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RECOMB
2003
Springer
9 years 8 months ago
Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals
We propose a framework for modeling sequence motifs based on the maximum entropy principle (MEP). We recommend approximating short sequence motif distributions with the maximum en...
Gene W. Yeo, Christopher B. Burge
BMCBI
2006
75views more  BMCBI 2006»
8 years 8 months ago
A machine learning strategy to identify candidate binding sites in human protein-coding sequence
Background: The splicing of RNA transcripts is thought to be partly promoted and regulated by sequences embedded within exons. Known sequences include binding sites for SR protein...
Thomas Down, Bernard Leong, Tim J. P. Hubbard
BMCBI
2006
116views more  BMCBI 2006»
8 years 8 months ago
Optimized mixed Markov models for motif identification
Background: Identifying functional elements, such as transcriptional factor binding sites, is a fundamental step in reconstructing gene regulatory networks and remains a challengi...
Weichun Huang, David M. Umbach, Uwe Ohler, Leping ...
BMCBI
2010
152views more  BMCBI 2010»
8 years 8 months ago
Apples and oranges: avoiding different priors in Bayesian DNA sequence analysis
Background: One of the challenges of bioinformatics remains the recognition of short signal sequences in genomic DNA such as donor or acceptor splice sites, splicing enhancers or ...
Jens Keilwagen, Jan Grau, Stefan Posch, Ivo Grosse
BMCBI
2010
113views more  BMCBI 2010»
8 years 8 months ago
Unifying generative and discriminative learning principles
Background: The recognition of functional binding sites in genomic DNA remains one of the fundamental challenges of genome research. During the last decades, a plethora of differe...
Jens Keilwagen, Jan Grau, Stefan Posch, Marc Stric...
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