TF-finder: a software package for identifying transcription factors involved in biological processes using microarray...

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Identifying transcription factors (TFs) is crucial for understanding biological regulation.
• Current methods face challenges due to complex gene networks and numerous TFs.
• Novel TF discovery methods are needed, especially those leveraging existing biological knowledge.

Purpose of the Study:

• To develop an automated software package, TF-finder, for recognizing TFs involved in specific biological processes.
• To utilize microarray data and existing knowledge bases for TF identification.
• To improve the efficiency and accuracy of novel TF discovery.

Main Methods:

• Developed TF-finder, an automated software package.
• Incorporated adaptive sparse canonical correlation analysis (ASCCA) to identify TFs using positive target genes.
• Implemented an enrichment test to validate identified TFs.

Main Results:

• TF-finder successfully identified key TFs in salt and drought tolerance using microarray data.
• The tool rediscovered experimentally validated TFs, demonstrating its efficacy.
• TF-finder showed superior performance in recognizing novel TFs compared to the Intersection of Coexpression (ICE) method.

Conclusions:

• TF-finder effectively infers novel TFs involved in biological processes.
• The software package leverages publicly available gene expression data and known positive genes.
• TF-finder offers a valuable tool for advancing our understanding of gene regulation.