Pattern recognition in genetic sequences by mismatch density

DOI10.1007/BF02459499zbMath0584.92009OpenAlexW4236413252MaRDI QIDQ1070960

Peter H. Sellers

Publication date: 1984

Published in: Bulletin of Mathematical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02459499

zbMATH Keywords

algorithmdynamic programmingalignmentexamplesdegree of similaritygenetic sequencespattern similaritydegree of mismatch

Mathematics Subject Classification ID

Genetics and epigenetics (92D10) Computational methods for problems pertaining to biology (92-08)

Related Items (9)

Efficient algorithms for locating the length-constrained heaviest segments with applications to biomolecular sequence analysis. ⋮ A nonlinear measure of subalignment similarity and its significance levels ⋮ Locally optimal subalignments using nonlinear similarity functions ⋮ Significance levels for biological sequence comparison using non-linear similarity functions ⋮ Linear-space algorithms that build local alignments from fragments ⋮ Approximate matching of regular expressions ⋮ A time-efficient, linar-space local similarity algorithm ⋮ Linear-time algorithms for computing maximum-density sequence segments with bioinformatics applications ⋮ Approximate periods of strings

Cites Work

• An extreme value theory for long head runs
• An algorithm for the distance between two finite sequences
• The theory and computation of evolutionary distances: Pattern recognition
• On the Theory and Computation of Evolutionary Distances

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