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BMCBI
2005
89views more  BMCBI 2005»
15 years 5 months ago
An empirical analysis of training protocols for probabilistic gene finders
Background: Generalized hidden Markov models (GHMMs) appear to be approaching acceptance as a de facto standard for state-of-the-art ab initio gene finding, as evidenced by the re...
William H. Majoros, Steven Salzberg
BMCBI
2005
196views more  BMCBI 2005»
15 years 5 months ago
Chemistry in Bioinformatics
Chemical information is now seen as critical for most areas of life sciences. But unlike Bioinformatics, where data is Openly available and freely re-usable, most chemical informa...
Peter Murray-Rust, John B. O. Mitchell, Henry S. R...
BMCBI
2005
106views more  BMCBI 2005»
15 years 5 months ago
SIMPROT: Using an empirically determined indel distribution in simulations of protein evolution
Background: General protein evolution models help determine the baseline expectations for the evolution of sequences, and they have been extensively useful in sequence analysis an...
Andy Pang, Andrew D. Smith, Paulo A. S. Nuin, Elis...
BMCBI
2005
100views more  BMCBI 2005»
15 years 5 months ago
Evolutionary models for insertions and deletions in a probabilistic modeling framework
Background: Probabilistic models for sequence comparison (such as hidden Markov models and pair hidden Markov models for proteins and mRNAs, or their context-free grammar counterp...
Elena Rivas
BMCBI
2005
97views more  BMCBI 2005»
15 years 5 months ago
Phylogenetic reconstruction of ancestral character states for gene expression and mRNA splicing data
Background: As genomes evolve after speciation, gene content, coding sequence, gene expression, and splicing all diverge with time from ancestors with close relatives. A minimum e...
Roald Rossnes, Ingvar Eidhammer, David A. Liberles
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