Abstract
With the increase in huge amount of biological sequence data from large genome and proteome sequencing projects, efforts have been made to develop computational algorithms and databases to manage the information. This chapter is an attempt to highlight some of the commonly used algorithms for the biological sequence analysis ranging from pairwise sequence analysis, multiple sequence analysis, phylogenetic analysis, and prediction of the probability of a desired motif in the sequence. The chapter is organized in the form of basic questions that arise in the researchers’ mind and their step-by-step solution using important algorithms and statistical methods. The examples are used and elaborated in such a way that the algorithms can be easily understood by students with nonmathematical and nonstatistical background.
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Smita, S., Singh, K.P., Akhoon, B.A., Gupta, S.K. (2013). Biological Sequence Analysis: Algorithms and Statistical Methods. In: Arora, D., Das, S., Sukumar, M. (eds) Analyzing Microbes. Springer Protocols Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34410-7_20
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DOI: https://doi.org/10.1007/978-3-642-34410-7_20
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34409-1
Online ISBN: 978-3-642-34410-7
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