Gene regulatory network inference: Data integration in dynamic models—A review

Cytoscape: A software Environment for integrated models of biomolecular interaction networks

Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888

The Elements of Statistical Learning

Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162

System Identification: Theory for the User

Lennart Ljung, A. (1987) · Cited by 17,690

Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans

Fire, A., Xu, S., Montgomery, M. K., Kostas, S. A., Driver, S. E., & Mello, C. C. (1998) · Nature · doi:10.1038/35888 · Cited by 15,429

System identification—Theory for the user

Sinha, N. K. (1989) · Automatica · doi:10.1016/0005-1098(89)90019-8 · Cited by 9,310

The Large-Scale Organization of Metabolic Networks

Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N., & Barabási, A.-L. (2000) · Nature · doi:10.1038/35036627 · Cited by 4,972

Metabolic stability and epigenesis in randomly constructed genetic nets

Kauffman, S. A. (1969) · Journal of Theoretical Biology · doi:10.1016/0022-5193(69)90015-0 · Cited by 4,871

Using Bayesian Networks to Analyze Expression Data

Friedman, N., Michal Linial, B., Nachman, I., & Pe’er, D. (2000) · Journal of Computational Biology · doi:10.1089/106652700750050961 · Cited by 3,248

Network motifs in the transcriptional regulation network of Escherichia coli

Shen-Orr, S. S., Milo, R., Mangan, S., & Alon, U. S. (2002) · Nature Genetics · doi:10.1038/ng881 · Cited by 2,970

Transcriptional Regulatory Networks in Saccharomyces cerevisiae

Lee, T. I., Rinaldi, N. J., Robert, F., Odom, D. T., Bar-Joseph, Z., Gerber, G. K., Hannett, N. M., Harbison, C. T., Thompson, C. M., Simon, I., et al. (2002) · Science · doi:10.1126/science.1075090 · Cited by 2,956

Modeling and Simulation of Genetic Regulatory Systems: A Literature Review

de Jong, H. (2002) · Journal of Computational Biology · doi:10.1089/10665270252833208 · Cited by 2,660

ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context

Margolin, A. A., Nemenman, I., Basso, K., Wiggins, C., Stolovitzky, G., Favera, R. D., & Califano, A. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-s1-s7 · Cited by 2,420

Proteomics to study genes and genomes

Pandey, A., & Mann, M. (2000) · Nature · doi:10.1038/35015709 · Cited by 2,399

Stochasticity in gene expression: from theories to phenotypes

Kærn, M., Elston, T. C., Blake, W. J., & Collins, J. J. (2005) · Nature Reviews Genetics · doi:10.1038/nrg1615 · Cited by 2,318

A Gene-Coexpression Network for Global Discovery of Conserved Genetic Modules

Stuart, J. M., Segal, E., Koller, D., & Kim, S. K. (2003) · Science · doi:10.1126/science.1087447 · Cited by 2,274

ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context

Margolin, A. A., Nemenman, I. M., Basso, K., Wiggins, C. H., Stolovitzky, G. A., Favera, R. D., & Califano, A. (2006) · BMC Bioinformatics · doi:10.7916/d8g15zbp · Cited by 2,260

Microarray data normalization and transformation

Quackenbush, J. (2002) · Nature Genetics · doi:10.1038/ng1032 · Cited by 1,975

Genome-Wide Location and Function of DNA Binding Proteins

Ren, B., Robert, F., Wyrick, J. J., Aparicio, O. M., Jennings, E. G., Simon, I., Zeitlinger, J., Schreiber, J., Hannett, N. M., Kanin, E. I., et al. (2000) · Science · doi:10.1126/science.290.5500.2306 · Cited by 1,768

A Tutorial on Learning with Bayesian Networks

Heckerman, D. E. (2008) · Studies in computational intelligence · doi:10.1007/978-3-540-85066-3_3 · Cited by 1,712

Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data

Segal, E., Shapira, M., Regev, A., Pe’er, D., Botstein, D., Koller, D., & Friedman, N. (2003) · Nature Genetics · doi:10.1038/ng1165 · Cited by 1,678

Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles

Faith, J. J., Hayete, B., Thaden, J. T., Mogno, I., Wierzbowski, J., Cottarel, G., Kasif, S., Collins, J. J., & Gardner, T. S. (2007) · PLoS Biology · doi:10.1371/journal.pbio.0050008 · Cited by 1,563

Reverse engineering of regulatory networks in human B cells

Basso, K., Margolin, A. A., Stolovitzky, G. A., Klein, U., Dalla‐Favera, R., & Califano, A. (2005) · Nature Genetics · doi:10.1038/ng1532 · Cited by 1,408

Metabolomics by numbers: acquiring and understanding global metabolite data

Goodacre, R., Vaidyanathan, S., Dunn, W. B., Harrigan, G. G., & Kell, D. B. (2004) · Trends in biotechnology · doi:10.1016/j.tibtech.2004.03.007 · Cited by 1,291

Nonlinear System Identification

Nelles, O. (2001) · Springer eBooks · doi:10.1007/978-3-662-04323-3 · Cited by 1,272

Applied bioinformatics for the identification of regulatory elements

Wasserman, W. W., & Sandelin, A. (2004) · Nature Reviews Genetics · doi:10.1038/nrg1315 · Cited by 1,233

The Regulation of Cellular Systems

Heinrich, R., & Schuster, S. (1996) · Springer eBooks · doi:10.1007/978-1-4613-1161-4 · Cited by 1,202

Inferring Genetic Networks and Identifying Compound Mode of Action via Expression Profiling

Gardner, T. S., di Bernardo, D., Lorenz, D., & Collins, J. J. (2003) · Science · doi:10.1126/science.1081900 · Cited by 1,117

Nonlinear system identification

Walter, E. (2003) · Automatica · doi:10.1016/s0005-1098(02)00239-x · Cited by 1,056

Revealing the world of RNA interference

Mello, C. C., & Conte, D. (2004) · Nature · doi:10.1038/nature02872 · Cited by 1,019

Boolean formalization of genetic control circuits

Thomas, R. (1973) · Journal of Theoretical Biology · doi:10.1016/0022-5193(73)90247-6 · Cited by 993

MUTUAL INFORMATION RELEVANCE NETWORKS: FUNCTIONAL GENOMIC CLUSTERING USING PAIRWISE ENTROPY MEASUREMENTS

Butte, A. J., & Kohane, I. S. (1999) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789814447331_0040 · Cited by 956

Reveal, a general reverse engineering algorithm for inference of genetic network architectures.

Liang, S., Fuhrman, S., & Somogyi, R. (1998) · PubMed · Cited by 950

Genetic network inference: from co-expression clustering to reverse engineering

D’haeseleer, P., Liang, S., & Somogyi, R. (2000) · Bioinformatics · doi:10.1093/bioinformatics/16.8.707 · Cited by 943

Parameter estimation in biochemical pathways: a comparison of global optimization methods

Moles, C. G., Mendes, P., & Banga, J. R. (2003) · Genome Research · doi:10.1101/gr.1262503 · Cited by 858

Ontological analysis of gene expression data: current tools, limitations, and open problems

Khatri, P., & Drăghici, S. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti565 · Cited by 850

The mutual information: detecting and evaluating dependencies between variables

Steuer, R., Kurths, J., Daub, C. O., Weise, J., & Selbig, J. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.suppl_2.s231 · Cited by 815

How to infer gene networks from expression profiles

Bansal, M., Belcastro, V., Ambesi‐Impiombato, A., & di Bernardo, D. (2007) · Molecular Systems Biology · doi:10.1038/msb4100120 · Cited by 789

Biochemical systems analysis

Savageau, M. A. (1969) · Journal of Theoretical Biology · doi:10.1016/s0022-5193(69)80026-3 · Cited by 724

MODELING GENE EXPRESSION WITH DIFFERENTIAL EQUATIONS

Chen, T., He, H., & Church, G. M. (1998) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789814447300_0004 · Cited by 700

IDENTIFICATION OF GENETIC NETWORKS FROM A SMALL NUMBER OF GENE EXPRESSION PATTERNS UNDER THE BOOLEAN NETWORK MODEL

Akutsu, T., Miyano, S., & Kuhara, S. (1998) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789814447300_0003 · Cited by 698

The hardwiring of development: organization and function of genomic regulatory systems

Arnone, M. I., & Davidson, E. H. (1997) · Development · doi:10.1242/dev.124.10.1851 · Cited by 693

Reverse engineering gene networks using singular value decomposition and robust regression

Yeung, M. K. S., Tegnér, J., & Collins, J. J. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.092576199 · Cited by 667

Computational discovery of gene modules and regulatory networks

Bar‐Joseph, Z., Gerber, G. K., Lee, T. I., Rinaldi, N. J., Yoo, J. Y., Robert, F., Gordon, D. B., Fraenkel, E., Jaakkola, T., Young, R. A., et al. (2003) · Nature Biotechnology · doi:10.1038/nbt890 · Cited by 605

Computational Analysis of Biochemical Systems: A Practical Guide for Biochemists and Molecular Biologists

Voit, E. O. (2000) · Cited by 587

Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic Bayesian networks

Husmeier, D. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg313 · Cited by 536

A comparative review of statistical methods for discovering differentially expressed genes in replicated microarray experiments

Pan, W. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.4.546 · Cited by 522

The inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo

Bonneau, R., Reiss, D. J., Shannon, P., Facciotti, M., Hood, L., Baliga, N. S., & Thorsson, V. (2006) · Genome Biology · doi:10.1186/gb-2006-7-5-r36 · Cited by 510

LINEAR MODELING OF mRNA EXPRESSION LEVELS DURING CNS DEVELOPMENT AND INJURY

D’haeseleer, P., Wen, X., Fuhrman, S., & Somogyi, R. (1998) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789814447300_0005 · Cited by 498

Reverse engineering gene networks: integrating genetic perturbations with dynamical modeling

Tegnér, J., Yeung, M. K. S., Hasty, J., & Collins, J. J. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0933416100 · Cited by 433

Gene networks inference using dynamic Bayesian networks

Perrin, B.-E., Ralaivola, L., Mazurie, A., Bottani, S., Mallet, J. J., & d’Alché–Buc, F. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg1071 · Cited by 425

MODELING REGULATORY NETWORKS WITH WEIGHT MATRICES

Weaver, D. C., Workman, C. T., & Stormo, G. D. (1998) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789814447300_0011 · Cited by 409

Inferring cellular networks – a review

Markowetz, F. M., & Spang, R. (2007) · BMC Bioinformatics · doi:10.1186/1471-2105-8-s6-s5 · Cited by 398

Boolean network models of cellular regulation: prospects and limitations

Bornholdt, S. (2008) · Journal of The Royal Society Interface · doi:10.1098/rsif.2008.0132.focus · Cited by 394

USING GRAPHICAL MODELS AND GENOMIC EXPRESSION DATA TO STATISTICALLY VALIDATE MODELS OF GENETIC REGULATORY NETWORKS

Hartemink, A. J., Gifford, D. K., Jaakkola, T., & Young, R. A. (2000) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789814447362_0042 · Cited by 392

Inference of gene regulatory networks and compound mode of action from time course gene expression profiles

Bansal, M., Gatta, G. D., & di Bernardo, D. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl003 · Cited by 389

From correlation to causation networks: a simple approximate learning algorithm and its application to high-dimensional plant gene expression data

Opgen-Rhein, R., & Strimmer, K. (2007) · BMC Systems Biology · doi:10.1186/1752-0509-1-37 · Cited by 386

Dialogue on Reverse‐Engineering Assessment and Methods

Stolovitzky, G. A., Monroe, D., & Califano, A. (2007) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1407.021 · Cited by 377

Protein interaction networks from yeast to human

Bork, P., Jensen, L. J., von Mering, C., Ramani, A. K., Lee, I., & Marcotte, E. M. (2004) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2004.05.003 · Cited by 354

Chemogenomic profiling on a genome-wide scale using reverse-engineered gene networks

di Bernardo, D., Thompson, M. J., Gardner, T. S., Chobot, S. E., Eastwood, E. L., Wojtovich, A. P., Elliott, S. J., Schaus, S. E., & Collins, J. J. (2005) · Nature Biotechnology · doi:10.1038/nbt1075 · Cited by 349

Inferring gene regulatory networks from multiple microarray datasets

Wang, Y., Joshi, T., Zhang, X., Xu, D. H., & Chen, L. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl396 · Cited by 324

Judging the Quality of Gene Expression-Based Clustering Methods Using Gene AnnotationPreprint

Gibbons, F. D., & Roth, F. P. (2002) · Genome Research · doi:10.1101/gr.397002 · Cited by 322

A primer on learning in Bayesian networks for computational biology

Needham, C. J., Bradford, J. R., Bulpitt, A. J., & Westhead, D. R. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030129 · Cited by 311

A hybrid approach for efficient and robust parameter estimation in biochemical pathways

Rodriguez-Fernandez, M., Mendes, P., & Banga, J. R. (2006) · Biosystems · doi:10.1016/j.biosystems.2005.06.016 · Cited by 304

Biochemical systems analysis

Savageau, M. A. (1970) · Journal of Theoretical Biology · doi:10.1016/s0022-5193(70)80013-3 · Cited by 302

Dynamic modeling of gene expression data

Holter, N. S., Maritan, A., Cieplak, M., Fedoroff, N. V., & Banavar, J. R. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.4.1693 · Cited by 300

DISCOVERY OF REGULATORY INTERACTIONS THROUGH PERTURBATION: INFERENCE AND EXPERIMENTAL DESIGN

Ideker, T., THORSSONt, V., & Karp, R. M. (1999) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789814447331_0029 · Cited by 276

COMBINING LOCATION AND EXPRESSION DATA FOR PRINCIPLED DISCOVERY OF GENETIC REGULATORY NETWORK MODELS

Hartemink, A. J., Gifford, D. K., Jaakkola, T., & Young, R. A. (2001) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789812799623_0041 · Cited by 267

Reconstructing Gene Regulatory Networks with Bayesian Networks by Combining Expression Data with Multiple Sources of Prior Knowledge

Werhli, A. V., & Husmeier, D. (2007) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1282 · Cited by 263

Inference of S-system models of genetic networks using a cooperative coevolutionary algorithm

Kimura, S., Ide, K., Kashihara, A., Kano, M., Okada, M., Masui, R., Nakagawa, N., Yokoyama, S., Kuramitsu, S., & Konagaya, A. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bti071 · Cited by 259

Dynamic modelling and analysis of biochemical networks: mechanism-based models and model-based experiments

van Riel, N. A. W. (2006) · Briefings in Bioinformatics · doi:10.1093/bib/bbl040 · Cited by 259

Handbook of computational molecular biology

(2006) · Choice Reviews Online · doi:10.5860/choice.43-6513 · Cited by 235

Reverse-engineering transcription control networks

Gardner, T. S., & Faith, J. J. (2005) · Physics of Life Reviews · doi:10.1016/j.plrev.2005.01.001 · Cited by 233

Reconstructing dynamic regulatory maps

Ernst, J., Vainas, O., Harbison, C. T., Simon, I., & Bar‐Joseph, Z. (2007) · Molecular Systems Biology · doi:10.1038/msb4100115 · Cited by 216

Artificial gene networks for objective comparison of analysis algorithms

Mendes, P., Sha, W., & Ye, K. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg1069 · Cited by 208

Modeling T-cell activation using gene expression profiling and state-space models

Rangel‐Escareño, C., Angus, J. E., Ghahramani, Z., Lioumi, M., Sotheran, E. C., Gaiba, A., Wild, D. L., & Falciani, F. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth093 · Cited by 207

Inferring a system of differential equations for a gene regulatory network by using genetic programming

Sakamoto, E., & Iba, H. (2002) · Congress on Evolutionary Computation · doi:10.1109/cec.2001.934462 · Cited by 204

Conservation and Coevolution in the Scale-Free Human Gene Coexpression Network

Jordan, I. K., Mariño‐Ramírez, L., Wolf, Y. I., & Koonin, E. V. (2004) · Molecular Biology and Evolution · doi:10.1093/molbev/msh222 · Cited by 194

Genetic Network Modeling

van Someren, E. P., Wessels, L. F. A., Backer, E., & Reinders, M. J. T. (2002) · Pharmacogenomics · doi:10.1517/14622416.3.4.507 · Cited by 194

SIRENE: supervised inference of regulatory networks

Mordelet, F., & Vert, J. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn273 · Cited by 191

Estimating gene networks from gene expression data by combining Bayesian network model with promoter element detection

Tamada, Y., Kim, S., Bannai, H., Imoto, S., Tashiro, K., Kuhara, S., & Miyano, S. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg1082 · Cited by 189

Reverse Engineering the Gap Gene Network of Drosophila melanogaster

Perkins, T. J., Jaeger, J., Reinitz, J., & Glass, L. (2006) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0020051 · Cited by 187

Linear modeling of genetic networks from experimental data.

van Someren, E. P., Wessels, L., & Reinders, M. J. T. (2000) · PubMed · Cited by 175

INFORMATIVE STRUCTURE PRIORS: JOINT LEARNING OF DYNAMIC REGULATORY NETWORKS FROM MULTIPLE TYPES OF DATA

Bernard, A., & Hartemink, A. J. (2004) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789812702456_0044 · Cited by 173

COMBINING MICROARRAYS AND BIOLOGICAL KNOWLEDGE FOR ESTIMATING GENE NETWORKS VIA BAYESIAN NETWORKS

Imoto, S., Higuchi, T., Goto, T., Tashiro, K., Kuhara, S., & Miyano, S. (2004) · Journal of Bioinformatics and Computational Biology · doi:10.1142/s021972000400048x · Cited by 172

Boolean dynamics of genetic regulatory networks inferred from microarray time series data

Martin, S., Zhang, Z., Martino, A., & Faulon, J. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm021 · Cited by 171

Inference from Clustering with Application to Gene-Expression Microarrays

Dougherty, E. R., Barrera, J., Marcel Brun, A., Kim, S., Junior, R. M. C., Chen, Y., Bittner, M. L., & Trent, J. M. (2002) · Journal of Computational Biology · doi:10.1089/10665270252833217 · Cited by 158

A COMPARISON OF GENETIC NETWORK MODELS

Wessels, L. F. A., van Someren, E. P., & Reinders, M. J. T. (2000) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789814447362_0049 · Cited by 151

Coarse-grained reverse engineering of genetic regulatory networks

Wahde, M., & Hertz, J. (2000) · Biosystems · doi:10.1016/s0303-2647(99)00090-8 · Cited by 148

Reconstructing biological networks using conditional correlation analysis

Rice, J. J., Tu, Y., & Stolovitzky, G. A. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bti064 · Cited by 135

Dynamic network reconstruction from gene expression data applied to immune response during bacterial infection

Guthke, R., Moller, U., Hoffmann, M., Thiès, F., & Topfer, S. (2004) · Computer applications in the biosciences · doi:10.1093/bioinformatics/bti226 · Cited by 131

Reconstructing gene-regulatory networks from time series, knock-out data, and prior knowledge

Geier, F. M., Timmer, J., & Fleck, C. C. (2007) · BMC Systems Biology · doi:10.1186/1752-0509-1-11 · Cited by 122

Molecular discrimination of responders and nonresponders to anti-TNFalpha therapy in rheumatoid arthritis by etanercept

Koczan, D., Drynda, S., Hecker, M., Drynda, A., Guthke, R., Kekow, J., & Thiesen, H. (2008) · Arthritis Research & Therapy · doi:10.1186/ar2419 · Cited by 120

Reverse engineering of gene regulatory networks

Cho, K.-H., Choo, S., Jung, S. H., Kim, J., Choi, H. S., & Kim, J. (2007) · IET Systems Biology · doi:10.1049/iet-syb:20060075 · Cited by 120

Comparing association network algorithms for reverse engineering of large-scale gene regulatory networks: synthetic versus real data

Soranzo, N., Ginestra Bianconi, A., & Altafini, C. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm163 · Cited by 115

Non-transcriptional pathway features reconstructed from secondary effects of RNA interference

Markowetz, F. M., Bloch, J., & Spang, R. (2005) · Computer applications in the biosciences · doi:10.1093/bioinformatics/bti662 · Cited by 97

Parameter optimization in S-system models

Vilela, M., Chou, I.-C., Vinga, S., de Vasconcelos, A. T. R., Voit, E. O., & Almeida, J. S. (2008) · BMC Systems Biology · doi:10.1186/1752-0509-2-35 · Cited by 96

Identification of metabolic system parameters using global optimization methods

Polisetty, P. K., Voit, E. O., & Gatzke, E. P. (2006) · Theoretical Biology and Medical Modelling · doi:10.1186/1742-4682-3-4 · Cited by 93

Combining microarrays and biological knowledge for estimating gene networks via Bayesian networks

Imoto, S., Higuchi, T., Goto, T., Tashiro, K., Kuhara, S., & Miyano, S. (2004) · IEEE Computational Systems Bioinformatics Conference (CSB) · doi:10.1109/csb.2003.1227309 · Cited by 90

Computational and Statistical Approaches to Genomics

Zhang, W., & Shmulevich, I. (2002) · Springer eBooks · doi:10.1007/b101927 · Cited by 87

USING PROTEIN-PROTEIN INTERACTIONS FOR REFINING GENE NETWORKS ESTIMATED FROM MICROARRAY DATA BY BAYESIAN NETWORKS

Nariai, N., KIM, S., IMOTO, S., & Miyano, S. (2003) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789812704856_0032 · Cited by 83

Non-uniqueness and Inversions in Cluster Analysis

Morgan, B. J. T., & Ray, A. P. G. (1995) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.2307/2986199 · Cited by 82

Least absolute regression network analysis of the murine osteoblast differentiation network

van Someren, E. P., Vaes, B. L. T., Steegenga, W. T., Sijbers, A. M., Dechering, K. J., & Reinders, M. J. T. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti816 · Cited by 82

Handbook of Computational Molecular Biology

Aluru, S. (2005) · Chapman & Hall/CRC eBooks · doi:10.1201/9781420036275 · Cited by 80

Building and analysing genome-wide gene disruption networks

Rung, J., Schlitt, T., Brāzma, A., Freivalds, K., & Vilo, J. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.suppl_2.s202 · Cited by 75

Computational and Experimental Approaches for Modeling Gene Regulatory Networks

Goutsias, J. I., & Lee, N. (2007) · Current Pharmaceutical Design · doi:10.2174/138161207780765945 · Cited by 59

Identifying gene regulatory networks from experimental data

Chen, T., Filkov, V., & Skiena, S. (2001) · Parallel Computing · doi:10.1016/s0167-8191(00)00092-2 · Cited by 58

Using Prior Knowledge to Improve Genetic Network Reconstruction from Microarray Data

Le, P. P., Bahl, A., & Ungar, L. (2004) · In Silico Biology · doi:10.3233/isb-00137 · Cited by 55

Identifying Gene Regulatory Networks from Gene Expression Data

Aluru, S. (2005) · Chapman & Hall/CRC eBooks · doi:10.1201/9781420036275-41 · Cited by 45

Tumor classification by gene expression profiling

Granzow, M., Berrar, D., Dubitzky, W., Schuster, A., Azuaje, F. J., & Eils, R. (2001) · ACM SIGBIO Newsletter · doi:10.1145/381371.381384 · Cited by 44

From Coexpression to Coregulation: An Approach to Inferring Transcriptional Regulation among Gene Classes from Large-Scale Expression Data

Mjolsness, E., Mann, T., Castaño, R., & Wold, B. J. (1999) · CaltechAUTHORS (California Institute of Technology) · Cited by 42

Indeterminacy of Reverse Engineering of Gene Regulatory Networks: The Curse of Gene Elasticity

Krishnan, A. V., Giuliani, A., & Tomita, M. (2007) · PLoS ONE · doi:10.1371/journal.pone.0000562 · Cited by 41

The end of the microarray Tower of Babel: will universal standards lead the way?

Kawasaki, E. S. (2006) · PubMed Central · Cited by 39

USING DIRECTED INFORMATION TO BUILD BIOLOGICALLY RELEVANT INFLUENCE NETWORKS

Rao, A. U. K., Hero, A. O., States, D. J., & Engel, J. D. (2008) · Journal of Bioinformatics and Computational Biology · doi:10.1142/s0219720008003515 · Cited by 38

Identifying Gene Regulatory Networks from Gene Expression Data

Filkov, V. (2005) · Chapman & Hall/CRC computer and information science series · doi:10.1201/9781420036275.ch27 · Cited by 37

Studying the Conditions for Learning Dynamic Bayesian Networks to Discover Genetic Regulatory Networks

van Berlo, R. J. P., van Someren, E. P., & Reinders, M. J. T. (2003) · SIMULATION · doi:10.1177/0037549703040942 · Cited by 33

Modelling metabolic networks using power-laws and S-systems

Voit, E. O. (2008) · Essays in Biochemistry · doi:10.1042/bse0450029 · Cited by 33

Bayesian variable selection and data integration for biological regulatory networks

Jensen, S. T., Chen, G., & Stoeckert, C. J. (2007) · The Annals of Applied Statistics · doi:10.1214/07-aoas130 · Cited by 29

Searching for Limited Connectivity in Genetic Network Models

van Someren, E. P. (2004) · Cited by 28

A stochastic differential equation model for transcriptional regulatory networks

Climescu-Haulica, A., & Quirk, M. D. (2007) · BMC Bioinformatics · doi:10.1186/1471-2105-8-s5-s4 · Cited by 25

Rank-based edge reconstruction for scale-free genetic regulatory networks

Chen, G., Larsen, P., Almasri, E., & Dai, Y. D. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-75 · Cited by 25

Discovery of Gene Regulatory Networks in Aspergillus fumigatus

Guthke, R., Kniemeyer, O., Albrecht, D., Brakhage, A. A., & Möller, U. (2008) · Springer eBooks · doi:10.1007/978-3-540-71037-0_3 · Cited by 21

Comparing mathematical models on the problem of network inference

Spieth, C., Hassis, N., & Streichert, F. (2006) · Genetic and Evolutionary Computation Conference (GECCO) · doi:10.1145/1143997.1144045 · Cited by 20

The NetGenerator Algorithm: Reconstruction of Gene Regulatory Networks

Toepfer, S., Guthke, R., Driesch, D., Woetzel, D., & Pfaff, M. (2008) · Springer eBooks · doi:10.1007/978-3-540-71037-0_8 · Cited by 19

A statistical method to incorporate biological knowledge for generating testable novel gene regulatory interactions from microarray experiments

Larsen, P., Almasri, E., Chen, G., & Dai, Y. D. (2007) · BMC Bioinformatics · doi:10.1186/1471-2105-8-317 · Cited by 18

USING DIRECTED INFORMATION TO BUILD BIOLOGICALLY RELEVANT INFLUENCE NETWORKS

Rao, A. U. K., Hero, A. O., States, D. J., & Engel, J. D. (2007) · IEEE Computational Systems Bioinformatics Conference (CSB) · doi:10.1142/9781860948732_0018 · Cited by 18

Performance of data resampling methods for robust class discovery based on clustering

Möller, U., & Radke, D. (2006) · Intelligent Data Analysis · doi:10.3233/ida-2006-10204 · Cited by 16

Inferring regulatory systems with noisy pathway information

Spieth, C., Streichert, F., Speer, N., & Zell, A. (2005) · Cited by 15

Regularization and Noise Injection for Improving Genetic Network Models

van Someren, E. P., Wessels, L. F. A., Reinders, M. J. T., & Backer, E. (2006) · Springer eBooks · doi:10.1007/0-387-26288-1_14 · Cited by 14

Quantitative Evaluation of Established Clustering Methods for Gene Expression Data

Radke, D., & Möller, U. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-30547-7_40 · Cited by 3

Integrating Prior Knowledge into the Fitness Function of an Evolutionary Algorithm for Deriving Gene Regulatory Networks

Birkmeier, B. (2006) · Cited by 2

Microbial interactions: from networks to models

Faust, K., & Raes, J. (2012) · Nature Reviews Microbiology · doi:10.1038/nrmicro2832 · Cited by 4,268

Gene co-expression analysis for functional classification and gene–disease predictions

van Dam, S., Võsa, U., van der Graaf, A., Franke, L., & de Magalhães, J. P. (2017) · Briefings in Bioinformatics · doi:10.1093/bib/bbw139 · Cited by 995

Integrated Analysis of Transcriptomic and Proteomic Data

Haider, S., & Pal, R. (2013) · Current Genomics · doi:10.2174/1389202911314020003 · Cited by 446

Data based identification and prediction of nonlinear and complex dynamical systems

Wang, W.-X., Lai, Y.-C., & Grebogi, C. (2016) · Physics Reports · doi:10.1016/j.physrep.2016.06.004 · Cited by 328

Gene regulatory networks and their applications: understanding biological and medical problems in terms of networks

Emmert-Streib, F., Dehmer, M., & Haibe-Kains, B. (2014) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2014.00038 · Cited by 282

Reverse engineering of gene regulatory networks

Cho, K.-H., Choo, S., Jung, S. H., Kim, J., Choi, H. S., & Kim, J. (2007) · IET Systems Biology · doi:10.1049/iet-syb:20060075 · Cited by 120

Reverse engineering of gene regulatory networks from biological data

Liu, L., Wu, F., & Zhang, W. (2012) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.1068 · Cited by 14

Computational methods for Gene Regulatory Networks reconstruction and analysis: A review

Delgado-Chaves, F. M., & Gómez-Vela, F. (2018) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2018.10.006 · Cited by 213

iLSGRN: inference of large-scale gene regulatory networks based on multi-model fusion

Wu, Y., Qian, B., Wang, A., Dong, H., Zhu, E., & Ma, B. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad619 · Cited by 5

Integrating heterogeneous gene expression data for gene regulatory network modelling

Sîrbu, A., Ruskin, H. J., & Crane, M. (2011) · Theory in Biosciences · doi:10.1007/s12064-011-0133-0 · Cited by 8