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Volumn , Issue , 2015, Pages 2406-2410

Graph inference enhancement with clustering: Application to Gene Regulatory Network reconstruction

Author keywords

combinatorial Dirichlet problem; genomic data analysis; graph construction; random walker

Indexed keywords

BIOLOGY; COMPUTER GRAPHICS; GENE EXPRESSION; GENES; RANDOM PROCESSES;

EID: 84963983894     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EUSIPCO.2015.7362816     Document Type: Conference Paper
Times cited : (1)

References (22)
  • 2
    • 85032751310 scopus 로고    scopus 로고
    • The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains
    • May
    • D. I. Shuman, S. K. Narang, P. Frossard, A. Ortega, and P. Vandergheynst, "The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains, " IEEE Signal Process. Mag., vol. 30, no. 3, pp. 83-98, May 2013.
    • (2013) IEEE Signal Process. Mag. , vol.30 , Issue.3 , pp. 83-98
    • Shuman, D.I.1    Narang, S.K.2    Frossard, P.3    Ortega, A.4    Vandergheynst, P.5
  • 4
    • 78650101617 scopus 로고    scopus 로고
    • Covariance estimation in decomposable Gaussian graphical models
    • Mar.
    • A. Wiesel, Y. C. Eldar, and A. O. Hero III, "Covariance estimation in decomposable Gaussian graphical models, " IEEE Trans. Signal Process., vol. 58, no. 3, pp. 1482-1492, Mar. 2010.
    • (2010) IEEE Trans. Signal Process. , vol.58 , Issue.3 , pp. 1482-1492
    • Wiesel, A.1    Eldar, Y.C.2    Hero, A.O.3
  • 5
    • 84963959413 scopus 로고    scopus 로고
    • Learning graphs from signal observations under smoothness prior
    • X. Dong, D. Thanou, P. Frossard, and P. Vandergheynst, "Learning graphs from signal observations under smoothness prior, " PREPRINT, 2014.
    • (2014) PREPRINT
    • Dong, X.1    Thanou, D.2    Frossard, P.3    Vandergheynst, P.4
  • 6
    • 84255196314 scopus 로고    scopus 로고
    • Communities, modules and largescale structure in networks
    • M. E. J. Newman, "Communities, modules and largescale structure in networks, " Nat. Phys., vol. 8, no. 1, pp. 25-31, 2012.
    • (2012) Nat. Phys. , vol.8 , Issue.1 , pp. 25-31
    • Newman, M.E.J.1
  • 7
    • 33846207510 scopus 로고    scopus 로고
    • Random walks for image segmentation
    • Nov.
    • L. Grady, "Random walks for image segmentation, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 11, pp. 1768-1783, Nov. 2006.
    • (2006) IEEE Trans. Pattern Anal. Mach. Intell. , vol.28 , Issue.11 , pp. 1768-1783
    • Grady, L.1
  • 8
    • 33745012299 scopus 로고    scopus 로고
    • Modularity and community structure in networks
    • Jun.
    • M. E. Newman, "Modularity and community structure in networks, " Proc. Nat. Acad. Sci. U. S. A., vol. 103, no. 23, pp. 8577-8582, Jun. 2006.
    • (2006) Proc. Nat. Acad. Sci. U. S. A. , vol.103 , Issue.23 , pp. 8577-8582
    • Newman, M.E.1
  • 9
    • 84911881839 scopus 로고    scopus 로고
    • Bi-CoPaM ensemble clustering application to five Escherichia coli bacterial datasets
    • Lisbon, Portugal, Sep. 1-5
    • B. Abu-Jamous, F. Rui, D. J. Roberts, and A. K. Nandi, "Bi-CoPaM ensemble clustering application to five Escherichia coli bacterial datasets, " in Proc. Eur. Sig. Im-age Proc. Conf., Lisbon, Portugal, Sep. 1-5, 2014, pp. 2485-2489.
    • (2014) Proc. Eur. Sig. Im-age Proc. Conf. , pp. 2485-2489
    • Abu-Jamous, B.1    Rui, F.2    Roberts, D.J.3    Nandi, A.K.4
  • 10
    • 0036191190 scopus 로고    scopus 로고
    • Inference of a genetic network by a combined approach of cluster analysis and graphical Gaussian modeling
    • Feb.
    • H. Toh and K. Horimoto, "Inference of a genetic network by a combined approach of cluster analysis and graphical Gaussian modeling, " Bioinformatics, vol. 18, no. 2, pp. 287-297, Feb. 2002.
    • (2002) Bioinformatics , vol.18 , Issue.2 , pp. 287-297
    • Toh, H.1    Horimoto, K.2
  • 11
    • 0842288337 scopus 로고    scopus 로고
    • Inferring cellular networks using probabilistic graphical models
    • Feb.
    • N. Friedman, "Inferring cellular networks using probabilistic graphical models, " Science, vol. 303, no. 5659, pp. 799-805, Feb. 2004.
    • (2004) Science , vol.303 , Issue.5659 , pp. 799-805
    • Friedman, N.1
  • 12
    • 59549086094 scopus 로고    scopus 로고
    • SIMoNe: Statistical inference for modular networks
    • J. Chiquet, A. Smith, G. Grasseau, C. Matias, and C. Ambroise, "SIMoNe: Statistical Inference for MOdular NEtworks, " Bioinformatics, vol. 25, no. 3, pp. 417-418, 2009.
    • (2009) Bioinformatics , vol.25 , Issue.3 , pp. 417-418
    • Chiquet, J.1    Smith, A.2    Grasseau, G.3    Matias, C.4    Ambroise, C.5
  • 15
    • 84905028671 scopus 로고    scopus 로고
    • A comprehensive comparison of association estimators for gene network inference algorithms
    • Aug.
    • Z. Kurt, N. Aydin, and G. Altay, "A comprehensive comparison of association estimators for gene network inference algorithms, " Bioinformatics, vol. 30, no. 15, pp. 2142-2149, Aug. 2014.
    • (2014) Bioinformatics , vol.30 , Issue.15 , pp. 2142-2149
    • Kurt, Z.1    Aydin, N.2    Altay, G.3
  • 16
  • 17
    • 33846400424 scopus 로고    scopus 로고
    • Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles
    • J. J. Faith, B. Hayete, J. T. Thaden, I. Mogno, J. Wierzbowski, G. Cottarel, S. Kasif, J. J. Collins, and T. S. Gardner, "Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles, " PLoS Biol., vol. 5, no. 1, pp. 54-66, 2007.
    • (2007) PLoS Biol. , vol.5 , Issue.1 , pp. 54-66
    • Faith, J.J.1    Hayete, B.2    Thaden, J.T.3    Mogno, I.4    Wierzbowski, J.5    Cottarel, G.6    Kasif, S.7    Collins, J.J.8    Gardner, T.S.9
  • 18
    • 77958570788 scopus 로고    scopus 로고
    • Inferring regulatory networks from expression data using tree-based methods
    • Sep.
    • V. A. Huynh-Thu, A. Irrthum, L. Wehenkel, and P. Geurts, "Inferring regulatory networks from expression data using tree-based methods, " PLoS One, vol. 5, no. 9, pp. 1-10, Sep. 2010.
    • (2010) PLoS One , vol.5 , Issue.9 , pp. 1-10
    • Huynh-Thu, V.A.1    Irrthum, A.2    Wehenkel, L.3    Geurts, P.4
  • 19
    • 0037941585 scopus 로고    scopus 로고
    • Module networks: Discovering regulatory modules and their condition specific regulators from gene expression data
    • E. Segal, M. Shapira, A. Regev, D. Pe'er, D. Botstein, D. Koller, and N. Friedman, "Module networks: Discovering regulatory modules and their condition specific regulators from gene expression data, " Nat. Genet., vol. 34, no. 166-176, pp. 2003, 2003.
    • (2003) Nat. Genet. , vol.34 , Issue.166-176 , pp. 2003
    • Segal, E.1    Shapira, M.2    Regev, A.3    Pe'Er, D.4    Botstein, D.5    Koller, D.6    Friedman, N.7
  • 20
    • 84946098505 scopus 로고    scopus 로고
    • Fast convex optimization for connectivity enforcement in gene regulatory network inference
    • Melbourne, Australia, Apr. 19-24
    • A. Pirayre, C. Couprie, L. Duval, and J.-C. Pesquet, "Fast convex optimization for connectivity enforcement in gene regulatory network inference, " in Proc. Int. Conf. Acoust. Speech Signal Process., Melbourne, Australia, Apr. 19-24, 2015.
    • (2015) Proc. Int. Conf. Acoust. Speech Signal Process.
    • Pirayre, A.1    Couprie, C.2    Duval, L.3    Pesquet, J.-C.4
  • 21
    • 70249141267 scopus 로고    scopus 로고
    • Global optimization for first order Markov Random Fields with submodular priors
    • Combinatorial Approach to Image Analysis
    • J. Darbon, "Global optimization for first order Markov Random Fields with submodular priors, " Discrete Appl. Math., vol. 157, no. 16, pp. 3412-3423, 2009, Combinatorial Approach to Image Analysis.
    • (2009) Discrete Appl. Math. , vol.157 , Issue.16 , pp. 3412-3423
    • Darbon, J.1


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