메뉴 건너뛰기




Volumn 33, Issue 19, 2017, Pages 3080-3087

JDINAC: Joint density-based non-parametric differential interaction network analysis and classification using high-dimensional sparse omics data

Author keywords

[No Author keywords available]

Indexed keywords

BREAST TUMOR; CARCINOMA; COMPUTER SIMULATION; FEMALE; GENE REGULATORY NETWORK; GENETICS; HUMAN;

EID: 85030683641     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btx360     Document Type: Article
Times cited : (25)

References (48)
  • 1
    • 0034069495 scopus 로고    scopus 로고
    • Gene ontology: Tool for the unification of biology
    • Ashburner, M., et al. (2000). Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet., 25, 25-29
    • (2000) The Gene Ontology Consortium. Nat. Genet , vol.25 , pp. 25-29
    • Ashburner, M.1
  • 2
    • 78649703966 scopus 로고    scopus 로고
    • Rewiring of genetic networks in response to DNA damage
    • Bandyopadhyay, S., et al. (2010). Rewiring of genetic networks in response to DNA damage. Science, 330, 1385-1389
    • (2010) Science , vol.330 , pp. 1385-1389
    • Bandyopadhyay, S.1
  • 3
    • 78650373804 scopus 로고    scopus 로고
    • Network medicine: A network-based approach to human disease
    • Barabasi, A.L., et al. (2011). Network medicine: a network-based approach to human disease. Nat. Rev. Genet., 12, 56-68
    • (2011) Nat. Rev. Genet , vol.12 , pp. 56-68
    • Barabasi, A.L.1
  • 4
    • 0028806271 scopus 로고
    • Expression of hemidesmosomes and component proteins is lost by invasive breast cancer cells
    • Bergstraesser, L.M., et al. (1995). Expression of hemidesmosomes and component proteins is lost by invasive breast cancer cells. Am. J. Pathol., 147, 1823-1839
    • (1995) Am. J. Pathol , vol.147 , pp. 1823-1839
    • Bergstraesser, L.M.1
  • 5
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • Breiman, L. (2001). Random forests. Mach Learn., 45, 5-32
    • (2001) Mach Learn , vol.45 , pp. 5-32
    • Breiman, L.1
  • 6
    • 84949130891 scopus 로고    scopus 로고
    • Rewiring makes the difference
    • Califano, A. (2011). Rewiring makes the difference. Mol. Syst. Biol., 7, 463
    • (2011) Mol. Syst. Biol , vol.7 , pp. 463
    • Califano, A.1
  • 7
    • 5044245707 scopus 로고    scopus 로고
    • Gene co-expression network topology provides a framework for molecular characterization of cellular state
    • Carter, S.L., et al. (2004). Gene co-expression network topology provides a framework for molecular characterization of cellular state. Bioinformatics, 20, 2242-2250
    • (2004) Bioinformatics , vol.20 , pp. 2242-2250
    • Carter, S.L.1
  • 8
    • 77953913791 scopus 로고    scopus 로고
    • From differential expression to differential networking -identification of dysfunctional regulatory networks in diseases
    • de la Fuente, A. (2010). From differential expression to differential networking -identification of dysfunctional regulatory networks in diseases. Trends Genet., 26, 326-333
    • (2010) Trends Genet , vol.26 , pp. 326-333
    • De La Fuente, A.1
  • 9
    • 34548550573 scopus 로고    scopus 로고
    • Systematic construction of gene coexpression networks with applications to human T helper cell differentiation process
    • Elo, L.L., et al. (2007). Systematic construction of gene coexpression networks with applications to human T helper cell differentiation process. Bioinformatics, 23, 2096-2103
    • (2007) Bioinformatics , vol.23 , pp. 2096-2103
    • Elo, L.L.1
  • 10
    • 84902801533 scopus 로고    scopus 로고
    • An integrated workflow for proteome-wide off-target identification and polypharmacology drug design
    • Evangelidis, T., and Xie, L. (2014). An integrated workflow for proteome-wide off-target identification and polypharmacology drug design. Tsinghua Sci. Technol., 19, 275-284
    • (2014) Tsinghua Sci. Technol , vol.19 , pp. 275-284
    • Evangelidis, T.1    Xie, L.2
  • 11
    • 84969895621 scopus 로고    scopus 로고
    • Feature augmentation via nonparametrics and selection (fans) in high-dimensional classification
    • Fan, J., et al. (2016). Feature Augmentation via Nonparametrics and Selection (FANS) in High-Dimensional Classification. J AmStatAssoc., 111, 275-287
    • (2016) J AmStatAssoc , vol.111 , pp. 275-287
    • Fan, J.1
  • 12
    • 41849150779 scopus 로고    scopus 로고
    • FOXOs, cancer and regulation of apoptosis
    • Fu, Z., and Tindall, D.J. (2008). FOXOs, cancer and regulation of apoptosis. Oncogene, 27, 2312-2319
    • (2008) Oncogene , vol.27 , pp. 2312-2319
    • Fu, Z.1    Tindall, D.J.2
  • 13
    • 84875380606 scopus 로고    scopus 로고
    • DiffCorr: An R package to analyze and visualize differential correlations in biological networks
    • Fukushima, A. (2013). DiffCorr: an R package to analyze and visualize differential correlations in biological networks. Gene, 518, 209-214
    • (2013) Gene , vol.518 , pp. 209-214
    • Fukushima, A.1
  • 14
    • 84880220238 scopus 로고    scopus 로고
    • Differential network analysis for the identification of condition-specific pathway activity and regulation
    • Gambardella, G., et al. (2013). Differential network analysis for the identification of condition-specific pathway activity and regulation. Bioinformatics, 29, 1776-1785
    • (2013) Bioinformatics , vol.29 , pp. 1776-1785
    • Gambardella, G.1
  • 15
    • 0034480070 scopus 로고    scopus 로고
    • Prognostic significance of TGF beta 1 and TGF beta 3 in human breast carcinoma
    • Ghellal, A., et al. (2000). Prognostic significance of TGF beta 1 and TGF beta 3 in human breast carcinoma. Anticancer Res., 20, 4413-4418
    • (2000) Anticancer Res , vol.20 , pp. 4413-4418
    • Ghellal, A.1
  • 16
    • 69949119988 scopus 로고    scopus 로고
    • Coordinate regulation of FOXO1 by miR-27a miR-96, and miR-182 in breast cancer cells
    • Guttilla, I.K., and White, B.A. (2009). Coordinate regulation of FOXO1 by miR-27a, miR-96, and miR-182 in breast cancer cells. J. Biol. Chem, 284, 23204-23216
    • (2009) J. Biol. Chem , vol.284 , pp. 23204-23216
    • Guttilla, I.K.1    White, B.A.2
  • 17
    • 84947554993 scopus 로고    scopus 로고
    • DINGO: Differential network analysis in genomics
    • Ha, M.J., et al. (2015). DINGO: differential network analysis in genomics. Bioinformatics, 31, 3413-3420
    • (2015) Bioinformatics , vol.31 , pp. 3413-3420
    • Ha, M.J.1
  • 18
    • 84973621882 scopus 로고    scopus 로고
    • Discriminant analysis on high dimensional Gaussian copula model
    • He, Y., et al. (2016). Discriminant analysis on high dimensional Gaussian copula model. Stat. Probab. Lett., 117, 100-112
    • (2016) Stat. Probab. Lett , vol.117 , pp. 100-112
    • He, Y.1
  • 19
    • 67049159812 scopus 로고    scopus 로고
    • A differential wiring analysis of expression data correctly identifies the gene containing the causal mutation
    • Hudson, N.J., et al. (2009). A differential wiring analysis of expression data correctly identifies the gene containing the causal mutation. PLoS Comput. Biol., 5, e1000382
    • (2009) Plos Comput. Biol , vol.5 , pp. e1000382
    • Hudson, N.J.1
  • 20
    • 84856094560 scopus 로고    scopus 로고
    • Differential network biology
    • Ideker, T., and Krogan, N.J. (2012). Differential network biology. Mol. Syst. Biol., 8, 565
    • (2012) Mol. Syst. Biol , vol.8 , pp. 565
    • Ideker, T.1    Krogan, N.J.2
  • 21
    • 84921910280 scopus 로고    scopus 로고
    • Detection for pathway effect contributing to disease in systems epidemiology with a case-control design
    • Ji, J., et al. (2015). Detection for pathway effect contributing to disease in systems epidemiology with a case-control design. BMJ Open, 5, e006721
    • (2015) BMJ Open , vol.5 , pp. e006721
    • Ji, J.1
  • 22
    • 84957873113 scopus 로고    scopus 로고
    • A powerful score-based statistical test for group difference in weighted biological networks
    • Ji, J., et al. (2016). A powerful score-based statistical test for group difference in weighted biological networks. BMC Bioinformatics, 17, 86
    • (2016) BMC Bioinformatics , vol.17 , pp. 86
    • Ji, J.1
  • 23
    • 0033982936 scopus 로고    scopus 로고
    • KEGG: Kyoto encyclopedia of genes and genomes
    • Kanehisa, M., and Goto, S. (2000). KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res., 28, 27-30
    • (2000) Nucleic Acids Res , vol.28 , pp. 27-30
    • Kanehisa, M.1    Goto, S.2
  • 24
    • 84884537159 scopus 로고    scopus 로고
    • FGF2-induced effects on transcriptome associated with regeneration competence in adult human fibroblasts
    • Kashpur, O., et al. (2013). FGF2-induced effects on transcriptome associated with regeneration competence in adult human fibroblasts. BMC Genomics, 14, 656
    • (2013) BMC Genomics , vol.14 , pp. 656
    • Kashpur, O.1
  • 25
    • 84878714179 scopus 로고    scopus 로고
    • Finding the targets of a drug by integration of gene expression data with a protein interaction network
    • Laenen, G., et al. (2013). Finding the targets of a drug by integration of gene expression data with a protein interaction network. Mol. Biosyst., 9, 1676-1685
    • (2013) Mol. Biosyst , vol.9 , pp. 1676-1685
    • Laenen, G.1
  • 26
    • 84876692798 scopus 로고    scopus 로고
    • Tropomyosin regulates cell migration during skin wound healing
    • Lees, J.G., et al. (2013). Tropomyosin regulates cell migration during skin wound healing. J. Invest. Dermatol., 133, 1330-1339
    • (2013) J. Invest. Dermatol , vol.133 , pp. 1330-1339
    • Lees, J.G.1
  • 27
    • 77957813589 scopus 로고    scopus 로고
    • DCGL: An R package for identifying differentially coexpressed genes and links from gene expression microarray data
    • Liu, B.H., et al. (2010). DCGL: an R package for identifying differentially coexpressed genes and links from gene expression microarray data. Bioinformatics, 26, 2637-2638
    • (2010) Bioinformatics , vol.26 , pp. 2637-2638
    • Liu, B.H.1
  • 28
    • 84884709908 scopus 로고    scopus 로고
    • Extracellular matrix components in breast cancer progression and metastasis
    • Oskarsson, T. (2013). Extracellular matrix components in breast cancer progression and metastasis. Breast, 22(Suppl 2), S66-S72
    • (2013) Breast , vol.22 , Issue.SUPPL2 , pp. S66-S72
    • Oskarsson, T.1
  • 29
    • 33749988857 scopus 로고    scopus 로고
    • Simultaneous identification of differential gene expression and connectivity in inflammation, adipogenesis and cancer
    • Reverter, A., et al. (2006). Simultaneous identification of differential gene expression and connectivity in inflammation, adipogenesis and cancer. Bioinformatics, 22, 2396-2404
    • (2006) Bioinformatics , vol.22 , pp. 2396-2404
    • Reverter, A.1
  • 30
    • 84943550160 scopus 로고    scopus 로고
    • Differential analysis of biological networks
    • Ruan, D., et al. (2015). Differential analysis of biological networks. BMC Bioinformatics, 16, 327
    • (2015) BMC Bioinformatics , vol.16 , pp. 327
    • Ruan, D.1
  • 31
    • 3543121913 scopus 로고    scopus 로고
    • Protease-activated receptors (PAR1 and PAR2) contribute to tumor cell motility and metastasis
    • Shi, X., et al. (2004). Protease-activated receptors (PAR1 and PAR2) contribute to tumor cell motility and metastasis. Mol. Cancer Res., 2, 395-402
    • (2004) Mol. Cancer Res , vol.2 , pp. 395-402
    • Shi, X.1
  • 32
    • 33845663074 scopus 로고    scopus 로고
    • Elucidating progesterone effects in breast cancer: Cross talk with PDGF signaling pathway in smooth muscle cell
    • Soares, R., et al. (2007). Elucidating progesterone effects in breast cancer: cross talk with PDGF signaling pathway in smooth muscle cell. J. Cell. Biochem., 100, 174-183
    • (2007) J. Cell. Biochem , vol.100 , pp. 174-183
    • Soares, R.1
  • 33
    • 33847642829 scopus 로고    scopus 로고
    • Basic fibroblast growth factor stimulates fibronectin expression through phospholipase C gamma, protein kinase C alpha, c-Src, NF-kappaB, and p300 pathway in osteoblasts
    • Tang, C.H., et al. (2007). Basic fibroblast growth factor stimulates fibronectin expression through phospholipase C gamma, protein kinase C alpha, c-Src, NF-kappaB, and p300 pathway in osteoblasts. J. Cell. Physiol., 211, 45-55
    • (2007) J. Cell. Physiol , vol.211 , pp. 45-55
    • Tang, C.H.1
  • 34
    • 77957319820 scopus 로고    scopus 로고
    • DiffCoEx: A simple and sensitive method to find differentially coexpressed gene modules
    • Tesson, B.M., et al. (2010). DiffCoEx: a simple and sensitive method to find differentially coexpressed gene modules. BMC Bioinformatics, 11, 497
    • (2010) BMC Bioinformatics , vol.11 , pp. 497
    • Tesson, B.M.1
  • 35
    • 85194972808 scopus 로고    scopus 로고
    • Regression shrinkage and selection via the lasso
    • Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. J R. Stat. Soc. B, 58, 267-288
    • (1996) J R. Stat. Soc. B , vol.58 , pp. 267-288
    • Tibshirani, R.1
  • 36
    • 80052970809 scopus 로고    scopus 로고
    • FoxO transcription factors regulation by AKT and 14-3-3 proteins
    • Tzivion, G., et al. (2011). FoxO transcription factors; Regulation by AKT and 14-3-3 proteins. Biochim. Biophys. Acta, 1813, 1938-1945
    • (2011) Biochim. Biophys. Acta , vol.1813 , pp. 1938-1945
    • Tzivion, G.1
  • 37
    • 34547649056 scopus 로고    scopus 로고
    • CoXpress: Differential co-expression in gene expression data
    • Watson, M. (2006). CoXpress: differential co-expression in gene expression data. BMC Bioinformatics, 7, 509
    • (2006) BMC Bioinformatics , vol.7 , pp. 509
    • Watson, M.1
  • 38
    • 84964694939 scopus 로고    scopus 로고
    • The antitumorigenic function of EGFR in metastatic breast cancer is regulated by expression of Mig6
    • Wendt, M.K., et al. (2015). The antitumorigenic function of EGFR in metastatic breast cancer is regulated by expression of Mig6. Neoplasia, 17, 124-133
    • (2015) Neoplasia , vol.17 , pp. 124-133
    • Wendt, M.K.1
  • 39
    • 84944714575 scopus 로고    scopus 로고
    • Developing multi-target therapeutics to fine-tune the evolutionary dynamics of the cancer ecosystem
    • Xie, L., and Bourne, P.E. (2015). Developing multi-target therapeutics to fine-tune the evolutionary dynamics of the cancer ecosystem. Front. Pharmacol., 6, 209
    • (2015) Front. Pharmacol , vol.6 , pp. 209
    • Xie, L.1    Bourne, P.E.2
  • 40
    • 84884889100 scopus 로고    scopus 로고
    • Network-based inference framework for identifying cancer genes from gene expression data
    • Yang, B., et al. (2013). Network-based inference framework for identifying cancer genes from gene expression data. Biomed. Res. Int., 2013, 401649
    • (2013) Biomed. Res. Int , vol.2013 , pp. 401649
    • Yang, B.1
  • 41
    • 80055040407 scopus 로고    scopus 로고
    • FZD7 has a critical role in cell proliferation in triple negative breast cancer
    • Yang, L., et al. (2011). FZD7 has a critical role in cell proliferation in triple negative breast cancer. Oncogene, 30, 4437-4446
    • (2011) Oncogene , vol.30 , pp. 4437-4446
    • Yang, L.1
  • 42
    • 84874794126 scopus 로고    scopus 로고
    • An inferential framework for biological network hypothesis tests
    • Yates, P.D., and Mukhopadhyay, N.D. (2013). An inferential framework for biological network hypothesis tests. BMC Bioinformatics, 14, 94
    • (2013) BMC Bioinformatics , vol.14 , pp. 94
    • Yates, P.D.1    Mukhopadhyay, N.D.2
  • 43
    • 17744412020 scopus 로고    scopus 로고
    • The expression and localization of fibroblast growth factor-1 (FGF-1) and FGF receptor-1 (FGFR-1) in human breast cancer
    • Yoshimura, N., et al. (1998). The expression and localization of fibroblast growth factor-1 (FGF-1) and FGF receptor-1 (FGFR-1) in human breast cancer. Clin. Immunol. Immunopathol., 89, 28-34
    • (1998) Clin. Immunol. Immunopathol , vol.89 , pp. 28-34
    • Yoshimura, N.1
  • 44
    • 84860718683 scopus 로고    scopus 로고
    • ClusterProfiler: An R package for comparing biological themes among gene clusters
    • Yu, G., et al. (2012). clusterProfiler: an R package for comparing biological themes among gene clusters. omics, 16, 284-287
    • (2012) Omics , vol.16 , pp. 284-287
    • Yu, G.1
  • 45
    • 60149089400 scopus 로고    scopus 로고
    • Differential dependency network analysis to identify condition-specific topological changes in biological networks
    • Zhang, B., et al. (2009). Differential dependency network analysis to identify condition-specific topological changes in biological networks. Bioinformatics, 25, 526-532
    • (2009) Bioinformatics , vol.25 , pp. 526-532
    • Zhang, B.1
  • 46
    • 84901451119 scopus 로고    scopus 로고
    • Direct estimation of differential networks
    • Zhao, S.D., et al. (2014). Direct estimation of differential networks. Biometrika, 101, 253-268
    • (2014) Biometrika , vol.101 , pp. 253-268
    • Zhao, S.D.1
  • 47
    • 79959792388 scopus 로고    scopus 로고
    • Construction of a recombinant human FGF1 expression vector for mammary gland-specific expression in human breast cancer cells
    • Zhou, Y., et al. (2011). Construction of a recombinant human FGF1 expression vector for mammary gland-specific expression in human breast cancer cells. Mol. Cell. Biochem., 354, 39-46
    • (2011) Mol. Cell. Biochem , vol.354 , pp. 39-46
    • Zhou, Y.1
  • 48
    • 84901761987 scopus 로고    scopus 로고
    • TCGA-assembler: Open-source software for retrieving and processing TCGA data
    • Zhu, Y., et al. (2014). TCGA-assembler: open-source software for retrieving and processing TCGA data. Nat. Methods, 11, 599-600
    • (2014) Nat. Methods , vol.11 , pp. 599-600
    • Zhu, Y.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.