ArticlePloS one2008
A visual data mining tool that facilitates reconstruction of transcription regulatory networks.
Article in PloS one, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Exploiting plant transcriptomic databases: Resources, tools, and approaches.Plant communications · 2022Review
- Phenotypic and molecular convergence of 2q23.1 deletion syndrome with other neurodevelopmental syndromes associated with autism spectrum disorder.International journal of molecular sciences · 2015Article
- ImmuCo: a database of gene co-expression in immune cells.Nucleic acids research · 2015Article
- Comprehensive literature review and statistical considerations for microarray meta-analysis.Nucleic acids research · 2012Review
- Managing biological complexity across orthologs with a visual knowledgebase of documented biomolecular interactions.Scientific reports · 2012Article
- Article
- Systematic analysis of gene expression differences between left and right atria in different mouse strains and in human atrial tissue.PloS one · 2011Article
- Classification of genes and putative biomarker identification using distribution metrics on expression profiles.PloS one · 2010Article
- The use of neuroproteomics in drug abuse research.Drug and alcohol dependence · 2010Review
- Assembly of an interactive correlation network for the Arabidopsis genome using a novel heuristic clustering algorithm.Plant physiology · 2010Article
- STARNET 2: a web-based tool for accelerating discovery of gene regulatory networks using microarray co-expression data.BMC bioinformatics · 2009Article
- Cardiac metabolism and arrhythmias.Circulation. Arrhythmia and electrophysiology · 2009Review
- Microarray retriever: a web-based tool for searching and large scale retrieval of public microarray data.Nucleic acids research · 2008Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAlthough the use of microarray technology has seen exponential growth, analysis of microarray data remains a challenge to many investigators. One difficulty lies in the interpretation of a list of differentially expressed genes, or in how to plan new experiments given that knowledge. Clustering methods can be used to identify groups of genes with similar expression patterns, and genes with unknown function can be provisionally annotated based on the concept of "guilt by association", where function is tentatively inferred from the known functions of genes with similar expression patterns. These methods frequently suffer from two limitations: (1) visualization usually only gives access to group membership, rather than specific information about nearest neighbors, and (2) the resolution or quality of the relationships are not easily inferred. METHODOLOGY/PRINCIPAL
findingsWe have addressed these issues by improving the precision of similarity detection over that of a single experiment and by creating a tool to visualize tractable association networks: we (1) performed meta-analysis computation of correlation coefficients for all gene pairs in a heterogeneous data set collected from 2,145 publicly available micorarray samples in mouse, (2) filtered the resulting distribution of over 130 million correlation coefficients to build new, more tractable distributions from the strongest correlations, and (3) designed and implemented a new Web based tool (StarNet, http://vanburenlab.medicine.tamhsc.edu/starnet.html) for visualization of sub-networks of the correlation coefficients built according to user specified parameters. CONCLUSIONS/SIGNIFICANCE: Correlations were calculated across a heterogeneous collection of publicly available microarray data. Users can access this analysis using a new freely available Web-based application for visualizing tractable correlation networks that are flexibly specified by the user. This new resource enables rapid hypothesis development for transcription regulatory relationships.
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