietras CM, Feng X, et al: New directions for diffusion-based network prediction of protein function: incorporating pathways with confidence. Bioinformatics 2014, 30(12):219-227.
    • (2014) Bioinformatics , vol.30 , Issue.12 , pp. 219-227
    • Cao, M.1    Pietras, C.M.2    Feng, X.3
  • 11
    • 84865223440 scopus 로고    scopus 로고
    • Synergy of multi-label hierarchical ensembles, data fusion, and cost-sensitive methods for gene functional inference
    • Cesa-Bianchi N, Re M, Valentini G: Synergy of multi-label hierarchical ensembles, data fusion, and cost-sensitive methods for gene functional inference. Machine Learning 2012, 88(1-2):209-241.
    • (2012) Machine Learning , vol.88 , Issue.1-2 , pp. 209-241
    • Cesa-Bianchi, N.1    Re, M.2    Valentini, G.3
  • 14
    • 27544435126 scopus 로고    scopus 로고
    • Fast protein classification with multiple networks
    • Tsuda K, Shin H, Schölkopf B: Fast protein classification with multiple networks. Bioinformatics 2005, 21(S2):59-65.
    • (2005) Bioinformatics , vol.21 , pp. 59-65
    • Tsuda, K.1    Shin, H.2    Schölkopf, B.3
  • 15
    • 47549107689 scopus 로고    scopus 로고
    • Genemania: a real-time multiple association network integration algorithm for predicting gene function
    • Mostafavi S, Ray D, Warde-Farley, et al: Genemania: a real-time multiple association network integration algorithm for predicting gene function. Genome Biology 2008, 9(S1):4.
    • (2008) Genome Biology , vol.9 , pp. 4
    • Mostafavi, S.1    Ray, D.2    Warde-Farley3
  • 16
    • 77954309042 scopus 로고    scopus 로고
    • Fast integration of heterogeneous data sources for predicting gene function with limited annotation
    • Mostafavi S, Morris Q: Fast integration of heterogeneous data sources for predicting gene function with limited annotation. Bioinformatics 2010, 26(14):1759-1765.
    • (2010) Bioinformatics , vol.26 , Issue.14 , pp. 1759-1765
    • Mostafavi, S.1    Morris, Q.2
  • 17
    • 1542714925 scopus 로고    scopus 로고
    • Mismatch string kernels for discriminative protein classification
    • Leslie CS, Eskin E, Cohen A, et al: Mismatch string kernels for discriminative protein classification. Bioinformatics 2004, 20(4):467-476.
    • (2004) Bioinformatics , vol.20 , Issue.4 , pp. 467-476
    • Leslie, C.S.1    Eskin, E.2    Cohen, A.3
  • 19
    • 67650898284 scopus 로고    scopus 로고
    • Incorporating functional inter-relationships into protein function prediction algorithms
    • Pandey G, Myers CL, Kumar V: Incorporating functional inter-relationships into protein function prediction algorithms. BMC Bioinformatics 2009, 10(1):142.
    • (2009) BMC Bioinformatics , vol.10 , Issue.1 , pp. 142
    • Pandey, G.1    Myers, C.L.2    Kumar, V.3
  • 21
    • 84861118865 scopus 로고    scopus 로고
    • Improving go semantic similarity measures by exploring the ontology beneath the terms and modelling uncertainty
    • Yang H, Nepusz T, Paccanaro A: Improving go semantic similarity measures by exploring the ontology beneath the terms and modelling uncertainty. Bioinformatics 2012, 28(10):1383-1389.
    • (2012) Bioinformatics , vol.28 , Issue.10 , pp. 1383-1389
    • Yang, H.1    Nepusz, T.2    Paccanaro, A.3
  • 22
    • 84878328074 scopus 로고    scopus 로고
    • Measuring gene functional similarity based on group-wise comparison of go terms
    • Teng Z, Guo M, Liu X, et al: Measuring gene functional similarity based on group-wise comparison of go terms. Bioinformatics 2013, 29(11):1424-1432.
    • (2013) Bioinformatics , vol.29 , Issue.11 , pp. 1424-1432
    • Teng, Z.1    Guo, M.2    Liu, X.3
  • 28
    • 80055017471 scopus 로고    scopus 로고
    • Efficient semi-supervised learning on locally informative multiple graphs
    • Shiga M, Mamitsuka H: Efficient semi-supervised learning on locally informative multiple graphs. Pattern Recognition 2012, 45(3):1035-1049.
    • (2012) Pattern Recognition , vol.45 , Issue.3 , pp. 1035-1049
    • Shiga, M.1    Mamitsuka, H.2
  • 29
    • 85161973596 scopus 로고    scopus 로고
    • Multi-label multiple kernel learning by stochastic approximation: Application to visual object recognition
    • Bucak S, Jin R, Jain AK: Multi-label multiple kernel learning by stochastic approximation: Application to visual object recognition. Advances in Neural Information Processing Systems (NIPS) 2010, 325-333.
    • (2010) Advances in Neural Information Processing Systems (NIPS) , pp. 325-333
    • Bucak, S.1    Jin, R.2    Jain, A.K.3
  • 30
    • 0034069495 scopus 로고    scopus 로고
    • Gene ontology: tool for the unification of biology
    • Ashburner M, Ball CA, Blake JA, et al: Gene ontology: tool for the unification of biology. Nature Genetics 2000, 25(1):25-29.
    • (2000) Nature Genetics , vol.25 , Issue.1 , pp. 25-29
    • Ashburner, M.1    Ball, C.A.2    Blake, J.A.3
  • 31
    • 0033669189 scopus 로고    scopus 로고
    • A network of protein-protein interactions in yeast
    • Schwikowski B, Uetz P, Fields S: A network of protein-protein interactions in yeast. Nature Biotechnology 2000, 18(12):1257-1261.
    • (2000) Nature Biotechnology , vol.18 , Issue.12 , pp. 1257-1261
    • Schwikowski, B.1    Uetz, P.2    Fields, S.3
  • 36
    • 84891357101 scopus 로고    scopus 로고
    • Inferring the soybean (glycine max) microrna functional network based on target gene network
    • Xu Y, Guo M, Liu X, et al: Inferring the soybean (glycine max) microrna functional network based on target gene network. Bioinformatics 2014, 30(1):94-103.
    • (2014) Bioinformatics , vol.30 , Issue.1 , pp. 94-103
    • Xu, Y.1    Guo, M.2    Liu, X.3
  • 39
    • 1542271409 scopus 로고    scopus 로고
    • Predicting protein function from protein/protein interaction data: a probabilistic approach
    • Letovsky S, Kasif S: Predicting protein function from protein/protein interaction data: a probabilistic approach. Bioinformatics 2003, 19(S1):197-204.
    • (2003) Bioinformatics , vol.19 , pp. 197-204
    • Letovsky, S.1    Kasif, S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.