Maximum Entropy Modeling of Short Sequence Motifs with Applications to RNA Splicing Signals-Reference-Cited by-同舟云学术

Maximum Entropy Modeling of Short Sequence Motifs with Applications to RNA Splicing Signals

Published:2004-03 Issue:2-3 Volume:11 Page:377-394
ISSN:1066-5277
Container-title:Journal of Computational Biology
language:en
Short-container-title:Journal of Computational Biology

Author:

Yeo Gene¹,Burge Christopher B.²

Affiliation:

1. Department of Biology, Massachusetts Institute of Technology, 77 Massachusetts Avenue Building 68-223, Cambridge, MA 02319

2. Department of Brain and Cognitive Sciences, Center for Biological and Computational Learning, MassachusettsInstitute of Technology, Cambridge, MA 02319

Publisher

Mary Ann Liebert Inc

Subject

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

Link

http://www.liebertpub.com/doi/pdf/10.1089/1066527041410418

Reference26 articles.

1. Modeling splicing sites with pairwise correlations

2. A note on approximations to discrete probability distributions

3. Nucleotides of transcription factor binding sites exert interdependent effects on the binding affinities of transcription factors

4. Prediction of complete gene structures in human genomic DNA

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