메뉴 건너뛰기




Volumn 19, Issue 6, 2017, Pages 1370-1381

Network approaches to systems biology analysis of complex disease: Integrative methods for multi-omics data

Author keywords

Computational methods; Integrative omics; Network approaches; Systems biology

Indexed keywords

TRANSCRIPTOME;

EID: 85057257442     PISSN: 14675463     EISSN: 14774054     Source Type: Journal    
DOI: 10.1093/bib/bbx066     Document Type: Article
Times cited : (255)

References (110)
  • 1
    • 77954034488 scopus 로고    scopus 로고
    • Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: A study of the ADNI cohort
    • Shen L, Kim S, Risacher SL, et al. Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: a study of the ADNI cohort. Neuroimage 2010;53(3):1051-63.
    • (2010) Neuroimage , vol.53 , Issue.3 , pp. 1051-1063
    • Shen, L.1    Kim, S.2    Risacher, S.L.3
  • 2
    • 84888317489 scopus 로고    scopus 로고
    • Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease
    • Lambert JC, Ibrahim-Verbaas CA, Harold D, et al. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease. Nat Genet 2013;45(12):1452-8.
    • (2013) Nat Genet , vol.45 , Issue.12 , pp. 1452-1458
    • Lambert, J.C.1    Ibrahim-Verbaas, C.A.2    Harold, D.3
  • 3
    • 70549088602 scopus 로고    scopus 로고
    • Genome-wide association study reveals genetic risk underlying Parkinson's disease
    • Simon-Sanchez J, Schulte C, Bras JM, et al. Genome-wide association study reveals genetic risk underlying Parkinson's disease. Nat Genet 2009;41(12):1308-12.
    • (2009) Nat Genet , vol.41 , Issue.12 , pp. 1308-1312
    • Simon-Sanchez, J.1    Schulte, C.2    Bras, J.M.3
  • 4
    • 84876907931 scopus 로고    scopus 로고
    • Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer's disease
    • Zhang B, Gaiteri C, Bodea LG, et al. Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer's disease. Cell 2013;153(3):707-20.
    • (2013) Cell , vol.153 , Issue.3 , pp. 707-720
    • Zhang, B.1    Gaiteri, C.2    Bodea, L.G.3
  • 5
    • 84994544504 scopus 로고    scopus 로고
    • TYROBP genetic variants in early-onset Alzheimer's disease
    • Pottier C, Ravenscroft TA, Brown PH, et al. TYROBP genetic variants in early-onset Alzheimer's disease. Neurobiol Aging 2016;48:222.e9-e15.
    • (2016) Neurobiol Aging , vol.48 , pp. 222e9-222e15
    • Pottier, C.1    Ravenscroft, T.A.2    Brown, P.H.3
  • 6
    • 84890546613 scopus 로고    scopus 로고
    • Systems genetics approaches to understand complex traits
    • Civelek M, Lusis AJ. Systems genetics approaches to understand complex traits. Nat Rev Genet 2014;15(1):34-48.
    • (2014) Nat Rev Genet , vol.15 , Issue.1 , pp. 34-48
    • Civelek, M.1    Lusis, A.J.2
  • 7
    • 70249134919 scopus 로고    scopus 로고
    • Molecular networks as sensors and drivers of common human diseases
    • Schadt EE. Molecular networks as sensors and drivers of common human diseases. Nature 2009;461(7261):218-23.
    • (2009) Nature , vol.461 , Issue.7261 , pp. 218-223
    • Schadt, E.E.1
  • 8
    • 77955474351 scopus 로고    scopus 로고
    • The Alzheimer's disease neuroimaging initiative: Progress report and future plans
    • Weiner MW, Aisen PS, Jack CR, Jr et al. The Alzheimer's disease neuroimaging initiative: progress report and future plans. Alzheimers Dement 2010;6(3):202.e7-11.e7.
    • (2010) Alzheimers Dement , vol.6 , Issue.3 , pp. 202e7-211e7
    • Weiner, M.W.1    Aisen, P.S.2    Jack, C.R.3
  • 9
    • 84937580795 scopus 로고    scopus 로고
    • Genetic studies of quantitative MCI and AD phenotypes in ADNI: Progress, opportunities, and plans
    • Saykin AJ, Shen L, Yao X, et al. Genetic studies of quantitative MCI and AD phenotypes in ADNI: progress, opportunities, and plans. Alzheimers Dement 2015;11(7):792-814.
    • (2015) Alzheimers Dement , vol.11 , Issue.7 , pp. 792-814
    • Saykin, A.J.1    Shen, L.2    Yao, X.3
  • 10
    • 84905871217 scopus 로고    scopus 로고
    • Drug Intervention Response Predictions with PARADIGM (DIRPP) identifies drug resistant cancer cell lines and pathway mechanisms of resistance
    • Brubaker D, Difeo Chen AY, et al. Drug Intervention Response Predictions with PARADIGM (DIRPP) identifies drug resistant cancer cell lines and pathway mechanisms of resistance. Pac Symp Biocomput 2014:125-35.
    • (2014) Pac Symp Biocomput , pp. 125-135
    • Brubaker, D.1    Difeo Chen, A.Y.2
  • 11
    • 84897022815 scopus 로고    scopus 로고
    • Comprehensive molecular characterization of urothelial bladder carcinoma
    • The Cancer Genome Atlas Research Network
    • The Cancer Genome Atlas Research Network. Comprehensive molecular characterization of urothelial bladder carcinoma. Nature 2014;507(7492):315-22.
    • (2014) Nature , vol.507 , Issue.7492 , pp. 315-322
  • 12
    • 79959838081 scopus 로고    scopus 로고
    • Integrated genomic analyses of ovarian carcinoma
    • The Cancer Genome Atlas Research Network
    • The Cancer Genome Atlas Research Network. Integrated genomic analyses of ovarian carcinoma. Nature 2011;474(7353):609-15.
    • (2011) Nature , vol.474 , Issue.7353 , pp. 609-615
  • 13
    • 84943613527 scopus 로고    scopus 로고
    • Comprehensive molecular portraits of invasive lobular breast cancer
    • Ciriello G, Gatza ML, Beck AH, et al. Comprehensive molecular portraits of invasive lobular breast cancer. Cell 2015;163(2):506-19.
    • (2015) Cell , vol.163 , Issue.2 , pp. 506-519
    • Ciriello, G.1    Gatza, M.L.2    Beck, A.H.3
  • 14
    • 0034973569 scopus 로고    scopus 로고
    • Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer
    • Ritchie MD, Hahn LW, Roodi N, et al. Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer. Am J Hum Genet 2001;69(1):138-47.
    • (2001) Am J Hum Genet , vol.69 , Issue.1 , pp. 138-147
    • Ritchie, M.D.1    Hahn, L.W.2    Roodi, N.3
  • 15
    • 69449103972 scopus 로고    scopus 로고
    • Epistasis and its implications for personal genetics
    • Moore JH, Williams SM. Epistasis and its implications for personal genetics. Am J Hum Genet 2009;85(3):309-20.
    • (2009) Am J Hum Genet , vol.85 , Issue.3 , pp. 309-320
    • Moore, J.H.1    Williams, S.M.2
  • 16
    • 84927516032 scopus 로고    scopus 로고
    • Hippocampal transcriptome-guided genetic analysis of correlated episodic memory phenotypes in Alzheimer's disease
    • Yan J, Kim S, Nho SK, et al. Hippocampal transcriptome-guided genetic analysis of correlated episodic memory phenotypes in Alzheimer's disease. Front Genet 2015;6:117.
    • (2015) Front Genet , vol.6 , pp. 117
    • Yan, J.1    Kim, S.2    Nho, S.K.3
  • 17
    • 84911408654 scopus 로고    scopus 로고
    • A genetic interaction network model of a complex neurological disease
    • Tyler AL, McGarr TC, Beyer BJ, et al. A genetic interaction network model of a complex neurological disease. Genes Brain Behav 2014;13(8):831-40.
    • (2014) Genes Brain Behav , vol.13 , Issue.8 , pp. 831-840
    • Tyler, A.L.1    McGarr, T.C.2    Beyer, B.J.3
  • 18
    • 84874776155 scopus 로고    scopus 로고
    • An evolutionary perspective on epistasis and the missing heritability
    • Hemani G, Knott S, Haley C. An evolutionary perspective on epistasis and the missing heritability. PLoS Genet 2013;9(2):e1003295.
    • (2013) PLoS Genet , vol.9 , Issue.2
    • Hemani, G.1    Knott, S.2    Haley, C.3
  • 19
    • 84978193699 scopus 로고    scopus 로고
    • Genotypic context and epistasis in individuals and populations
    • Sackton TB, Hartl DL. Genotypic context and epistasis in individuals and populations. Cell 2016;166(2):279-87.
    • (2016) Cell , vol.166 , Issue.2 , pp. 279-287
    • Sackton, T.B.1    Hartl, D.L.2
  • 20
    • 84903291815 scopus 로고    scopus 로고
    • Microbial evolution. Global epistasis makes adaptation predictable despite sequence-level stochasticity
    • Kryazhimskiy S, Rice DP, Jerison ER, et al. Microbial evolution. global epistasis makes adaptation predictable despite sequence-level stochasticity. Science 2014;344(6191):1519-22.
    • (2014) Science , vol.344 , Issue.6191 , pp. 1519-1522
    • Kryazhimskiy, S.1    Rice, D.P.2    Jerison, E.R.3
  • 21
    • 34548292504 scopus 로고    scopus 로고
    • Plink: A tool set for whole-genome association and population-based linkage analyses
    • Purcell S, Neale B, Todd-Brown K, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007;81(3):559-75.
    • (2007) Am J Hum Genet , vol.81 , Issue.3 , pp. 559-575
    • Purcell, S.1    Neale, B.2    Todd-Brown, K.3
  • 22
    • 75849134020 scopus 로고    scopus 로고
    • InterSNP: Genome-wide interaction analysis guided by a priori information
    • Herold C, Steffens M, Brockschmidt FF, et al. INTERSNP: genome-wide interaction analysis guided by a priori information. Bioinformatics 2009;25(24):3275-81.
    • (2009) Bioinformatics , vol.25 , Issue.24 , pp. 3275-3281
    • Herold, C.1    Steffens, M.2    Brockschmidt, F.F.3
  • 23
    • 67349166946 scopus 로고    scopus 로고
    • Detecting gene-gene interactions that underlie human diseases
    • Cordell HJ. Detecting gene-gene interactions that underlie human diseases. Nat Rev Genet 2009;10(6):392-404.
    • (2009) Nat Rev Genet , vol.10 , Issue.6 , pp. 392-404
    • Cordell, H.J.1
  • 24
    • 77953893931 scopus 로고    scopus 로고
    • Fastepistasis: A high performance computing solution for quantitative trait epistasis
    • Schupbach T, Xenarios I, Bergmann S, et al. FastEpistasis: a high performance computing solution for quantitative trait epistasis. Bioinformatics 2010;26(11):1468-9.
    • (2010) Bioinformatics , vol.26 , Issue.11 , pp. 1468-1469
    • Schupbach, T.1    Xenarios, I.2    Bergmann, S.3
  • 25
    • 77956395423 scopus 로고    scopus 로고
    • Boost: A fast approach to detecting gene-gene interactions in genome-wide case-control studies
    • Wan X, Yang C, Yang Q, et al. BOOST: a fast approach to detecting gene-gene interactions in genome-wide case-control studies. Am J Hum Genet 2010;87(3):325-40.
    • (2010) Am J Hum Genet , vol.87 , Issue.3 , pp. 325-340
    • Wan, X.1    Yang, C.2    Yang, Q.3
  • 26
    • 60149109479 scopus 로고    scopus 로고
    • Snpharvester: A filtering-based approach for detecting epistatic interactions in genomewide association studies
    • Yang C, He Z, Wan X, et al. SNPHarvester: a filtering-based approach for detecting epistatic interactions in genomewide association studies. Bioinformatics 2009;25(4):504-11.
    • (2009) Bioinformatics , vol.25 , Issue.4 , pp. 504-511
    • Yang, C.1    He, Z.2    Wan, X.3
  • 27
    • 79953753220 scopus 로고    scopus 로고
    • Genome-wide interaction-based association analysis identified multiple new susceptibility Loci for common diseases
    • Liu Y, Xu H, Chen S, et al. Genome-wide interaction-based association analysis identified multiple new susceptibility Loci for common diseases. PLoS Genet 2011;7(3):e1001338.
    • (2011) PLoS Genet , vol.7 , Issue.3
    • Liu, Y.1    Xu, H.2    Chen, S.3
  • 28
    • 79957823590 scopus 로고    scopus 로고
    • Epigpu: Exhaustive pairwise epistasis scans parallelized on consumer level graphics cards
    • Hemani G, Theocharidis A, Wei W, et al. EpiGPU: exhaustive pairwise epistasis scans parallelized on consumer level graphics cards. Bioinformatics 2011;27(11):1462-5.
    • (2011) Bioinformatics , vol.27 , Issue.11 , pp. 1462-1465
    • Hemani, G.1    Theocharidis, A.2    Wei, W.3
  • 29
    • 79952742395 scopus 로고    scopus 로고
    • Finding unique filter sets in PLATO: A precursor to efficient interaction analysis in GWAS data
    • Grady BJ, Torstenson E, Dudek SM, et al. Finding unique filter sets in PLATO: a precursor to efficient interaction analysis in GWAS data. Pac Symp Biocomput 2010:315-26.
    • (2010) Pac Symp Biocomput , pp. 315-326
    • Grady, B.J.1    Torstenson, E.2    Dudek, S.M.3
  • 30
    • 33751074962 scopus 로고    scopus 로고
    • Test for interaction between two unlinked loci
    • Zhao JY, Jin L, Xiong MM. Test for interaction between two unlinked loci. Am J Hum Genet 2006;79(5):831-45.
    • (2006) Am J Hum Genet , vol.79 , Issue.5 , pp. 831-845
    • Zhao, J.Y.1    Jin, L.2    Xiong, M.M.3
  • 31
    • 79952740772 scopus 로고    scopus 로고
    • EPIBLASTER-fast exhaustive two-locus epistasis detection strategy using graphical processing units
    • Kam-Thong T, Czamara D, Tsuda K, et al. EPIBLASTER-fast exhaustive two-locus epistasis detection strategy using graphical processing units. Eur J Hum Genet 2011;19(4):465-71.
    • (2011) Eur J Hum Genet , vol.19 , Issue.4 , pp. 465-471
    • Kam-Thong, T.1    Czamara, D.2    Tsuda, K.3
  • 32
    • 84868312363 scopus 로고    scopus 로고
    • Ultrafast genome-wide scan for SNP-SNP interactions in common complex disease
    • Prabhu S, Pe'er I. Ultrafast genome-wide scan for SNP-SNP interactions in common complex disease. Genome Res 2012;22(11):2230-40.
    • (2012) Genome Res , vol.22 , Issue.11 , pp. 2230-2240
    • Prabhu, S.1    Pe'Er, I.2
  • 33
    • 84902440126 scopus 로고    scopus 로고
    • EPIQ-efficient detection of SNP-SNP epistatic interactions for quantitative traits
    • Arkin Y, Rahmani E, Kleber ME, et al. EPIQ-efficient detection of SNP-SNP epistatic interactions for quantitative traits. Bioinformatics 2014;30(12):i19-i25.
    • (2014) Bioinformatics , vol.30 , Issue.12 , pp. i19-i25
    • Arkin, Y.1    Rahmani, E.2    Kleber, M.E.3
  • 34
    • 33645230600 scopus 로고    scopus 로고
    • Multifactor dimensionality reduction: An analysis strategy for modelling and detecting gene-gene interactions in human genetics and pharmaco-genomics studies
    • Motsinger AA, Ritchie MD. Multifactor dimensionality reduction: an analysis strategy for modelling and detecting gene-gene interactions in human genetics and pharmaco-genomics studies. Hum Genomics 2006;2(5):318-28.
    • (2006) Hum Genomics , vol.2 , Issue.5 , pp. 318-328
    • Motsinger, A.A.1    Ritchie, M.D.2
  • 35
    • 35748972938 scopus 로고    scopus 로고
    • Log-linear model-based multifactor dimensionality reduction method to detect gene gene interactions
    • Lee SY, Chung Y, Elston RC, et al. Log-linear model-based multifactor dimensionality reduction method to detect gene gene interactions. Bioinformatics 2007;23(19):2589-95.
    • (2007) Bioinformatics , vol.23 , Issue.19 , pp. 2589-2595
    • Lee, S.Y.1    Chung, Y.2    Elston, R.C.3
  • 36
    • 69449088874 scopus 로고    scopus 로고
    • Spatially uniform reliefF (SURF) for computationally-efficient filtering of gene-gene interactions
    • Greene CS, Penrod NM, Kiralis J, et al. Spatially uniform reliefF (SURF) for computationally-efficient filtering of gene-gene interactions. BioData Min 2009;2(1):5.
    • (2009) BioData Min , vol.2 , Issue.1 , pp. 5
    • Greene, C.S.1    Penrod, N.M.2    Kiralis, J.3
  • 37
    • 33748675883 scopus 로고    scopus 로고
    • Parallel multifactor dimensionality reduction: A tool for the large-scale analysis of gene-gene interactions
    • Bush WS, Dudek SM, Ritchie MD. Parallel multifactor dimensionality reduction: a tool for the large-scale analysis of gene-gene interactions. Bioinformatics 2006;22(17):2173-4.
    • (2006) Bioinformatics , vol.22 , Issue.17 , pp. 2173-2174
    • Bush, W.S.1    Dudek, S.M.2    Ritchie, M.D.3
  • 38
    • 34548352849 scopus 로고    scopus 로고
    • Bayesian inference of epistatic interactions in case-control studies
    • Zhang Y, Liu JS. Bayesian inference of epistatic interactions in case-control studies. Nat Genet 2007;39(9):1167-73.
    • (2007) Nat Genet , vol.39 , Issue.9 , pp. 1167-1173
    • Zhang, Y.1    Liu, J.S.2
  • 39
    • 33745599582 scopus 로고    scopus 로고
    • A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility
    • Moore JH, Gilbert JC, Tsai CT, et al. A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility. J Theor Biol 2006;241(2):252-61.
    • (2006) J Theor Biol , vol.241 , Issue.2 , pp. 252-261
    • Moore, J.H.1    Gilbert, J.C.2    Tsai, C.T.3
  • 40
    • 35348897831 scopus 로고    scopus 로고
    • Information-theoretic metrics for visualizing gene-environment interactions
    • Chanda P, Zhang A, Brazeau D, et al. Information-theoretic metrics for visualizing gene-environment interactions. Am J Hum Genet 2007;81(5):939-63.
    • (2007) Am J Hum Genet , vol.81 , Issue.5 , pp. 939-963
    • Chanda, P.1    Zhang, A.2    Brazeau, D.3
  • 41
    • 84908162497 scopus 로고    scopus 로고
    • Detecting epistasis in human complex traits
    • Wei WH, Hemani G, Haley CS. Detecting epistasis in human complex traits. Nat Rev Genet 2014;15(11):722-33.
    • (2014) Nat Rev Genet , vol.15 , Issue.11 , pp. 722-733
    • Wei, W.H.1    Hemani, G.2    Haley, C.S.3
  • 42
    • 84971619991 scopus 로고    scopus 로고
    • Review: High-performance computing to detect epistasis in genome scale data sets
    • Upton A, Trelles O, Cornejo-Garcia JA, et al. Review: high-performance computing to detect epistasis in genome scale data sets. Brief Bioinform 2016;17(3):368-79.
    • (2016) Brief Bioinform , vol.17 , Issue.3 , pp. 368-379
    • Upton, A.1    Trelles, O.2    Cornejo-Garcia, J.A.3
  • 43
    • 84887497497 scopus 로고    scopus 로고
    • A review for detecting gene-gene interactions using machine learning methods in genetic epidemiology
    • Koo CL, Liew MJ, Mohamad MS, et al. A review for detecting gene-gene interactions using machine learning methods in genetic epidemiology. Biomed Res Int 2013;2013:432375.
    • (2013) Biomed Res Int , vol.2013 , pp. 432375
    • Koo, C.L.1    Liew, M.J.2    Mohamad, M.S.3
  • 44
    • 84900302836 scopus 로고    scopus 로고
    • Detection and replication of epistasis influencing transcription in humans
    • Hemani G, Shakhbazov K, Westra HJ, et al. Detection and replication of epistasis influencing transcription in humans. Nature 2014;508(7495):249-53.
    • (2014) Nature , vol.508 , Issue.7495 , pp. 249-253
    • Hemani, G.1    Shakhbazov, K.2    Westra, H.J.3
  • 45
    • 84878539189 scopus 로고    scopus 로고
    • Investigation of epistasis between DAOA and 5HTR1A variants on clinical outcomes in patients with Schizophrenia
    • Chiesa A, Lia L, Han C, et al. Investigation of epistasis between DAOA and 5HTR1A variants on clinical outcomes in patients with Schizophrenia. Genet Test Mol Biomarkers 2013;17(6):504-7.
    • (2013) Genet Test Mol Biomarkers , vol.17 , Issue.6 , pp. 504-507
    • Chiesa, A.1    Lia, L.2    Han, C.3
  • 47
    • 60549111634 scopus 로고    scopus 로고
    • WGCNA: An R package for weighted correlation network analysis
    • Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 2008;9:559.
    • (2008) BMC Bioinformatics , vol.9 , pp. 559
    • Langfelder, P.1    Horvath, S.2
  • 48
    • 33846400424 scopus 로고    scopus 로고
    • Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles
    • Faith JJ, Hayete B, Thaden JT, et al. Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles. PLoS Biol 2007;5(1):54-66.
    • (2007) PLoS Biol , vol.5 , Issue.1 , pp. 54-66
    • Faith, J.J.1    Hayete, B.2    Thaden, J.T.3
  • 49
    • 33947305781 scopus 로고    scopus 로고
    • Aracne: An algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context
    • Margolin AA, Nemenman I, Basso K, et al. ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinformatics 2006;7:S7.
    • (2006) BMC Bioinformatics , vol.7 , pp. S7
    • Margolin, A.A.1    Nemenman, I.2    Basso, K.3
  • 50
    • 59949086432 scopus 로고    scopus 로고
    • Minet: A R/Bioconductor package for inferring large transcriptional networks using mutual information
    • Meyer PE, Lafitte F, Bontempi G. minet: A R/Bioconductor package for inferring large transcriptional networks using mutual information. BMC Bioinformatics 2008;9:461.
    • (2008) BMC Bioinformatics , vol.9 , pp. 461
    • Meyer, P.E.1    Lafitte, F.2    Bontempi, G.3
  • 51
    • 84869882656 scopus 로고    scopus 로고
    • Tigress: Trustful Inference of Gene REgulation using Stability Selection
    • Haury AC, Mordelet Vera-Licona FP, et al. TIGRESS: Trustful Inference of Gene REgulation using Stability Selection. BMC Syst Biol 2012;6:145.
    • (2012) BMC Syst Biol , vol.6 , pp. 145
    • Haury, A.C.1    Mordelet Vera-Licona, F.P.2
  • 52
    • 77958570788 scopus 로고    scopus 로고
    • Inferring regulatory networks from expression data using tree-based methods
    • Huynh-Thu VA, Irrthum A, Wehenkel L, et al. Inferring regulatory networks from expression data using tree-based methods. PLoS One 2010;5(9):e12776.
    • (2010) PLoS One , vol.5 , Issue.9
    • Huynh-Thu, V.A.1    Irrthum, A.2    Wehenkel, L.3
  • 53
    • 84931051773 scopus 로고    scopus 로고
    • Integrative random forest for gene regulatory network inference
    • Petralia F, Wang P, Yang JL, et al. Integrative random forest for gene regulatory network inference. Bioinformatics 2015;31(12):197-205.
    • (2015) Bioinformatics , vol.31 , Issue.12 , pp. 197-205
    • Petralia, F.1    Wang, P.2    Yang, J.L.3
  • 54
    • 0033707946 scopus 로고    scopus 로고
    • Using Bayesian networks to analyze expression data
    • Friedman N, Linial M, Nachman I, et al. Using Bayesian networks to analyze expression data. J Comput Biol 2000;7(3-4):601-20.
    • (2000) J Comput Biol , vol.7 , Issue.3-4 , pp. 601-620
    • Friedman, N.1    Linial, M.2    Nachman, I.3
  • 55
    • 58349093534 scopus 로고    scopus 로고
    • BNFinder: Exact and efficient method for learning Bayesian networks
    • Wilczynski B, Dojer N. BNFinder: exact and efficient method for learning Bayesian networks. Bioinformatics 2009;25(2):286-7.
    • (2009) Bioinformatics , vol.25 , Issue.2 , pp. 286-287
    • Wilczynski, B.1    Dojer, N.2
  • 56
    • 84944909900 scopus 로고    scopus 로고
    • Bayesian network inference enables unbiased phenotypic anchoring of transcriptomic responses to cigarette smoke in humans
    • Jennen DG, van Leeuwen DM, Hendrickx DM, et al. Bayesian network inference enables unbiased phenotypic anchoring of transcriptomic responses to cigarette smoke in humans. Chem Res Toxicol 2015;28(10):1936-48.
    • (2015) Chem Res Toxicol , vol.28 , Issue.10 , pp. 1936-1948
    • Jennen, D.G.1    Van Leeuwen, D.M.2    Hendrickx, D.M.3
  • 57
    • 12344259602 scopus 로고    scopus 로고
    • Advances to Bayesian network inference for generating causal networks from observational biological data
    • Yu J, Smith VA, Wang PP, et al. Advances to Bayesian network inference for generating causal networks from observational biological data. Bioinformatics 2004;20(18):3594-603.
    • (2004) Bioinformatics , vol.20 , Issue.18 , pp. 3594-3603
    • Yu, J.1    Smith, V.A.2    Wang, P.P.3
  • 58
    • 33750384429 scopus 로고    scopus 로고
    • Sebini: Software environment for biological network inference
    • Taylor RC, Shah A, Treatman C, et al. SEBINI: Software Environment for BIological Network Inference. Bioinformatics 2006;22(21):2706-8.
    • (2006) Bioinformatics , vol.22 , Issue.21 , pp. 2706-2708
    • Taylor, R.C.1    Shah, A.2    Treatman, C.3
  • 59
    • 77952663448 scopus 로고    scopus 로고
    • Timedelay-Aracne: Reverse engineering of gene networks from time-course data by an information theoretic approach
    • Zoppoli P, Morganella S, Ceccarelli M. TimeDelay-ARACNE: reverse engineering of gene networks from time-course data by an information theoretic approach. BMC Bioinformatics 2010;11:154.
    • (2010) BMC Bioinformatics , vol.11 , pp. 154
    • Zoppoli, P.1    Morganella, S.2    Ceccarelli, M.3
  • 60
    • 84900566215 scopus 로고    scopus 로고
    • Mider: Network inference with mutual information distance and entropy reduction
    • Villaverde AF, Ross J, Moran F, et al. MIDER: network inference with mutual information distance and entropy reduction. PLoS One 2014;9(5):e96732.
    • (2014) PLoS One , vol.9 , Issue.5
    • Villaverde, A.F.1    Ross, J.2    Moran, F.3
  • 61
    • 84870305264 scopus 로고    scopus 로고
    • Wisdom of crowds for robust gene network inference
    • Marbach D, Costello JC, Kuffner R, et al. Wisdom of crowds for robust gene network inference. Nat Methods 2012;9(8):796-804.
    • (2012) Nat Methods , vol.9 , Issue.8 , pp. 796-804
    • Marbach, D.1    Costello, J.C.2    Kuffner, R.3
  • 62
    • 77957110013 scopus 로고    scopus 로고
    • Advantages and limitations of current network inference methods
    • De Smet R, Marchal K. Advantages and limitations of current network inference methods. Nat Rev Microbiol 2010;8(10):717-29.
    • (2010) Nat Rev Microbiol , vol.8 , Issue.10 , pp. 717-729
    • De Smet, R.1    Marchal, K.2
  • 63
    • 84923647642 scopus 로고    scopus 로고
    • NAIL, a software tool-set for inferring, analyzing and visualizing regulatory networks
    • Hurley DG, Cursons J, Wang YK, et al. NAIL, a software tool-set for inferring, analyzing and visualizing regulatory networks. Bioinformatics 2015;31(2):277-8.
    • (2015) Bioinformatics , vol.31 , Issue.2 , pp. 277-278
    • Hurley, D.G.1    Cursons, J.2    Wang, Y.K.3
  • 64
    • 84893359865 scopus 로고    scopus 로고
    • Inferring metabolic networks using the Bayesian adaptive graphical lasso with informative priors
    • Peterson C, Vannucci M, Karakas C, et al. Inferring metabolic networks using the Bayesian adaptive graphical lasso with informative priors. Stat Interface 2013;6(4):547-58.
    • (2013) Stat Interface , vol.6 , Issue.4 , pp. 547-558
    • Peterson, C.1    Vannucci, M.2    Karakas, C.3
  • 65
    • 84924975742 scopus 로고    scopus 로고
    • Assembly and interrogation of Alzheimer's disease genetic networks reveal novel regulators of progression
    • Aubry S, Shin W, Crary JF, et al. Assembly and interrogation of Alzheimer's disease genetic networks reveal novel regulators of progression. PLoS One 2015;10(3):e0120352.
    • (2015) PLoS One , vol.10 , Issue.3
    • Aubry, S.1    Shin, W.2    Crary, J.F.3
  • 66
    • 84922601156 scopus 로고    scopus 로고
    • Bayesian graphical network analyses reveal complex biological interactions specific to Alzheimer's disease
    • Rembach A, Stingo FC, Peterson C, et al. Bayesian graphical network analyses reveal complex biological interactions specific to Alzheimer's disease. J Alzheimers Dis 2015;44(3):917-25.
    • (2015) J Alzheimers Dis , vol.44 , Issue.3 , pp. 917-925
    • Rembach, A.1    Stingo, F.C.2    Peterson, C.3
  • 67
    • 84862499271 scopus 로고    scopus 로고
    • Pathway analysis of genomic data: Concepts, methods, and prospects for future development
    • Ramanan VK, Shen L, Moore JH, et al. Pathway analysis of genomic data: concepts, methods, and prospects for future development. Trends Genet 2012;28(7):323-32.
    • (2012) Trends Genet , vol.28 , Issue.7 , pp. 323-332
    • Ramanan, V.K.1    Shen, L.2    Moore, J.H.3
  • 68
    • 84880617636 scopus 로고    scopus 로고
    • WEB-based GEne SeT AnaLysis Toolkit (WebGestalt): Update 2013
    • Wang J, Duncan D, Shi Z, et al. WEB-based GEne SeT AnaLysis Toolkit (WebGestalt): update 2013. Nucleic Acids Res 2013;41:W77-83.
    • (2013) Nucleic Acids Res , vol.41 , pp. W77-W83
    • Wang, J.1    Duncan, D.2    Shi, Z.3
  • 69
    • 58549112996 scopus 로고    scopus 로고
    • Bioinformatics enrichment tools: Paths toward the comprehensive functional analysis of large gene lists
    • Huang da W, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res 2009;37(1):1-13.
    • (2009) Nucleic Acids Res , vol.37 , Issue.1 , pp. 1-13
    • Huang Da, W.1    Sherman, B.T.2    Lempicki, R.A.3
  • 70
    • 84866449583 scopus 로고    scopus 로고
    • EnrichNet: Network-based gene set enrichment analysis
    • Glaab E, Baudot A, Krasnogor N, et al. EnrichNet: network-based gene set enrichment analysis. Bioinformatics 2012;28(18):i451-7.
    • (2012) Bioinformatics , vol.28 , Issue.18 , pp. i451-i457
    • Glaab, E.1    Baudot, A.2    Krasnogor, N.3
  • 71
    • 0038054341 scopus 로고    scopus 로고
    • PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes
    • Mootha VK, Lindgren CM, Eriksson KF, et al. PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet 2003;34(3):267-73.
    • (2003) Nat Genet , vol.34 , Issue.3 , pp. 267-273
    • Mootha, V.K.1    Lindgren, C.M.2    Eriksson, K.F.3
  • 72
    • 36249029788 scopus 로고    scopus 로고
    • Pathway-based approaches for analysis of genomewide association studies
    • Wang K, Li MY, Bucan M. Pathway-based approaches for analysis of genomewide association studies. Am J Hum Genet 2007;81(6):1278-83.
    • (2007) Am J Hum Genet , vol.81 , Issue.6 , pp. 1278-1283
    • Wang, K.1    Li, M.Y.2    Bucan, M.3
  • 73
    • 71249124573 scopus 로고    scopus 로고
    • Comparing gene set analysis methods on single-nucleotide polymorphism data from genetic analysis workshop 16
    • Tintle NL, Borchers B, Brown M, et al. Comparing gene set analysis methods on single-nucleotide polymorphism data from genetic analysis workshop 16. BMC Proc 2009;3(Suppl 7):S96.
    • (2009) BMC Proc , vol.3 , pp. S96
    • Tintle, N.L.1    Borchers, B.2    Brown, M.3
  • 74
    • 84969988591 scopus 로고    scopus 로고
    • Systematic functional annotation and visualization of biological networks
    • Baryshnikova A. Systematic functional annotation and visualization of biological networks. Cell Syst 2016;2(6):412-21.
    • (2016) Cell Syst , vol.2 , Issue.6 , pp. 412-421
    • Baryshnikova, A.1
  • 75
    • 58049215467 scopus 로고    scopus 로고
    • A novel signaling pathway impact analysis
    • Tarca AL, Draghici S, Khatri P, et al. A novel signaling pathway impact analysis. Bioinformatics 2009;25(1):75-82.
    • (2009) Bioinformatics , vol.25 , Issue.1 , pp. 75-82
    • Tarca, A.L.1    Draghici, S.2    Khatri, P.3
  • 76
    • 84907033478 scopus 로고    scopus 로고
    • Phenonet: Identification of key networks associated with disease phenotype
    • Ben-Hamo R, Gidoni M, Efroni S. PhenoNet: identification of key networks associated with disease phenotype. Bioinformatics 2014;30(17):2399-405.
    • (2014) Bioinformatics , vol.30 , Issue.17 , pp. 2399-2405
    • Ben-Hamo, R.1    Gidoni, M.2    Efroni, S.3
  • 77
    • 78651324347 scopus 로고    scopus 로고
    • The STRING database in 2011: Functional interaction networks of proteins, globally integrated and scored
    • Szklarczyk D, Franceschini A, Kuhn M, et al. The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored. Nucleic Acids Res 2011;39:D561-8.
    • (2011) Nucleic Acids Res , vol.39 , pp. D561-D568
    • Szklarczyk, D.1    Franceschini, A.2    Kuhn, M.3
  • 80
    • 84995370935 scopus 로고    scopus 로고
    • Network-based pathway enrichment analysis with incomplete network information
    • Ma J, Shojaie A, Michailidis G. Network-based pathway enrichment analysis with incomplete network information. Bioinformatics 2016;32(20):3165-74.
    • (2016) Bioinformatics , vol.32 , Issue.20 , pp. 3165-3174
    • Ma, J.1    Shojaie, A.2    Michailidis, G.3
  • 81
    • 77955894773 scopus 로고    scopus 로고
    • An interferon-inducible neutrophil-driven blood transcriptional signature in human tuberculosis
    • Berry MP, Graham CM, McNab FW, et al. An interferon-inducible neutrophil-driven blood transcriptional signature in human tuberculosis. Nature 2010;466(7309):973-7.
    • (2010) Nature , vol.466 , Issue.7309 , pp. 973-977
    • Berry, M.P.1    Graham, C.M.2    McNab, F.W.3
  • 82
    • 77956369535 scopus 로고    scopus 로고
    • Genetic variation influences glutamate concentrations in brains of patients with multiple sclerosis
    • Baranzini SE, Srinivasan R, Khankhanian P, et al. Genetic variation influences glutamate concentrations in brains of patients with multiple sclerosis. Brain 2010;133(9):2603-11.
    • (2010) Brain , vol.133 , Issue.9 , pp. 2603-2611
    • Baranzini, S.E.1    Srinivasan, R.2    Khankhanian, P.3
  • 83
    • 84926157747 scopus 로고    scopus 로고
    • Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes
    • Leiserson MD, Vandin F, Wu HT, et al. Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes. Nat Genet 2015;47(2):106-14.
    • (2015) Nat Genet , vol.47 , Issue.2 , pp. 106-114
    • Leiserson, M.D.1    Vandin, F.2    Wu, H.T.3
  • 84
    • 78650562728 scopus 로고    scopus 로고
    • DMGWAs: Dense module searching for genome-wide association studies in protein-protein interaction networks
    • Jia P, Zheng S, Long J, et al. dmGWAS: dense module searching for genome-wide association studies in protein-protein interaction networks. Bioinformatics 2011;27(1):95-102.
    • (2011) Bioinformatics , vol.27 , Issue.1 , pp. 95-102
    • Jia, P.1    Zheng, S.2    Long, J.3
  • 85
    • 80052493684 scopus 로고    scopus 로고
    • A network-based approach to prioritize results from genome-wide association studies
    • Akula N, Baranova A, Seto D, et al. A network-based approach to prioritize results from genome-wide association studies. PLoS One 2011;6(9):e24220.
    • (2011) PLoS One , vol.6 , Issue.9
    • Akula, N.1    Baranova, A.2    Seto, D.3
  • 86
    • 33747035889 scopus 로고    scopus 로고
    • Predicting disease genes using protein-protein interactions
    • Oti M, Snel B, Huynen MA, et al. Predicting disease genes using protein-protein interactions. J Med Genet 2006;43(8):691-8.
    • (2006) J Med Genet , vol.43 , Issue.8 , pp. 691-698
    • Oti, M.1    Snel, B.2    Huynen, M.A.3
  • 87
    • 33646884801 scopus 로고    scopus 로고
    • Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes
    • Franke L, van Bakel H, Fokkens L, et al. Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes. Am J Hum Genet 2006;78(6):1011-25.
    • (2006) Am J Hum Genet , vol.78 , Issue.6 , pp. 1011-1025
    • Franke, L.1    Van Bakel, H.2    Fokkens, L.3
  • 88
    • 41549139527 scopus 로고    scopus 로고
    • Walking the interactome for prioritization of candidate disease genes
    • Kohler S, Bauer S, Horn D, et al. Walking the interactome for prioritization of candidate disease genes. Am J Hum Genet 2008;82(4):949-58.
    • (2008) Am J Hum Genet , vol.82 , Issue.4 , pp. 949-958
    • Kohler, S.1    Bauer, S.2    Horn, D.3
  • 89
    • 84930083700 scopus 로고    scopus 로고
    • Understanding multicellular function and disease with human tissue-specific networks
    • Greene CS, Krishnan A, Wong AK, et al. Understanding multicellular function and disease with human tissue-specific networks. Nat Genet 2015;47(6):569-76.
    • (2015) Nat Genet , vol.47 , Issue.6 , pp. 569-576
    • Greene, C.S.1    Krishnan, A.2    Wong, A.K.3
  • 90
    • 84897521088 scopus 로고    scopus 로고
    • Clustering gene expression regulators: New approach to disease subtyping
    • Pyatnitskiy M, Mazo I, Shkrob M, et al. Clustering gene expression regulators: new approach to disease subtyping. PLoS One 2014;9(1):e84955.
    • (2014) PLoS One , vol.9 , Issue.1
    • Pyatnitskiy, M.1    Mazo, I.2    Shkrob, M.3
  • 91
    • 84876261160 scopus 로고    scopus 로고
    • Pathway-based personalized analysis of cancer
    • Drier Y, Sheffer M, Domany E. Pathway-based personalized analysis of cancer. Proc Natl Acad Sci USA 2013;110(16):6388-93.
    • (2013) Proc Natl Acad Sci USA , vol.110 , Issue.16 , pp. 6388-6393
    • Drier, Y.1    Sheffer, M.2    Domany, E.3
  • 92
    • 79955513489 scopus 로고    scopus 로고
    • The pathologist: An automated tool for pathway-centric analysis
    • Greenblum SI, Efroni S, Schaefer CF, et al. The PathOlogist: an automated tool for pathway-centric analysis. BMC Bioinformatics 2011;12:133.
    • (2011) BMC Bioinformatics , vol.12 , pp. 133
    • Greenblum, S.I.1    Efroni, S.2    Schaefer, C.F.3
  • 93
    • 84971621968 scopus 로고    scopus 로고
    • Using prior knowledge from cellular pathways and molecular networks for diagnostic specimen classification
    • Glaab E. Using prior knowledge from cellular pathways and molecular networks for diagnostic specimen classification. Brief Bioinform 2015;17(3):440-52.
    • (2015) Brief Bioinform , vol.17 , Issue.3 , pp. 440-452
    • Glaab, E.1
  • 94
    • 84907030081 scopus 로고    scopus 로고
    • Transcriptome-guided amyloid imaging genetic analysis via a novel structured sparse learning algorithm
    • Yan J, Du L, Kim S, et al. Transcriptome-guided amyloid imaging genetic analysis via a novel structured sparse learning algorithm. Bioinformatics 2014;30(17):i564-71.
    • (2014) Bioinformatics , vol.30 , Issue.17 , pp. i564-i571
    • Yan, J.1    Du, L.2    Kim, S.3
  • 95
    • 42649140560 scopus 로고    scopus 로고
    • Network-constrained regularization and variable selection for analysis of genomic data
    • Li CY, Li HZ. Network-constrained regularization and variable selection for analysis of genomic data. Bioinformatics 2008;24(9):1175-82.
    • (2008) Bioinformatics , vol.24 , Issue.9 , pp. 1175-1182
    • Li, C.Y.1    Li, H.Z.2
  • 96
    • 77954195272 scopus 로고    scopus 로고
    • Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM
    • Vaske CJ, Benz SC, Sanborn JZ, et al. Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM. Bioinformatics 2010;26(12):i237-45.
    • (2010) Bioinformatics , vol.26 , Issue.12 , pp. i237-i245
    • Vaske, C.J.1    Benz, S.C.2    Sanborn, J.Z.3
  • 97
    • 84924370895 scopus 로고    scopus 로고
    • Integrative multi-omics module network inference with lemon-tree
    • Bonnet E, Calzone L, Michoel T. Integrative multi-omics module network inference with lemon-tree. PLoS Comput Biol 2015;11(2):e1003983.
    • (2015) PLoS Comput Biol , vol.11 , Issue.2
    • Bonnet, E.1    Calzone, L.2    Michoel, T.3
  • 98
    • 84897711239 scopus 로고    scopus 로고
    • Athena: The analysis tool for heritable and environmental network associations
    • Holzinger ER, Dudek SM, Frase AT, et al. ATHENA: the analysis tool for heritable and environmental network associations. Bioinformatics 2014;30(5):698-705.
    • (2014) Bioinformatics , vol.30 , Issue.5 , pp. 698-705
    • Holzinger, E.R.1    Dudek, S.M.2    Frase, A.T.3
  • 99
    • 84859959092 scopus 로고    scopus 로고
    • Stitching together multiple data dimensions reveals interacting metabolomic and transcriptomic networks that modulate cell regulation
    • Zhu J, Sova P, Xu QW, et al. Stitching together multiple data dimensions reveals interacting metabolomic and transcriptomic networks that modulate cell regulation. PLoS Biol 2012;10(4):e1001301.
    • (2012) PLoS Biol , vol.10 , Issue.4
    • Zhu, J.1    Sova, P.2    Xu, Q.W.3
  • 100
    • 84959292644 scopus 로고    scopus 로고
    • Common variants in ABCA7 and MS4A6A are associated with cortical and hippo-campal atrophy
    • Ramirez LM, Goukasian N, Porat S, et al. Common variants in ABCA7 and MS4A6A are associated with cortical and hippo-campal atrophy. Neurobiol Aging 2016;39:82-9.
    • (2016) Neurobiol Aging , vol.39 , pp. 82-89
    • Ramirez, L.M.1    Goukasian, N.2    Porat, S.3
  • 101
    • 84986596477 scopus 로고    scopus 로고
    • Perspective: The precision-oncology illusion
    • Prasad V. Perspective: the precision-oncology illusion. Nature 2016;537(7619):S63.
    • (2016) Nature , vol.537 , Issue.7619 , pp. S63
    • Prasad, V.1
  • 102
    • 84995934705 scopus 로고    scopus 로고
    • Molecular medicine: Precision oncology is not an illusion
    • Abrahams E, Eck SL. Molecular medicine: precision oncology is not an illusion. Nature 2016;539(7629):357.
    • (2016) Nature , vol.539 , Issue.7629 , pp. 357
    • Abrahams, E.1    Eck, S.L.2
  • 103
    • 85016138846 scopus 로고    scopus 로고
    • Integrated genomic and molecular characterization of cervical cancer
    • The Cancer Genome Atlas Research Network
    • The Cancer Genome Atlas Research Network. Integrated genomic and molecular characterization of cervical cancer. Nature 2017;543(7645):378-84.
    • (2017) Nature , vol.543 , Issue.7645 , pp. 378-384
  • 104
    • 84866894408 scopus 로고    scopus 로고
    • Comprehensive genomic characterization of squamous cell lung cancers
    • The Cancer Genome Atlas Research Network
    • The Cancer Genome Atlas Research Network. Comprehensive genomic characterization of squamous cell lung cancers. Nature 2012;489(7417):519-25.
    • (2012) Nature , vol.489 , Issue.7417 , pp. 519-525
  • 105
    • 84930624339 scopus 로고    scopus 로고
    • Integrative omics analysis of rheumatoid arthritis identifies non-obvious therapeutic targets
    • Whitaker JW, Boyle DL, Bartok B, et al. Integrative omics analysis of rheumatoid arthritis identifies non-obvious therapeutic targets. PLoS One 2015;10(4):e0124254.
    • (2015) PLoS One , vol.10 , Issue.4
    • Whitaker, J.W.1    Boyle, D.L.2    Bartok, B.3
  • 106
    • 84946566586 scopus 로고    scopus 로고
    • Integrative analysis of transcriptomic and epigenomic data to reveal regulation patterns for BMD variation
    • Zhang JG, Tan LJ, Xu C, et al. Integrative analysis of transcriptomic and epigenomic data to reveal regulation patterns for BMD variation. PLoS One 2015;10(9):e0138524.
    • (2015) PLoS One , vol.10 , Issue.9
    • Zhang, J.G.1    Tan, L.J.2    Xu, C.3
  • 107
    • 84901686870 scopus 로고    scopus 로고
    • An atlas of genetic influences on human blood metabolites
    • Shin SY, Fauman EB, Petersen AK, et al. An atlas of genetic influences on human blood metabolites. Nat Genet 2014;46(6):543-50.
    • (2014) Nat Genet , vol.46 , Issue.6 , pp. 543-550
    • Shin, S.Y.1    Fauman, E.B.2    Petersen, A.K.3
  • 108
    • 84937790219 scopus 로고    scopus 로고
    • The human blood metabolome-transcriptome interface
    • Bartel J, Krumsiek J, Schramm K, et al. The human blood metabolome-transcriptome interface. PLoS Genet 2015;11(6):e1005274.
    • (2015) PLoS Genet , vol.11 , Issue.6
    • Bartel, J.1    Krumsiek, J.2    Schramm, K.3
  • 109
    • 84938594824 scopus 로고    scopus 로고
    • Predicting censored survival data based on the interactions between meta-dimensional omics data in breast cancer
    • Kim D, Li R, Dudek SM, et al. Predicting censored survival data based on the interactions between meta-dimensional omics data in breast cancer. J Biomed Inform 2015;56:220-8.
    • (2015) J Biomed Inform , vol.56 , pp. 220-228
    • Kim, D.1    Li, R.2    Dudek, S.M.3
  • 110
    • 84925031191 scopus 로고    scopus 로고
    • Methods of integrating data to uncover genotype-phenotype interactions
    • Ritchie MD, Holzinger ER, Li R, et al. Methods of integrating data to uncover genotype-phenotype interactions. Nat Rev Genet 2015;16(2):85-97.
    • (2015) Nat Rev Genet , vol.16 , Issue.2 , pp. 85-97
    • Ritchie, M.D.1    Holzinger, E.R.2    Li, R.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.