Hidden markov models for bioinformatics

Hidden markov models for bioinformatics

by Koski, T.

Type Book
Rate 0.0 /5

Perequisites in probability calculus. Information and the kullback distance. Probabilistic models and learning. EM algorithm. Alignment and scoring. Mixture models and profiles. Markov chains. learning of markov chains. Markovian models for DNA sequences. Hidden markov models: an overview. HMM for DNA sequences. Left to right HMM for sequences. Derin's algorithm. Forward-backward algorithm. baum-welch learning algorithm. limit points of baum-welch. Asymptotics of learning. Full probabilistic HM…

Read More ↓
Details
Files
Reviews
Download

Title Statements

  • Full title :Hidden markov models for bioinformatics.

Summary

Perequisites in probability calculus. Information and the kullback distance. Probabilistic models and learning. EM algorithm. Alignment and scoring. Mixture models and profiles. Markov chains. learning of markov chains. Markovian models for DNA sequences. Hidden markov models: an overview. HMM for DNA sequences. Left to right HMM for sequences. Derin's algorithm. Forward-backward algorithm. baum-welch learning algorithm. limit points of baum-welch. Asymptotics of learning. Full probabilistic HMM. Index.

Read More ↓

Edition Statements

  • Publication Date:2001.

Publication Statements

  • Publisher(s):Kluwer
  • Place of Publication:Dordrecht
  • Language:eng
  • Publication Date:2001.

The Physical Object

  • Description:391 p.

Edition Identifiers

  • ISBN:1402001355, 9781402001352
  • oclc:ocn693445597
  • Dewey Decimal:570.285

Subjects

Bioinformàtica Estatistica matematica Modelos de Markov

Writers

Koski, T.

Rate & Review

0.0/5
(0 people Voted)

No reviews yet. Be the first to rate this work.

Files & Downloads

  • Hidden Markov models for bioinformatics -- (.pdf)

    PDF · 11.7 MB · updated
    Login →
Log in to request a copy