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In silico Identification of Eukaryotic Promoters

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Systems and Synthetic Biology

Abstract

The identification of promoters is essential for complete annotation of genomes and better understanding of gene regulatory networks. Experimental methods for promoter identification are costly, time-consuming and labor intensive. Hence, in silico methods are an attractive alternative. Computational methods for promoter prediction methods are easy, fast and can provide reliable results. A promoter prediction algorithm identifies promoter regions based on the idea that, promoter regions are different from other genomic regions in their features (sequence, context and structure). Promoter prediction algorithms are broadly classified as ab initio, hybrid and homology-based, depending on the information used for model design. The different approaches used in promoter prediction are briefly described here.

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Acknowledgement

MB is a recipient of the J. C. Bose National Fellowship of DST, India. We thank Rajasekaran for assistance in the preparation of Fig. 4.1.

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Authors and Affiliations

  1. Molecular Biophysics Unit, Indian Institute of Science, Bengaluru, Karnataka, India

    Venkata Rajesh Yella & Manju Bansal

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  1. Venkata Rajesh Yella
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  2. Manju Bansal
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Correspondence to Manju Bansal .

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Editors and Affiliations

  1. Centre for Computational Biology and Bioinformatics, Central University of Himachal Pradesh, Dharamshala, India

    Vikram Singh

  2. Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Gautam Budh Nagar, India

    Pawan K. Dhar

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Yella, V., Bansal, M. (2015). In silico Identification of Eukaryotic Promoters. In: Singh, V., Dhar, P. (eds) Systems and Synthetic Biology. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9514-2_4

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