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Inferring Function from Homology

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Bioinformatics

Part of the book series: Methods in Molecular Biology™ ((MIMB,volume 453))

Abstract

Modern molecular biology approaches often result in the accumulation of abundant biological sequence data. Ideally, the function of individual proteins predicted using such data would be determined experimentally. However, if a gene of interest has no predictable function or if the amount of data is too large to experimentally assess individual genes, bioinformatics techniques may provide additional information to allow the inference of function.

This chapter proposes a pipeline of freely available Web-based tools to analyze protein-coding DNA sequences of unknown function. Accumulated information obtained during each step of the pipeline is used to build a testable hypothesis of function.

The basis and use of sequence similarity methods of homologue detection are described, with emphasis on BLAST and PSI-BLAST. Annotation of gene function through protein domain detection using SMART and Pfam, and the potential for comparison to whole genome data are discussed.

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Acknowledgments

Thanks to Pauline Maden and Caleb Webber for reading and commenting on the manuscript. This work was supported by a Medical Research Council UK Bioinformatics Fellowship (G90/112) to R.D.E.

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Authors and Affiliations

  1. Department of Biology, University College London, London, United Kingdom

    Richard D. Emes

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  1. Richard D. Emes
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Editors and Affiliations

  1. School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia

    Jonathan M. Keith PhD

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© 2008 Humana Press, a part of Springer Science+Business Media, LLC

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Emes, R.D. (2008). Inferring Function from Homology. In: Keith, J.M. (eds) Bioinformatics. Methods in Molecular Biology™, vol 453. Humana Press. https://doi.org/10.1007/978-1-60327-429-6_6

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  • DOI: https://doi.org/10.1007/978-1-60327-429-6_6

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-60327-428-9

  • Online ISBN: 978-1-60327-429-6

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