SpringerProtocols: Abstract: From Promoter Analysis to Transcriptional Regulatory Network Prediction Using PAINT

From Promoter Analysis to Transcriptional Regulatory Network Prediction Using PAINT

By: Gregory E. Gonye², Praveen Chakravarthula², James S. Schwaber², Rajanikanth Vadigepalli²

Abstract

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Highly parallel gene-expression analysis has led to analysis of gene regulation, in particular coregulation, at a system level. Promoter analysis and interaction network toolset (PAINT) was developed to provide the biologist a computational tool to integrate functional genomics data, for example, from microarray-based gene-expression analysis with genomic sequence data to carry out transcriptional regulatory network analysis (TRNA). TRNA combines bioinformatics, used to identify and analyze gene-regulatory regions, and statistical significance testing, used to rank the likelihood of the involvement of individual transcription factors (TF), with visualization tools to identify TF likely to play a role in the cellular process under investigation. In summary, given a list of gene identifiers PAINT can: (1) fetch potential promoter sequences for the genes in the list, (2) find TF-binding sites on the sequences, (3) analyze the TF-binding site occurrences for over/underrepresentation compared with a reference, with or without coexpression clustering information, and (4) generate multiple visualizations for these analyses. At present, PAINT supports TRNA of the human, mouse, and rat genomes. PAINT is currently available as an online, web-based service located at: http://www.dbi.tju.edu/dbi/tools/paint.

Affiliation(s): (2) Thomas Jefferson University, Philadelphia, PA

Book Title: Gene Function Analysis

Series: Methods in Molecular Biology | Volume: 408 | Pub. Date: Aug-23-2007 | Page Range: 49-68 | DOI: 10.1007/978-1-59745-547-3_4

Subject: Genetics/Genomics

Key Words: Clustering - gene expression - gene regulation - network analysis - pattern recognition - transcription factors

References

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