ArticlePloS one2009
Incorporating existing network information into gene network inference.
Article in PloS one, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Optimizing data integration improves gene regulatory network inference in Arabidopsis thaliana.Bioinformatics (Oxford, England) · 2024Article
- CoVar: A generalizable machine learning approach to identify the coordinated regulators driving variational gene expression.PLoS computational biology · 2024Article
- Network reconstruction for trans acting genetic loci using multi-omics data and prior information.Genome medicine · 2022Article
- RSNET: inferring gene regulatory networks by a redundancy silencing and network enhancement technique.BMC bioinformatics · 2022Article
- Differential regulatory network-based quantification and prioritization of key genes underlying cancer drug resistance based on time-course RNA-seq data.PLoS computational biology · 2019Article
- Primary visual cortex shows laminar-specific and balanced circuit organization of excitatory and inhibitory synaptic connectivity.The Journal of physiology · 2016Article
- Gene Network Reconstruction by Integration of Prior Biological Knowledge.G3 (Bethesda, Md.) · 2015Article
- Inferring dynamic gene regulatory networks in cardiac differentiation through the integration of multi-dimensional data.BMC bioinformatics · 2015Article
- Computational Studies of the Intestinal Host-Microbiota Interactome.Computation (Basel, Switzerland) · 2015Article
- Reconstruction of composite regulator-target splicing networks from high-throughput transcriptome data.BMC genomics · 2015Article
- Functional association networks as priors for gene regulatory network inference.Bioinformatics (Oxford, England) · 2014Article
- Inference of the Xenopus tropicalis embryonic regulatory network and spatial gene expression patterns.BMC systems biology · 2014Article
- Artificial neural network inference (ANNI): a study on gene-gene interaction for biomarkers in childhood sarcomas.PloS one · 2014Article
- Gene regulatory network inference by point-based Gaussian approximation filters incorporating the prior information.EURASIP journal on bioinformatics & systems biology · 2013Article
- Construction of the influenza A virus infection-induced cell-specific inflammatory regulatory network based on mutual information and optimization.BMC systems biology · 2013Article
- Reverse-engineering the genetic circuitry of a cancer cell with predicted intervention in chronic lymphocytic leukemia.Proceedings of the National Academy of Sciences of the United States of America · 2013Article
- Article
- Integration of steady-state and temporal gene expression data for the inference of gene regulatory networks.PloS one · 2013Article
- Integrated inference and analysis of regulatory networks from multi-level measurements.Methods in cell biology · 2012Review
- Network quantitative trait loci mapping of circadian clock outputs identifies metabolic pathway-to-clock linkages in Arabidopsis.The Plant cell · 2011Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
One methodology that has met success to infer gene networks from gene expression data is based upon ordinary differential equations (ODE). However new types of data continue to be produced, so it is worthwhile to investigate how to integrate these new data types into the inference procedure. One such data is physical interactions between transcription factors and the genes they regulate as measured by ChIP-chip or ChIP-seq experiments. These interactions can be incorporated into the gene network inference procedure as a priori network information. In this article, we extend the ODE methodology into a general optimization framework that incorporates existing network information in combination with regularization parameters that encourage network sparsity. We provide theoretical results proving convergence of the estimator for our method and show the corresponding probabilistic interpretation also converges. We demonstrate our method on simulated network data and show that existing network information improves performance, overcomes the lack of observations, and performs well even when some of the existing network information is incorrect. We further apply our method to the core regulatory network of embryonic stem cells utilizing predicted interactions from two studies as existing network information. We show that including the prior network information constructs a more closely representative regulatory network versus when no information is provided.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.