Hidden Markov Models for Bioinformatics

Koski, Timo

ISBN 10: 1402001355 / ISBN 13: 9781402001352

Published by Kluwer Academic Publishers, 2001

About this Item

Gives a thorough and systematic introduction to probabilistic modeling in bioinformatics. This book contains a mathematically strict and extensive presentation of the kind of probabilistic models that have turned out to be useful in genome analysis. It also gives examples of known architectures (such as, profile HMM) used in genome analysis. Series: Computational Biology. Num Pages: 408 pages, biography. BIC Classification: PBT; PSAK. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 235 x 155 x 23. Weight in Grams: 758. . 2001. Hardback. . . . . Books ship from the US and Ireland.

Seller Inventory # V9781402001352

Bibliographic Details

• Title: Hidden Markov Models for Bioinformatics
• Publisher: Kluwer Academic Publishers
• Publication Date: 2001
• Language: English
• ISBN 10: 1402001355
• ISBN 13: 9781402001352
• Binding: Hardcover
• Condition: New

About this title

Synopsis

This text is based on a set of not es produced for courses given for gradu- ate students in mathematics, computer science and biochemistry during the academic year 1998-1999 at the University of Turku in Turku and at the Royal Institute of Technology (KTH) in Stockholm. The course in Turku was organized by Professor Mats Gyllenberg's groupl and was also included 2 within the postgraduate program ComBi, a Graduate School in Compu- tational Biology, Bioinformatics, and Biometry, directed by Professor Esko Ukkonen at the University of Helsinki. The purpose of the courses was to give a thorough and systematic intro duc ti on to probabilistic modelling in bioinformatics for advanced undergraduate and graduate students who had a fairly limited background in prob ability theory, but were otherwise well trained in mathematics and were already familiar with at least some of the techniques of algorithmic sequence analysis. Portions of the material have also been lectured at shorter graduate courses and seminars both in Finland and in Sweden. The initial set of notes circulated also for a time outside those two countries via the World Wide Web. The intermediate course in probability theory and techniques of discrete mathematics held by the author at the University College of Södertörn (Hud- dinge, Sweden) during the academic year 1997-1998 has also influenced the presentation. The opportunity to give this course is hereby gratefully ac- knowledged.