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Protein Homology Detection Through Alignment of Markov Random Fields pp 1–16Cite as

Introduction

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Abstract

This chapter describes background and surveys existing popular methods on homology detection and fold recognition. In particular, this chapter reviews homology detection methods from the following perspectives: alignment-free versus alignment-based, sequence-based versus profile-based, and generative versus discriminative machine learning. Finally, this chapter also reviews a few popular scoring functions for sequence-based or profile-based protein alignment.

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Authors and Affiliations

  1. Toyota Technological Institute, Chicago, IL, USA

    Jinbo Xu, Sheng Wang & Jianzhu Ma

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  1. Jinbo Xu
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  2. Sheng Wang
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  3. Jianzhu Ma
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Correspondence to Jinbo Xu .

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Xu, J., Wang, S., Ma, J. (2015). Introduction. In: Protein Homology Detection Through Alignment of Markov Random Fields. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-14914-1_1

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  • DOI: https://doi.org/10.1007/978-3-319-14914-1_1

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-14914-1

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