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Hidden Markov ProcessesTheory and Applications to Biology$
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M. Vidyasagar

Print publication date: 2014

Print ISBN-13: 9780691133157

Published to Princeton Scholarship Online: October 2017

DOI: 10.23943/princeton/9780691133157.001.0001

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Blast Theory

Blast Theory

Chapter:
(p.255) Chapter Nine Blast Theory
Source:
Hidden Markov Processes
Author(s):

M. Vidyasagar

Publisher:
Princeton University Press
DOI:10.23943/princeton/9780691133157.003.0009

This chapter deals with BLAST theory. BLAST (Basic Local Alignment Search Tool) is a widely used statistical method for finding similarities between sequences of symbols from finite alphabets. While the theory is completely general, the most widely used applications are to comparing sequences of nucleotides and sequences of amino acids. The fundamental objective of BLAST theory is to align sequences as well as possible, and then make a determination as to the level of statistical significance of the alignment. Thus one computes a “maximal segmental score” of the alignment between the two sequences, and tests to see whether the maximal segmental score could have been obtained purely as a matter of chance. The chapter presents the main results of BLAST theory, focusing on the moment generating function and application of the results. It also presents the proofs of the main results.

Keywords:   moment generating function, BLAST theory, sequence, finite alphabet, nucleotide, amino acids, alignment, maximal segmental score

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