A survey on algorithms to characterize transcription factor binding sites

Author:

Tognon Manuel123,Giugno Rosalba1,Pinello Luca234

Affiliation:

1. Computer Science Department, University of Verona , Verona, Italy

2. Molecular Pathology Unit, Center for Computational and Integrative Biology and Center for Cancer Research, Massachusetts General Hospital , Charlestown, Massachusetts , United States of America

3. Broad Institute of MIT and Harvard , Cambridge, Massachusetts , United States of America

4. Department of Pathology, Harvard Medical School , Boston, Massachusetts , United States of America

Abstract

Abstract Transcription factors (TFs) are key regulatory proteins that control the transcriptional rate of cells by binding short DNA sequences called transcription factor binding sites (TFBS) or motifs. Identifying and characterizing TFBS is fundamental to understanding the regulatory mechanisms governing the transcriptional state of cells. During the last decades, several experimental methods have been developed to recover DNA sequences containing TFBS. In parallel, computational methods have been proposed to discover and identify TFBS motifs based on these DNA sequences. This is one of the most widely investigated problems in bioinformatics and is referred to as the motif discovery problem. In this manuscript, we review classical and novel experimental and computational methods developed to discover and characterize TFBS motifs in DNA sequences, highlighting their advantages and drawbacks. We also discuss open challenges and future perspectives that could fill the remaining gaps in the field.

Funder

Horizon 2020

National Human Genome Research Institute

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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