메뉴 건너뛰기




Volumn 9, Issue 5, 2014, Pages

MIDER: Network inference with mutual information distance and entropy reduction

Author keywords

[No Author keywords available]

Indexed keywords

MITOGEN ACTIVATED PROTEIN KINASE;

EID: 84900566215     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0096732     Document Type: Article
Times cited : (105)

References (62)
  • 1
    • 84891892050 scopus 로고    scopus 로고
    • Reverse engineering and identification in systems biology: Strategies, perspectives and challenges
    • Villaverde AF, Banga JR (2014) Reverse engineering and identification in systems biology: strategies, perspectives and challenges. J R Soc Interface 11: 20130505.
    • (2014) J R Soc Interface , vol.11 , pp. 20130505
    • Villaverde, A.F.1    Banga, J.R.2
  • 2
    • 38449088751 scopus 로고    scopus 로고
    • Inferring cellular networks - A review
    • Markowetz F, Spang R (2007) Inferring cellular networks-a review. BMC Bioinform 8: S5.
    • (2007) BMC Bioinform , vol.8
    • Markowetz, F.1    Spang, R.2
  • 4
    • 61349180117 scopus 로고    scopus 로고
    • Gene regulatory network inference: Data integration in dynamic models - A review
    • Hecker M, Lambeck S, Toepfer S, van Someren E, Guthke R (2009) Gene regulatory network inference: Data integration in dynamic models - a review. Biosystems 96: 86-103.
    • (2009) Biosystems , vol.96 , pp. 86-103
    • Hecker, M.1    Lambeck, S.2    Toepfer, S.3    Van Someren, E.4    Guthke, R.5
  • 5
    • 77957110013 scopus 로고    scopus 로고
    • Advantages and limitations of current network inference methods
    • De Smet R, Marchal K (2010) Advantages and limitations of current network inference methods. Nat Rev Microbiol 8: 717-729.
    • (2010) Nat Rev Microbiol , vol.8 , pp. 717-729
    • De Smet, R.1    Marchal, K.2
  • 6
    • 77954484005 scopus 로고    scopus 로고
    • Revealing differences in gene network inference algorithms on the network level by ensemble methods
    • Altay G, Emmert-Streib F (2010) Revealing differences in gene network inference algorithms on the network level by ensemble methods. Bioinformatics 26: 1738-1744.
    • (2010) Bioinformatics , vol.26 , pp. 1738-1744
    • Altay, G.1    Emmert-Streib, F.2
  • 7
    • 84859371992 scopus 로고    scopus 로고
    • Gene network inference and visualization tools for biologists: Application to new human transcriptome datasets
    • Hurley D, Araki H, Tamada Y, Dunmore B, Sanders D, et al. (2012) Gene network inference and visualization tools for biologists: application to new human transcriptome datasets. Nucleic Acids Res 40: 2377-2398.
    • (2012) Nucleic Acids Res , vol.40 , pp. 2377-2398
    • Hurley, D.1    Araki, H.2    Tamada, Y.3    Dunmore, B.4    Sanders, D.5
  • 8
    • 84864921682 scopus 로고    scopus 로고
    • Drem 2.0: Improved reconstruction of dynamic regulatory networks from time-series expression data
    • Schulz M, Devanny W, Gitter A, Zhong S, Ernst J, et al. (2012) Drem 2.0: Improved reconstruction of dynamic regulatory networks from time-series expression data. BMC Syst Biol 6: 104.
    • (2012) BMC Syst Biol , vol.6 , pp. 104
    • Schulz, M.1    Devanny, W.2    Gitter, A.3    Zhong, S.4    Ernst, J.5
  • 9
    • 84884518215 scopus 로고    scopus 로고
    • Biostatistical approaches for the reconstruction of gene co-expression networks based on transcriptomic data
    • López-Kleine L, Leal L, López C (2013) Biostatistical approaches for the reconstruction of gene co-expression networks based on transcriptomic data. Brief Funct Genomics.
    • (2013) Brief Funct Genomics
    • López-Kleine, L.1    Leal, L.2    López, C.3
  • 10
    • 84899965645 scopus 로고    scopus 로고
    • Supervised, semi-supervised and unsupervised inference of gene regulatory networks
    • First published online: May 21, 2013
    • Maetschke SR, Madhamshettiwar PB, Davis MJ, Ragan MA (2013) Supervised, semi-supervised and unsupervised inference of gene regulatory networks. Brief Bioinform First published online: May 21, 2013.
    • (2013) Brief Bioinform
    • Maetschke, S.R.1    Madhamshettiwar, P.B.2    Davis, M.J.3    Ragan, M.A.4
  • 11
    • 84873290420 scopus 로고    scopus 로고
    • Inference of gene regulatory networks from genome-wide knockout fitness data
    • Wang L, Wang X, Arkin AP, Samoilov MS (2013) Inference of gene regulatory networks from genome-wide knockout fitness data. Bioinformatics 29: 338-346.
    • (2013) Bioinformatics , vol.29 , pp. 338-346
    • Wang, L.1    Wang, X.2    Arkin, A.P.3    Samoilov, M.S.4
  • 12
    • 3142617691 scopus 로고    scopus 로고
    • Mathematical and computational techniques to deduce complex biochemical reaction mechanisms
    • DOI 10.1016/j.pbiomolbio.2004.04.002, PII S007961070400046X
    • Crampin E, Schnell S, McSharry P (2004) Mathematical and computational techniques to deduce complex biochemical reaction mechanisms. Prog Biophys Mol Biol 86: 77-112. (Pubitemid 38946555)
    • (2004) Progress in Biophysics and Molecular Biology , vol.86 , Issue.1 , pp. 77-112
    • Crampin, E.J.1    Schnell, S.2    McSharry, P.E.3
  • 13
    • 41649102929 scopus 로고    scopus 로고
    • Determination of complex reaction mechanisms. Analysis of chemical, biological and genetic networks
    • Ross J (2008) Determination of complex reaction mechanisms. analysis of chemical, biological and genetic networks. J Phys Chem A 112: 2134-2143.
    • (2008) J Phys Chem A , vol.112 , pp. 2134-2143
    • Ross, J.1
  • 17
    • 84874715571 scopus 로고    scopus 로고
    • Biological network inference for drug discovery
    • Lecca P, Priami C (2012) Biological network inference for drug discovery. Drug Discov Today 18: 256-264.
    • (2012) Drug Discov Today , vol.18 , pp. 256-264
    • Lecca, P.1    Priami, C.2
  • 18
    • 84856043672 scopus 로고
    • A mathematical theory of communication
    • Shannon C (1948) A mathematical theory of communication. Bell Syst Tech J 27: 379-423.
    • (1948) Bell Syst Tech J , vol.27 , pp. 379-423
    • Shannon, C.1
  • 20
    • 33846400424 scopus 로고    scopus 로고
    • Large-scale mapping and validation of escherichia coli transcriptional regulation from a compendium of expression profiles
    • Faith J, Hayete B, Thaden J, Mogno I, Wierzbowski J, et al. (2007) Large-scale mapping and validation of escherichia coli transcriptional regulation from a compendium of expression profiles. PLoS Biol 5: e8.
    • (2007) PLoS Biol , vol.5
    • Faith, J.1    Hayete, B.2    Thaden, J.3    Mogno, I.4    Wierzbowski, J.5
  • 21
    • 84891892293 scopus 로고    scopus 로고
    • Reverse engineering cellular networks with information theoretic methods
    • Villaverde AF, Ross J, Banga JR (2013) Reverse engineering cellular networks with information theoretic methods. Cells 2: 306-329.
    • (2013) Cells , vol.2 , pp. 306-329
    • Villaverde, A.F.1    Ross, J.2    Banga, J.R.3
  • 22
    • 0026736363 scopus 로고
    • Determination of eukaryotic protein coding regions using neural networks and information theory
    • Farber R, Lapedes A, Sirotkin K (1992) Determination of eukaryotic protein coding regions using neural networks and information theory. J Mol Biol 226: 471-479.
    • (1992) J Mol Biol , vol.226 , pp. 471-479
    • Farber, R.1    Lapedes, A.2    Sirotkin, K.3
  • 24
    • 0031616241 scopus 로고    scopus 로고
    • Reveal, a general reverse engineering algorithm for inference of genetic network architectures
    • Liang S, Fuhrman S, Somogyi R (1998) Reveal, a general reverse engineering algorithm for inference of genetic network architectures. In: Pac. Symp. Biocomput. volume 3, pp. 18-29.
    • (1998) Pac. Symp. Biocomput. , vol.3 , pp. 18-29
    • Liang, S.1    Fuhrman, S.2    Somogyi, R.3
  • 25
    • 0031616361 scopus 로고    scopus 로고
    • Cluster analysis and data visualization of large scale gene expression data
    • Michaels G, Carr D, Askenazi M, Fuhrman S, Wen X, et al. (1998) Cluster analysis and data visualization of large scale gene expression data. In: Pac. Symp. Biocomp. volume 3, pp. 42-53.
    • (1998) Pac. Symp. Biocomp. , vol.3 , pp. 42-53
    • Michaels, G.1    Carr, D.2    Askenazi, M.3    Fuhrman, S.4    Wen, X.5
  • 26
    • 0033655775 scopus 로고    scopus 로고
    • Mutual information relevance networks: Functional genomic clustering using pairwise entropy measurements
    • Butte A, Kohane I (2000) Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements. In: Pac. Symp. Biocomput. volume 5, pp. 418-429.
    • (2000) Pac. Symp. Biocomput. , vol.5 , pp. 418-429
    • Butte, A.1    Kohane, I.2
  • 28
    • 0041744850 scopus 로고    scopus 로고
    • On the deduction of chemical reaction pathways from measurements of time series of concentrations
    • Samoilov M, Arkin A, Ross J (2001) On the deduction of chemical reaction pathways from measurements of time series of concentrations. Chaos 11: 108-114.
    • (2001) Chaos , vol.11 , pp. 108-114
    • Samoilov, M.1    Arkin, A.2    Ross, J.3
  • 29
    • 0000122278 scopus 로고
    • Statistical construction of chemical reaction mechanisms from measured time-series
    • Arkin A, Ross J (1995) Statistical construction of chemical reaction mechanisms from measured time-series. J Phys Chem 99: 970-979.
    • (1995) J Phys Chem , vol.99 , pp. 970-979
    • Arkin, A.1    Ross, J.2
  • 30
    • 0030848624 scopus 로고    scopus 로고
    • A test case of correlation metric construction of a reaction pathway from measurements
    • DOI 10.1126/science.277.5330.1275
    • Arkin A, Shen P, Ross J (1997) A test case of correlation metric construction of a reaction pathway from measurements. Science 277: 1275-1279. (Pubitemid 27449073)
    • (1997) Science , vol.277 , Issue.5330 , pp. 1275-1279
    • Arkin, A.1    Shen, P.2    Ross, J.3
  • 31
    • 84861436119 scopus 로고    scopus 로고
    • Inferring biochemical reaction pathways: The case of the gemcitabine pharmacokinetics
    • Lecca P, Morpurgo D, Fantaccini G, Casagrande A, Priami C (2012) Inferring biochemical reaction pathways: the case of the gemcitabine pharmacokinetics. BMC Syst Biol 6: 51.
    • (2012) BMC Syst Biol , vol.6 , pp. 51
    • Lecca, P.1    Morpurgo, D.2    Fantaccini, G.3    Casagrande, A.4    Priami, C.5
  • 33
    • 33947305781 scopus 로고    scopus 로고
    • Aracne: An algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context
    • Margolin A, Nemenman I, Basso K, Wiggins C, Stolovitzky G, et al. (2006) Aracne: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinform 7: S7.
    • (2006) BMC Bioinform , vol.7
    • Margolin, A.1    Nemenman, I.2    Basso, K.3    Wiggins, C.4    Stolovitzky, G.5
  • 34
    • 84879435511 scopus 로고    scopus 로고
    • haracne: Improving the accuracy of regulatory model reverse engineering via higher-order data processing inequality tests
    • Jang IS, Margolin A, Califano A (2013) haracne: improving the accuracy of regulatory model reverse engineering via higher-order data processing inequality tests. Interface Focus 3: 20130011.
    • (2013) Interface Focus , vol.3 , pp. 20130011
    • Jang, I.S.1    Margolin, A.2    Califano, A.3
  • 35
    • 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 (2010) Timedelay-aracne: Reverse engineering of gene networks from time-course data by an information theoretic approach. BMC Bioinform 11: 154.
    • (2010) BMC Bioinform , vol.11 , pp. 154
    • Zoppoli, P.1    Morganella, S.2    Ceccarelli, M.3
  • 36
    • 24344458137 scopus 로고    scopus 로고
    • Feature selection based on mutual information: Criteria of Max-Dependency, Max-Relevance, and Min-Redundancy
    • DOI 10.1109/TPAMI.2005.159
    • Peng H, Long F, Ding C (2005) Feature selection based on mutual information: criteria of maxdependency, max-relevance, and min-redundancy. IEEE T Pattern Anal Mach Intell 27: 1226-1238. (Pubitemid 41245053)
    • (2005) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.27 , Issue.8 , pp. 1226-1238
    • Peng, H.1    Long, F.2    Ding, C.3
  • 37
    • 36248999573 scopus 로고    scopus 로고
    • Information-theoretic inference of large transcriptional regulatory networks
    • Meyer P, Kontos K, Lafitte F, Bontempi G (2007) Information-theoretic inference of large transcriptional regulatory networks. EURASIP J Bioinform Syst Biol 2007: 79879.
    • (2007) EURASIP J Bioinform Syst Biol , vol.2007 , pp. 79879
    • Meyer, P.1    Kontos, K.2    Lafitte, F.3    Bontempi, G.4
  • 38
    • 59949086432 scopus 로고    scopus 로고
    • minet: A r/bioconductor package for inferring large transcriptional networks using mutual information
    • Meyer P, Lafitte F, Bontempi G (2008) minet: A r/bioconductor package for inferring large transcriptional networks using mutual information. BMC Bioinform 9: 461.
    • (2008) BMC Bioinform , vol.9 , pp. 461
    • Meyer, P.1    Lafitte, F.2    Bontempi, G.3
  • 39
    • 58149349958 scopus 로고    scopus 로고
    • Learning transcriptional regulatory networks from high throughput gene expression data using continuous three-way mutual information
    • Luo W, Hankenson K, Woolf P (2008) Learning transcriptional regulatory networks from high throughput gene expression data using continuous three-way mutual information. BMC Bioinform 9: 467.
    • (2008) BMC Bioinform , vol.9 , pp. 467
    • Luo, W.1    Hankenson, K.2    Woolf, P.3
  • 40
    • 33646516485 scopus 로고
    • Possible generalization of boltzmann-gibbs statistics
    • Tsallis C (1988) Possible generalization of boltzmann-gibbs statistics. J Stat Phys 52: 479-487.
    • (1988) J Stat Phys , vol.52 , pp. 479-487
    • Tsallis, C.1
  • 42
    • 0032337028 scopus 로고    scopus 로고
    • Information gain within nonextensive thermostatistics
    • Borland L, Plastino A, Tsallis C (1998) Information gain within nonextensive thermostatistics. J Math Phys 39: 6490.
    • (1998) J Math Phys , vol.39 , pp. 6490
    • Borland, L.1    Plastino, A.2    Tsallis, C.3
  • 43
    • 0000557971 scopus 로고    scopus 로고
    • Generalized entropy-based criterion for consistent testing
    • Tsallis C (1998) Generalized entropy-based criterion for consistent testing. Phys Rev E 58: 1442-1445.
    • (1998) Phys Rev E , vol.58 , pp. 1442-1445
    • Tsallis, C.1
  • 44
    • 79955558275 scopus 로고    scopus 로고
    • Inference of gene regulatory networks from time series by tsallis entropy
    • Lopes F, de Oliveira E, Cesar R (2011) Inference of gene regulatory networks from time series by tsallis entropy. BMC Syst Biol 5: 61.
    • (2011) BMC Syst Biol , vol.5 , pp. 61
    • Lopes, F.1    De Oliveira, E.2    Cesar, R.3
  • 45
    • 0042526388 scopus 로고    scopus 로고
    • The mutual information: Detecting and evaluating dependencies between variables
    • Steuer R, Kurths J, Daub C, Weise J, Selbig J (2002) The mutual information: detecting and evaluating dependencies between variables. Bioinformatics 18: S231-S240. (Pubitemid 41073239)
    • (2002) Bioinformatics , vol.18 , Issue.SUPPL. 2
    • Steuer, R.1    Kurths, J.2    Daub, C.O.3    Weise, J.4    Selbig, J.5
  • 46
    • 34548696055 scopus 로고
    • Independent coordinates for strange attractors from mutual information
    • Fraser A, Swinney H (1986) Independent coordinates for strange attractors from mutual information. Phys Rev A 33: 1134-1140.
    • (1986) Phys Rev A , vol.33 , pp. 1134-1140
    • Fraser, A.1    Swinney, H.2
  • 47
    • 27944469202 scopus 로고    scopus 로고
    • Statistical validation of mutual information calculations: Comparison of alternative numerical algorithms
    • Cellucci C, Albano A, Rapp P (2005) Statistical validation of mutual information calculations: Comparison of alternative numerical algorithms. Phys Rev E 71: 066208.
    • (2005) Phys Rev E , vol.71 , pp. 066208
    • Cellucci, C.1    Albano, A.2    Rapp, P.3
  • 48
    • 0001837838 scopus 로고
    • An informational measure of correlation
    • Linfoot E (1957) An informational measure of correlation. Inf Control 1: 85-89.
    • (1957) Inf Control , vol.1 , pp. 85-89
    • Linfoot, E.1
  • 49
    • 0032762144 scopus 로고    scopus 로고
    • An overlap invariant entropy measure of 3d medical image alignment
    • Studholme C, Hill D, Hawkes D (1999) An overlap invariant entropy measure of 3d medical image alignment. Pattern Recogn 32: 71-86.
    • (1999) Pattern Recogn , vol.32 , pp. 71-86
    • Studholme, C.1    Hill, D.2    Hawkes, D.3
  • 50
    • 0034324043 scopus 로고    scopus 로고
    • A formalism for relevance and its application in feature subset selection
    • Bell DA, Wang H (2000) A formalism for relevance and its application in feature subset selection. Mach Learn 41: 175-195.
    • (2000) Mach Learn , vol.41 , pp. 175-195
    • Bell, D.A.1    Wang, H.2
  • 51
    • 77951641247 scopus 로고    scopus 로고
    • Predicting causal effects in large-scale systems from observational data
    • Maathuis MH, Colombo D, Kalisch M, Bühlmann P (2010) Predicting causal effects in large-scale systems from observational data. Nat Methods 7: 247-248.
    • (2010) Nat Methods , vol.7 , pp. 247-248
    • Maathuis, M.H.1    Colombo, D.2    Kalisch, M.3    Bühlmann, P.4
  • 53
    • 84883812062 scopus 로고    scopus 로고
    • Network link prediction by global silencing of indirect correlations
    • Barzel B, Barabási AL (2013) Network link prediction by global silencing of indirect correlations. Nat Biotechnol 31: 720-725.
    • (2013) Nat Biotechnol , vol.31 , pp. 720-725
    • Barzel, B.1    Barabási, A.L.2
  • 54
    • 84883771767 scopus 로고    scopus 로고
    • Network deconvolution as a general method to distinguish direct dependencies in networks
    • Feizi S, Marbach D, Médard M, Kellis M (2013) Network deconvolution as a general method to distinguish direct dependencies in networks. Nat Biotechnol 31: 726-733.
    • (2013) Nat Biotechnol , vol.31 , pp. 726-733
    • Feizi, S.1    Marbach, D.2    Médard, M.3    Kellis, M.4
  • 55
    • 84887104223 scopus 로고    scopus 로고
    • Predicting functional gene interactions with the hierarchical interaction score
    • Snijder B, Liberali P, Frechin M, Stoeger T, Pelkmans L (2013) Predicting functional gene interactions with the hierarchical interaction score. Nat Methods 10: 1089-1092.
    • (2013) Nat Methods , vol.10 , pp. 1089-1092
    • Snijder, B.1    Liberali, P.2    Frechin, M.3    Stoeger, T.4    Pelkmans, L.5
  • 56
    • 12944275674 scopus 로고    scopus 로고
    • Measuring information transfer
    • Schreiber T (2000) Measuring information transfer. Phys Rev Lett 85: 461.
    • (2000) Phys Rev Lett , vol.85 , pp. 461
    • Schreiber, T.1
  • 57
    • 84873157905 scopus 로고    scopus 로고
    • The relation between granger causality and directed information theory: A review
    • Amblard PO, Michel OJ (2012) The relation between granger causality and directed information theory: a review. Entropy 15: 113-143.
    • (2012) Entropy , vol.15 , pp. 113-143
    • Amblard, P.O.1    Michel, O.J.2
  • 59
    • 63049128934 scopus 로고    scopus 로고
    • A yeast synthetic network for in vivo assessment of reverse-engineering and modeling approaches
    • Cantone I, Marucci L, Iorio F, Ricci MA, Belcastro V, et al. (2009) A yeast synthetic network for in vivo assessment of reverse-engineering and modeling approaches. Cell 137: 172.
    • (2009) Cell , vol.137 , pp. 172
    • Cantone, I.1    Marucci, L.2    Iorio, F.3    Ricci, M.A.4    Belcastro, V.5
  • 60
    • 0029790351 scopus 로고    scopus 로고
    • Ultrasensitivity in the mitogen-activated protein kinase cascade
    • Huang CY, Ferrell JE (1996) Ultrasensitivity in the mitogen-activated protein kinase cascade. Proc Natl Acad Sci U S A 93: 10078-10083.
    • (1996) Proc Natl Acad Sci U S A , vol.93 , pp. 10078-10083
    • Huang, C.Y.1    Ferrell, J.E.2
  • 61
    • 59649110273 scopus 로고    scopus 로고
    • Generating realistic in silico gene networks for performance assessment of reverse engineering methods
    • Marbach D, Schaffter T, Mattiussi C, Floreano D (2009) Generating realistic in silico gene networks for performance assessment of reverse engineering methods. J Comput Biol 16: 229-239.
    • (2009) J Comput Biol , vol.16 , pp. 229-239
    • Marbach, D.1    Schaffter, T.2    Mattiussi, C.3    Floreano, D.4
  • 62
    • 79961200389 scopus 로고    scopus 로고
    • Genenetweaver: In silico benchmark generation and performance profiling of network inference methods
    • Schaffter T, Marbach D, Floreano D (2011) Genenetweaver: in silico benchmark generation and performance profiling of network inference methods. Bioinformatics 27: 2263-2270.
    • (2011) Bioinformatics , vol.27 , pp. 2263-2270
    • Schaffter, T.1    Marbach, D.2    Floreano, D.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.