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Modulefinder: a tool for computational discovery of cis regulatory modules
Anthony A Philippakis1, Fangxue Sherry He, Martha L Bulyk
1Division of Genetics, Department of Medicine, Brigham & Women's Hospital Boston, MA 02115, USA. aphilippakis@receptor.med.harvard.edu
Summary
ModuleFinder identifies cis regulatory modules (CRMs) by analyzing transcription factor binding sites. This computational tool accurately detects CRMs using sequence clustering and evolutionary conservation, enhancing gene regulation studies.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Gene expression regulation is crucial for cellular function.
- Transcription factors (TFs) bind to specific genomic sites to control gene expression.
- Identifying cis regulatory modules (CRMs) is key to understanding gene regulation.
Purpose of the Study:
- To develop a computational tool, ModuleFinder, for identifying cis regulatory modules (CRMs).
- To evaluate CRMs based on transcription factor binding site (TFBS) clustering and evolutionary conservation.
- To provide a training-free method for CRM prediction.
Main Methods:
- ModuleFinder, a C program, implements a scoring scheme for CRM identification.
- The scheme assesses homotypic and heterotypic TFBS clustering.
- Evolutionary conservation across multiple genomes is also evaluated.
Main Results:
- ModuleFinder utilizes input sequences and TFBS motifs to derive scoring parameters.
- The tool demonstrated high sensitivity and specificity in identifying known CRMs.
- Validation datasets from mammals and flies confirmed ModuleFinder's accuracy.
Conclusions:
- ModuleFinder offers a robust and accurate method for predicting CRMs.
- The tool's ability to integrate clustering and conservation enhances CRM discovery.
- This approach advances the study of gene regulation and TF binding.