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

Systems biology and modeling in neuroblastoma: practicalities and perspectives

Logan, J. A., Kelly, M. E., Ayers, D., Shipillis, N., Baier, G., & Day, P. J. (2010) · Expert Review of Molecular Diagnostics · doi:10.1586/erm.10.4 · Cited by 13

Assessing the gain of biological data integration in gene networks inference

Vicente, F. F. D. R., Lopes, F. M., Hashimoto, R. F., & Junior, R. M. C. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-s6-s7 · Cited by 13

Computing a Worm: Reverse-Engineering Planarian Regeneration

Lobo, D., & Levin, M. G. (2016) · Emergence, complexity and computation · doi:10.1007/978-3-319-33921-4_24 · Cited by 14

Using single-index ODEs to study dynamic gene regulatory network

Zhang, Q., Yu, Y., Zhang, J., & Liang, H. (2018) · PLoS ONE · doi:10.1371/journal.pone.0192833 · Cited by 14

Large-Scale Functional Analysis of CRP-Mediated Feed-Forward Loops

Yang, C.-D., Huang, H., Chen, Y., Sirjana, S., Huang, H., & Tseng, C. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19082335 · Cited by 13

Inferring phage–bacteria infection networks from time-series data

Jover, L. F., Romberg, J. K., & Weitz, J. S. (2016) · Royal Society Open Science · doi:10.1098/rsos.160654 · Cited by 13

Unique superdiffusion induced by directionality in multiplex networks

Wang, X., Tejedor, A., Wang, Y., & Moreno, Y. (2021) · New Journal of Physics · doi:10.1088/1367-2630/abdb71 · Cited by 13

Inferring Time-Delayed Gene Regulatory Networks Using Cross-Correlation and Sparse Regression

Mundra, P. A., Zheng, J., Niranjan, M., Welsch, R. E., & Rajapakse, J. C. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-38036-5_10 · Cited by 13

Yeast Systems Biology

Castrillo, J. I., Pir, P., & Oliver, S. G. (2012) · Elsevier eBooks · doi:10.1016/b978-0-12-385944-0.00018-6 · Cited by 14

Big Data Analytics and Its Prospects in Computational Proteomics

Banerjee, S., Basu, S., & Nasipuri, M. (2015) · Advances in intelligent systems and computing · doi:10.1007/978-81-322-2247-7_60 · Cited by 12

Integrating epigenetic prior in dynamic Bayesian network for gene regulatory network inference

Chen, H., Maduranga, D. A. K., Mundra, P. A., & Zheng, J. (2013) · IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) · doi:10.1109/cibcb.2013.6595391 · Cited by 12

A Clustering based Method Accelerating Gene Regulatory Network Reconstruction

Dimitrakopoulos, G. Ν., Maraziotis, I. A., Sgarbas, K., & Bezerianos, A. (2014) · Procedia Computer Science · doi:10.1016/j.procs.2014.05.183 · Cited by 12

Parameter Estimation for Gene Regulatory Networks from Microarray Data: Cold Shock Response in Saccharomyces cerevisiae

Dahlquist, K. D., Fitzpatrick, B. G., Camacho, E. T., Entzminger, S. D., & Wanner, N. C. (2015) · Bulletin of Mathematical Biology · doi:10.1007/s11538-015-0092-6 · Cited by 12

Multi-Target Analysis and Design of Mitochondrial Metabolism

Angione, C., Costanza, J., Carapezza, G., Lió, P., & Nicosia, G. (2015) · PLoS ONE · doi:10.1371/journal.pone.0133825 · Cited by 12

A posterior probability approach for gene regulatory network inference in genetic perturbation data

Young, W. C., Raftery, A. E., & Yeung, K. Y. (2016) · Mathematical Biosciences & Engineering · doi:10.3934/mbe.2016041 · Cited by 12

Haploid evolutionary constructor: New features and further challenges

Lashin, S. A., & Matushkin, Y. G. (2012) · In Silico Biology · doi:10.3233/isb-2012-0447 · Cited by 12

Integration of Epigenetic Data in Bayesian Network Modeling of Gene Regulatory Network

Zheng, J., Chaturvedi, I., & Rajapakse, J. C. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-24855-9_8 · Cited by 12

Multivariate Mutual Information Measures for Discovering Biological Networks

Pham, T. H., Ho, T. B., Nguyen, Q. D., Tran, D. H., & Nguyen, V. H. (2012) · RIVF International Conference on Computing and Communication Technologies (RIVF) · doi:10.1109/rivf.2012.6169834 · Cited by 12

Correlation-based iterative clustering methods for time course data: The identification of temporal gene response modules for influenza infection in humans

Carey, M., Wu, S., Gan, G., & Wu, H. (2016) · Infectious Disease Modelling · doi:10.1016/j.idm.2016.07.001 · Cited by 12

Inferring Large-Scale Gene Regulatory Networks Using a Randomized Algorithm Based on Singular Value Decomposition

Fan, A., Wang, H., Xiang, H., & Zou, X. (2018) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2018.2825446 · Cited by 12

Incorporating biological knowledge for construction of fuzzy networks of gene associations

Gómez-Vela, F., Barranco, C. D., & Díaz–Díaz, N. (2016) · Applied Soft Computing · doi:10.1016/j.asoc.2016.01.014 · Cited by 11

The applications of network analysis in fruit ripening

Wee, C. C., Subbiah, V. K., Arita, M., & Goh, H. (2022) · Scientia Horticulturae · doi:10.1016/j.scienta.2022.111785 · Cited by 11

Stages of Gene Regulatory Network Inference: the Evolutionary Algorithm Role

Sîrbu, A., Heather, J., & Crane, M. (2011) · InTech eBooks · doi:10.5772/15182 · Cited by 11

Development and use of the Cytoscape app GFD-Net for measuring semantic dissimilarity of gene networks

Díaz–Montaña, J. J., & Díaz–Díaz, N. (2014) · F1000Research · doi:10.12688/f1000research.4573.1 · Cited by 11

TDSDMI: Inference of time-delayed gene regulatory network using S-system model with delayed mutual information

Yang, B., Zhang, W., Wang, H., Song, C., & Chen, Y. (2016) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2016.03.024 · Cited by 11

Dynamical resilience of networks against targeted attack

Xu, F., Si, S., Duan, D., Lv, C., & Xie, J. (2019) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2019.121329 · Cited by 12

Developmental switching in Physarum polycephalum : Petri net analysis of single cell trajectories of gene expression indicates responsiveness and genetic plasticity of the Waddington quasipotential landscape

Werthmann, B., & Marwan, W. (2017) · Journal of Physics D Applied Physics · doi:10.1088/1361-6463/aa8e2b · Cited by 11

Genome structure predicts modular transcriptome responses to genetic and environmental conditions

Mark, S., Weiss, J., Sharma, E., Liu, T.-A., Wang, W., Claycomb, J. M., & Cutter, A. (2019) · bioRxiv · doi:10.1111/mec.15185 · Cited by 10

Inferring Broad Regulatory Biology from Time Course Data: Have We Reached an Upper Bound under Constraints Typical of In Vivo Studies?

Vashishtha, S., Broderick, G., Craddock, T. J. A., FLETCHER, M. A., & Klimas, N. G. (2015) · PLoS ONE · doi:10.1371/journal.pone.0127364 · Cited by 11

A tree-like Bayesian structure learning algorithm for small-sample datasets from complex biological model systems

Yin, W., Garimalla, S., Moreno, A., Galinski, M. R., & Styczynski, M. P. (2015) · BMC Systems Biology · doi:10.1186/s12918-015-0194-7 · Cited by 10

A neural network based modeling and validation approach for identifying gene regulatory networks

Knott, S., Mostafavi, S., & Mousavi, P. (2010) · Neurocomputing · doi:10.1016/j.neucom.2010.04.018 · Cited by 11

Regulatory Snapshots: Integrative Mining of Regulatory Modules from Expression Time Series and Regulatory Networks

Gonçalves, J. P., Aires, R. S., Francisco, A. P., & Madeira, S. C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0035977 · Cited by 10

More than meets the eye: Emergent properties of transcription factors networks in Arabidopsis

Muhammad, D., Schmittling, S., Williams, C., & Long, T. A. (2016) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2016.07.017 · Cited by 11

Network Modeling and Control of Dynamic Disease Pathways, Review and Perspectives

Hsiao, Y.-C., & Dutta, A. (2024) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2024.3378155 · Cited by 10

Reconstruction of gene regulatory networks using graph neural networks

Emma Paul, M., Jereesh, A. S., & Kumar, G. S. (2024) · Applied Soft Computing · doi:10.1016/j.asoc.2024.111899 · Cited by 12

The Autoimmune Tautology: An In Silico Approach

Cifuentes, R., Restrepo-Montoya, D., & Anaya, J. (2012) · Autoimmune Diseases · doi:10.1155/2012/792106 · Cited by 10

Derivative-variable correlation reveals the structure of dynamical networks

Levnajić, Z. (2013) · The European Physical Journal B · doi:10.1140/epjb/e2013-30986-5 · Cited by 10

Social choice in distributed classification tasks: Dealing with vertically partitioned data

Recamonde‐Mendoza, M., & Bazzan, A. L. C. (2015) · Information Sciences · doi:10.1016/j.ins.2015.11.001 · Cited by 10

A Systems Approach to Integrative Biology: An Overview of Statistical Methods to Elucidate Association and Architecture

Ciaccio, M. F., Finkle, J. D., Xue, A. Y., & Bagheri, N. (2014) · Integrative and Comparative Biology · doi:10.1093/icb/icu037 · Cited by 10

Temporary and permanent control of partially specified Boolean networks

Brim, L., Pastva, S., Šafránek, D., & Šmijáková, E. (2022) · Biosystems · doi:10.1016/j.biosystems.2022.104795 · Cited by 10

Mini-review: Gene regulatory network benefits from three-dimensional chromatin conformation and structural biology

Zhu, X., Huang, Q., Luo, J., Kong, D., & Zhang, Y. (2023) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2023.02.028 · Cited by 12

Applying attractor dynamics to infer gene regulatory interactions involved in cellular differentiation

Ghaffarizadeh, A., Podgorski, G. J., & Flann, N. S. (2017) · Biosystems · doi:10.1016/j.biosystems.2016.12.004 · Cited by 9

A big data pipeline: Identifying dynamic gene regulatory networks from time-course Gene Expression Omnibus data with applications to influenza infection

Carey, M., Ramírez, J. C., Wu, S., & Wu, H. (2018) · Statistical Methods in Medical Research · doi:10.1177/0962280217746719 · Cited by 10

Inference of Genetic Networks From Time-Series and Static Gene Expression Data: Combining a Random-Forest-Based Inference Method With Feature Selection Methods

Kimura, S., Fukutomi, R., Tokuhisa, M., & Okada, M. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.595912 · Cited by 10

Data-Driven Boolean Network Inference Using a Genetic Algorithm With Marker-Based Encoding

Liu, X., Shi, N., Wang, Y., Ji, Z., & He, S. (2021) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2021.3055646 · Cited by 11

Transcriptome Dynamics and Potential Roles of Sox6 in the Postnatal Heart

An, C.-I., Ichihashi, Y., Peng, J., Sinha, N. R., & Hagiwara, N. (2016) · PLoS ONE · doi:10.1371/journal.pone.0166574 · Cited by 10

A hybrid framework for reverse engineering of robust Gene Regulatory Networks

Jafari, M., Ghavami, B., & Sattari-Naeini, V. (2017) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2017.05.004 · Cited by 10

The Ability of Different Imputation Methods to Preserve the Significant Genes and Pathways in Cancer

Aghdam, R., Baghfalaki, T., Khosravi, P., & Ansari, E. S. (2017) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2017.08.003 · Cited by 9

Network inference using steady-state data and Goldbeter–koshland kinetics

Oates, C. J., Hennessy, B. T., Lu, Y., Mills, G. B., & Mukherjee, S. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts459 · Cited by 10

A novel strategy for dynamic modeling of genome-scale interaction networks

Borzou, P., Ghaisari, J., Izadi, I., Eshraghi, Y., & Gheisari, Y. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad079 · Cited by 9

Generalization of neural network models for complex network dynamics

Vasiliauskaitė, V., & Antulov-Fantulin, N. (2024) · Communications Physics · doi:10.1038/s42005-024-01837-w · Cited by 11

BioBERT based text mining for incorporating prior knowledge in the inference of genetic network models

Gill, J. K., Chetty, M., Lim, S., & Hallinan, J. S. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.109623 · Cited by 9

A New Approach to Link Prediction in Gene Regulatory Networks

Turki, T., & Wang, J. T. L. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24834-9_47 · Cited by 9

A Petri-Net-Based Framework for Biomodel Engineering

Blätke, M. A., Röhr, C., Monika Heiner, A., & Marwan, W. (2014) · Modeling and simulation in science, engineering & technology · doi:10.1007/978-3-319-08437-4_6 · Cited by 9

On Sparsity as a Criterion in Reconstructing Biochemical Networks

Nordling, T. E. M., & Jacobsen, E. W. (2011) · IFAC Proceedings Volumes · doi:10.3182/20110828-6-it-1002.03499 · Cited by 9

Selection of negative examples in learning gene regulatory networks

Ceccarelli, M., & Cerulo, L. (2009) · IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW) · doi:10.1109/bibmw.2009.5332137 · Cited by 9

Genetic Network Inference Using Hierarchical Structure

Kimura, S., Tokuhisa, M., & Okada, M. (2016) · Frontiers in Physiology · doi:10.3389/fphys.2016.00057 · Cited by 9

Parallel Algorithms for Inferring Gene Regulatory Networks: A Review

Abbaszadeh, O., Khanteymoori, A., & Azarpeyvand, A. (2018) · Current Genomics · doi:10.2174/1389202919666180601081718 · Cited by 9

BayesPiles

Vogogias, A., Kennedy, J., Archambault, D., Bach, B., Smith, V. A., & Currant, H. (2018) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3230623 · Cited by 9

Identification of Minimum Set of Master Regulatory Genes in Gene Regulatory Networks

Bakhteh, S., Ghaffari-Hadigheh, ‎., & Chaparzadeh, N. (2018) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2018.2875692 · Cited by 9

Towards Human Cell Simulation

Spolaor, S., Gribaudo, M., Iacono, M., Kadavý, T., Oplatková, Z. K., Mauri, G., Sabri Pllana, A., Šenkeřík, R., Stojanovic, N. M., Turunen, E., et al. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-16272-6_8 · Cited by 9

Network Inference of Transcriptional Regulation in Germinating Low Phytic Acid Soybean Seeds

DeMers, L. C., Raboy, V., Li, S., & Maroof, M. A. S. (2021) · Frontiers in Plant Science · doi:10.3389/fpls.2021.708286 · Cited by 9

Analysis and Practical Guideline of Constraint-Based Boolean Method in Genetic Network Inference

Saithong, T., Bumee, S., Liamwirat, C., & Meechai, A. (2012) · PLoS ONE · doi:10.1371/journal.pone.0030232 · Cited by 9

Network inference using steady-state data and Goldbeter–Koshland kinetics

Oates, C. J., Hennessy, B. T., Lu, Y., Mills, G. B., & Mukherjee, S. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt057 · Cited by 9

From digital genetics to knowledge discovery: Perspectives in genetic network understanding

Beslon, G., Parsons, D. P., Peña, J.-M., Rigotti, C., & Sánchez-Dehesa, Y. (2010) · Intelligent Data Analysis · doi:10.3233/ida-2010-0415 · Cited by 9

Exploring candidate biological functions by Boolean Function Networks for Saccharomyces cerevisiae

Simak, M., Yeang, C., & Lu, H. H. (2017) · PLoS ONE · doi:10.1371/journal.pone.0185475 · Cited by 9

Bayesian Data Fusion of Gene Expression and Histone Modification Profiles for Inference of Gene Regulatory Network

Chen, H., Maduranga, D. A. K., Mundra, P. A., & Zheng, J. (2018) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2018.2869590 · Cited by 9

Dissecting and improving gene regulatory network inference using single-cell transcriptome dataPreprint

Xue, L., Wu, Y., & Lin, Y. (2023) · Genome Research · doi:10.1101/gr.277488.122 · Cited by 10

ViLoN—a multi-layer network approach to data integration demonstrated for patient stratification

Kańduła, M. M., Aldoshin, A. D., Singh, S., Kolaczyk, E. D., & Kreil, D. P. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac988 · Cited by 8

Discovering network dynamics with neural symbolic regression

Yu, Z., Ding, J., & Li, Y. (2025) · Nature Computational Science · doi:10.1038/s43588-025-00893-8 · Cited by 12

Modeling Signal Transduction from Protein Phosphorylation to Gene Expression

Cai, C., Chen, L., Jiang, X., & Lu, X. (2014) · Cancer Informatics · doi:10.4137/cin.s13883 · Cited by 8

Underpinning miRNA-miRNA co-functional interaction patterns in the metabolism of Oryza sativa by genome-scale network analysis

Banerjee, A. K., & Mal, C. (2020) · Heliyon · doi:10.1016/j.heliyon.2020.e05496 · Cited by 8

Inference of gene regulatory networks with the strong-inhibition Boolean model

Xia, Q., Liu, L., Ye, W., & Hu, G. (2011) · New Journal of Physics · doi:10.1088/1367-2630/13/8/083002 · Cited by 9

Systems Modeling at Multiple Levels of Regulation: Linking Systems and Genetic Networks to Spatially Explicit Plant Populations

Kitchen, J., & Allaby, R. G. (2013) · Plants · doi:10.3390/plants2010016 · Cited by 7

Regulatory network inferred using expression data of small sample size: application and validation in erythroid system

Zhu, F., Shi, L., Engel, J. D., & Guan, Y. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv186 · Cited by 8

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Kuzmanovski, V., Todorovski, L., & Džeroski, S. (2018) · GigaScience · doi:10.1093/gigascience/giy118 · Cited by 8

Characterization of Peroxisomal Regulation Networks

Mast, F. D., & Aitchison, J. D. (2018) · Sub-cellular biochemistry/Subcellular biochemistry · doi:10.1007/978-981-13-2233-4_16 · Cited by 8

Network Modeling and Inference of Peroxisome Proliferator-Activated Receptor Pathway in High fat diet-linked Obesity

Vundavilli, H., Tripathi, L. P., Datta, A. A., & Mizuguchi, K. (2020) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2021.110647 · Cited by 8

Mathematical Modelling of Gene Regulatory Networks

Tuek, A., & Kurtanjek, E. (2012) · InTech eBooks · doi:10.5772/31388 · Cited by 8

A Multi-GPU Hitting Set Algorithm for GRNs Inference

Carastan‐Santos, D., Camargo, R. Y. D., Martins, D., Song, S. W., Rozante, L. C. S., & Borelli, F. (2015) · IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) · doi:10.1109/ccgrid.2015.29 · Cited by 8

Reconstruction of Large-Scale Gene Regulatory Networks Using Bayesian Model Averaging

Kim, H., & Erol Gelenbe, A. (2011) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm.2011.95 · Cited by 8

Gene Network Biological Validity Based on Gene-Gene Interaction Relevance

Gómez-Vela, F., & Díaz–Díaz, N. (2014) · The Scientific World JOURNAL · doi:10.1155/2014/540679 · Cited by 8

MoCha: Molecular Characterization of Unknown Pathways

Lobo, D., Hammelman, J., & Levin, M. G. (2016) · Journal of Computational Biology · doi:10.1089/cmb.2015.0211 · Cited by 9

A supervised weighted similarity measure for gene expressions using biological knowledge

Ray, S. S., & Misra, S. (2016) · Gene · doi:10.1016/j.gene.2016.09.033 · Cited by 8

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Gómez-Vela, F., López, A. L., Lagares, J. A., Rodríguez–Baena, D. S., Barranco, C. D., García-Torres, M., & Divina, F. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-56154-7_32 · Cited by 8

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Mouresan, E. F., Selle, M. L., & Rönnegård, L. (2019) · G3 Genes Genomes Genetics · doi:10.1534/g3.119.400381 · Cited by 9

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Karamveer, K., & Uzun, Y. (2024) · Bioinformatics and Biology Insights · doi:10.1177/11779322241287120 · Cited by 9

GFD-Net: A novel semantic similarity methodology for the analysis of gene networks

Díaz–Montaña, J. J., Díaz–Díaz, N., & Gómez-Vela, F. (2017) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2017.02.013 · Cited by 7

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Gómez-Vela, F., Delgado-Chaves, F. M., Rodríguez–Baena, D. S., García-Torres, M., & Divina, F. (2019) · Entropy · doi:10.3390/e21121139 · Cited by 7

A Bayesian data fusion based approach for learning genome-wide transcriptional regulatory networks

Sauta, E., Demartini, A., Vitali, F., Riva, A., & Bellazzi, R. (2020) · BMC Bioinformatics · doi:10.1186/s12859-020-3510-1 · Cited by 7

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Bazzan, J., Echeveste, M. E. S., Formoso, C. T., & Kowalski, J. D. S. (2024) · Architectural Engineering and Design Management · doi:10.1080/17452007.2024.2306847 · Cited by 7

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Tan, S., Zhou, R., Wang, Y., Liu, Q., & Liu, X. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.124014 · Cited by 7

LogicGep: Boolean networks inference using symbolic regression from time-series transcriptomic profiling data

Zhang, D., Gao, S., Liu, Z., & Gao, R. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae286 · Cited by 7

KEGNI: knowledge graph enhanced framework for gene regulatory network inference

Li, P., Li, L., Nan, J., Chen, J., Sun, J., & Cao, Y. (2025) · Genome biology · doi:10.1186/s13059-025-03780-7 · Cited by 7

The evolution of higher-level biochemical reaction models

Ross, B. J. (2011) · Genetic Programming and Evolvable Machines · doi:10.1007/s10710-011-9144-3 · Cited by 7

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Guthke, R., Gerber, S., Conrad, T., Vlaic, S., Durmuş, S., Çakır, T., Sevilgen, F. E., Shelest, E., & Linde, J. (2016) · Frontiers in Microbiology · doi:10.3389/fmicb.2016.00570 · Cited by 7

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Pataskar, A., & Tiwari, V. K. (2016) · Transcription · doi:10.1080/21541264.2016.1204491 · Cited by 7

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Zhang, L., Wu, H. C., Ho, C. H., & Chan, S. C. (2018) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2018.2828810 · Cited by 8

Towards precise reconstruction of gene regulatory networks by data integration

Liu, Z. (2018) · Quantitative Biology · doi:10.1007/s40484-018-0139-4 · Cited by 8

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