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Phylogenetic Analysis of Protein Family

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Fungal Genomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1775))

Abstract

With the number of sequenced genomes increasing rapidly, it is impractical to perform functional and structural analyses on all individual proteins. Phylogenetic analysis employs a combination of molecular and statistical approaches to infer or estimate relationships among individuals. It provides a credible method to explore the relationship between sequence similarity and function of proteins belonging to the same family. This chapter describes a standardized framework of phylogenetic analysis to study large protein families. Bioinformatic approaches and online tools used in phylogenetic analyses are presented.

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Author information

Authors and Affiliations

  1. Centre for Structural and Functional Genomics, Concordia University, 7141 Sherbrooke Street West, Montreal, H4B 1R6, Quebec, Canada

    Letian Song & Sherry Wu

  2. Centre for Structural and Functional Genomics, Concordia University, Montreal, QC, Canada

    Adrian Tsang

Authors
  1. Letian Song
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  2. Sherry Wu
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  3. Adrian Tsang
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Corresponding author

Correspondence to Letian Song .

Editor information

Editors and Affiliations

  1. Fungal Physiology, Westerdijk Fungal, Biodiversity Institute, Utrecht, The Netherlands

    Ronald P. de Vries

  2. Centre for Structural and Functional Genomics, Concordia University, Montreal, Québec, Canada

    Adrian Tsang

  3. US Department of Energy, Joint Genome Institute, Walnut Creek, California, USA

    Igor V. Grigoriev

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© 2018 Springer Science+Business Media, LLC, part of Springer Nature

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Song, L., Wu, S., Tsang, A. (2018). Phylogenetic Analysis of Protein Family. In: de Vries, R., Tsang, A., Grigoriev, I. (eds) Fungal Genomics. Methods in Molecular Biology, vol 1775. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7804-5_21

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  • DOI: https://doi.org/10.1007/978-1-4939-7804-5_21

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7803-8

  • Online ISBN: 978-1-4939-7804-5

  • eBook Packages: Springer Protocols

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