ArticleBioinformatics (Oxford, England)2012
Utilizing RNA-Seq data for de novo coexpression network inference.
Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers.
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Who cites it
75 citing papers in PubMed.
- Modeling Brain Gene Expression in Alcohol Use Disorder with Genetic Animal Models.Current topics in behavioral neurosciences · 2025Review
- VI-VS: calibrated identification of feature dependencies in single-cell multiomics.Genome biology · 2024Article
- CASPER: A Phase I trial combining calaspargase pegol-mnkl and cobimetinib in pancreatic cancer.Future oncology (London, England) · 2024Article
- MIGGRI: A multi-instance graph neural network model for inferring gene regulatory networks for Drosophila from spatial expression images.PLoS computational biology · 2023Article
- Improving gene regulatory network inference and assessment: The importance of using network structure.Frontiers in genetics · 2023Article
- Sex Differences in the Brain Transcriptome Related to Alcohol Effects and Alcohol Use Disorder.Biological psychiatry · 2022Review
- Sugar signal mediates flavonoid biosynthesis in tea leaves.Horticulture research · 2022Article
- Integrative Analysis of Next-Generation Sequencing for Next-Generation Cancer Research toward Artificial Intelligence.Cancers · 2021Review
- On the Use of Heterogeneous Stock Mice to Map Transcriptomes Associated With Excessive Ethanol Consumption.Frontiers in psychiatry · 2021Review
- Comparative Analyses of Gene Co-expression Networks: Implementations and Applications in the Study of Evolution.Frontiers in genetics · 2021Review
- Modern Approaches for Transcriptome Analyses in Plants.Advances in experimental medicine and biology · 2021Article
- A Novel Method to Identify the Differences Between Two Single Cell Groups at Single Gene, Gene Pair, and Gene Module Levels.Frontiers in genetics · 2021Article
- Article
- Functional gene networks reveal distinct mechanisms segregating in migraine families.Brain : a journal of neurology · 2020Article
- RNA-Seq Analysis of Genetic and Transcriptome Network Effects of Dual-Trait Selection for Ethanol Preference and Withdrawal Using SOT and NOT Genetic Models.Alcoholism, clinical and experimental research · 2020Article
- Brain regional gene expression network analysis identifies unique interactions between chronic ethanol exposure and consumption.PloS one · 2020Article
- Gene Coexpression Network and Module Analysis across 52 Human Tissues.BioMed research international · 2020Article
- Identifying genuine protein-protein interactions within communities of gene co-expression networks using a deconvolution method.IET systems biology · 2019Article
- Co-expression network analysis identifies gonad- and embryo-associated protein modules in the sentinel species Gammarus fossarum.Scientific reports · 2019Article
- Cross-species molecular dissection across alcohol behavioral domains.Alcohol (Fayetteville, N.Y.) · 2018Review
15 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
Abstract
motivationRNA-Seq experiments have shown great potential for transcriptome profiling. While sequencing increases the level of biological detail, integrative data analysis is also important. One avenue is the construction of coexpression networks. Because the capacity of RNA-Seq data for network construction has not been previously evaluated, we constructed a coexpression network using striatal samples, derived its network properties and compared it with microarray-based networks.
resultsThe RNA-Seq coexpression network displayed scale-free, hierarchical network structure. We detected transcripts groups (modules) with correlated profiles; modules overlap distinct ontology categories. Neuroanatomical data from the Allen Brain Atlas reveal several modules with spatial colocalization. The network was compared with microarray-derived networks; correlations from RNA-Seq data were higher, likely because greater sensitivity and dynamic range. Higher correlations result in higher network connectivity, heterogeneity and centrality. For transcripts present across platforms, network structure appeared largely preserved. From this study, we present the first RNA-Seq data de novo network inference.
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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.