Optimal Amnesic Probabilistic Automata or How to Learn and Classify Proteins in Linear Time and Space-Reference-Cited by-同舟云学术

Optimal Amnesic Probabilistic Automata or How to Learn and Classify Proteins in Linear Time and Space

Published:2000-08 Issue:3-4 Volume:7 Page:381-393
ISSN:1066-5277
Container-title:Journal of Computational Biology
language:en
Short-container-title:Journal of Computational Biology

Author:

Apostolico Alberto¹,Bejerano Gill²

Affiliation:

1. Department of Computer Sciences, Purdue University, West Lafayette, IN 47907 and Dipartimento di Elettronica e Informatica, Università di Padova, Padova, Italy.

2. School of Computer Science and Engineering, The Hebrew University, Jerusalem 91904, Israel.

Publisher

Mary Ann Liebert Inc

Subject

Computational Theory and Mathematics,Computational Mathematics,Genetics,Molecular Biology,Modeling and Simulation

Link

http://www.liebertpub.com/doi/pdf/10.1089/106652700750050844

Reference16 articles.

1. On the computational complexity of approximating distributions by probabilistic automata

2. Efficient string matching

3. Optimal amnesic probabilistic automata or how to learn and classify proteins in linear time and space

4. Efficient Detection of Unusual Words

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