Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks.
Genome Res. 2012.
PMID: 22456606
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Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks.
Genome Res. 2012 Jul;22(7):1334-49. doi: 10.1101/gr.127191.111. Epub 2012 Mar 28.
Genome Res. 2012.
PMID: 22456606
Free PMC article.
Applying these methods to Drosophila melanogaster, we predict 300,000 regulatory edges in a network of 600 TFs and 12,000 target genes. ...Last, we use the regulatory network to predict target gene expression levels as a function o …
Applying these methods to Drosophila melanogaster, we predict 300,000 regulatory edges in a network of 600 TFs a …
Transcription factor networks in Drosophila melanogaster.
Cell Rep. 2014 Sep 25;8(6):2031-2043. doi: 10.1016/j.celrep.2014.08.038. Epub 2014 Sep 18.
Cell Rep. 2014.
PMID: 25242320
Free PMC article.
Specific cellular fates and functions depend on differential gene expression, which occurs primarily at the transcriptional level and is controlled by complex regulatory networks of transcription factors (TFs). ...We probe this network in vivo, demonst …
Specific cellular fates and functions depend on differential gene expression, which occurs primarily at the transcriptional le …
Boolean modeling of biological regulatory networks: a methodology tutorial.
Methods. 2013 Jul 15;62(1):3-12. doi: 10.1016/j.ymeth.2012.10.012. Epub 2012 Nov 9.
Methods. 2013.
PMID: 23142247
In this paper, we present a tutorial on the fundamental steps of Boolean modeling of biological regulatory networks. We demonstrate how to infer a Boolean network model from the available experimental data, analyze the network using graph-theore …
In this paper, we present a tutorial on the fundamental steps of Boolean modeling of biological regulatory networks. We …
Quantitative model analysis with diverse biological data: applications in developmental pattern formation.
Methods. 2013 Jul 15;62(1):56-67. doi: 10.1016/j.ymeth.2013.03.024. Epub 2013 Apr 2.
Methods. 2013.
PMID: 23557990
Review.
Mathematical modeling of transcription factor and signaling networks is widely used to understand if and how a mechanism works, and to infer regulatory interactions that produce a model consistent with the observed data. ...To bridge the mode …
Mathematical modeling of transcription factor and signaling networks is widely used to understand if and how a mechanism works …
Enhancing gene regulatory network inference through data integration with markov random fields.
Sci Rep. 2017 Feb 1;7:41174. doi: 10.1038/srep41174.
Sci Rep. 2017.
PMID: 28145456
Free PMC article.
Much progress has been made in deciphering gene regulatory networks computationally. However, gene regulatory network inference for most eukaryotic organisms remain challenging. ...We show GRACE's potential to produce high confidence r …
Much progress has been made in deciphering gene regulatory networks computationally. However, gene regulatory …
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