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Comparative Genomics Approaches to Identifying Functionally Related Genes

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Algorithms for Computational Biology (AlCoB 2014)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 8542))

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Abstract

The rapid progress in genome sequencing makes it possible to address fundamental problems of biology and achieve critical insights into the functioning of the live cells and entire organisms. However, the widening gap between the rapidly accumulating sequence data and our ability to properly annotate these data constitutes a major problem that slows down the progress of genome biology. This paper discusses the notion of “function” as it relates to computational biology, lists the most common ways of assigning function to the new genes, particularly those that specifically rely on comparative genome analysis, and briefly reviews the drawbacks of the current algorithms for semi-automated high-throughput functional annotation of genomes.

The article is a work of the United States Government; Title 17 U.S.C 105 provides that copyright protection is not available for any work of the United States government in the United States.

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  1. National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA

    Michael Y. Galperin & Eugene V. Koonin

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  1. Michael Y. Galperin
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  2. Eugene V. Koonin
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  1. Research Group on Mathematical Linguistics, Rovira i Virgili University, Avinguda Catalunya, 35, 43002, Tarragona, Spain

    Adrian-Horia Dediu  & Carlos Martín-Vide  & 

  2. Fachbereich 07, Institut für Informatik, Justus-Liebig-Universität, Arndtstraße 2, 35392, Gießen, Germany

    Bianca Truthe

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Galperin, M.Y., Koonin, E.V. (2014). Comparative Genomics Approaches to Identifying Functionally Related Genes. In: Dediu, AH., Martín-Vide, C., Truthe, B. (eds) Algorithms for Computational Biology. AlCoB 2014. Lecture Notes in Computer Science(), vol 8542. Springer, Cham. https://doi.org/10.1007/978-3-319-07953-0_1

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