Bioinformatics applied to gene transcription regulation
- Department of Endocrinology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
- (Correspondence should be addressed to G Altobelli; Email: g.altobelli{at}qmul.ac.uk)
Abstract
Understanding regulation of gene transcription is central to molecular biology as well as being of great interest in medicine. The molecular syntax of the concerted transcriptional activation/repression of gene networks in mammal cells, which shape the physiological response to the molecular signals, is often unknown or not completely understood. Combining genome-wide experiments with in silico approaches opens the way to a more systematic comprehension of the molecular mechanisms of transcription regulation. Diverse bioinformatics tools have been developed to help unravel these mechanisms, by handling and processing data at different stages: from data collection and storage to the identification of molecular targets and from the detection of DNA motif signatures in the regulatory sequences of functionally related genes to the identification of relevant regulatory networks. Moreover, the large amount of genome-wide scale data recently produced has attracted professionals from diverse backgrounds to this cutting-edge realm of molecular biology. This mini-review is intended as an orientation for multidisciplinary professionals, introducing a streamlined workflow in gene transcription regulation with emphasis on sequence analysis. It provides an outlook on tools and methods, selected from a host of bioinformatics resources available today. It has been designed for the benefit of students, investigators, and professionals who seek a coherent yet quick introduction to in silico approaches to analyzing regulation of gene transcription in the post-genomic era.
- Revision received 15 June 2012
- Accepted 21 June 2012
- Made available online as an Accepted Preprint 21 June 2012
- © 2012 Society for Endocrinology