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» Maximum entropy methods for biological sequence modeling
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EMNLP
2004
13 years 11 months ago
Comparing and Combining Generative and Posterior Probability Models: Some Advances in Sentence Boundary Detection in Speech
We compare and contrast two different models for detecting sentence-like units in continuous speech. The first approach uses hidden Markov sequence models based on N-grams and max...
Yang Liu, Andreas Stolcke, Elizabeth Shriberg, Mar...
ISMB
1998
13 years 11 months ago
Sequence Assembly Validation by Multiple Restriction Digest Fragment Coverage Analysis
DNA sequence analysis depends on the accurate assembly of fragment reads for the determination of a consensus sequence. This report examines the possibility of analyzing multiple,...
Eric C. Rouchka, David J. States
RECOMB
2005
Springer
14 years 10 months ago
Learning Interpretable SVMs for Biological Sequence Classification
Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
Christin Schäfer, Gunnar Rätsch, Sö...
BMCBI
2004
113views more  BMCBI 2004»
13 years 10 months ago
Oligo kernels for datamining on biological sequences: a case study on prokaryotic translation initiation sites
Background: Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks ...
Peter Meinicke, Maike Tech, Burkhard Morgenstern, ...
RECOMB
2004
Springer
14 years 10 months ago
Maximum likelihood resolution of multi-block genotypes
We present a new algorithm for the problems of genotype phasing and block partitioning. Our algorithm is based on a new stochastic model, and on the novel concept of probabilistic...
Gad Kimmel, Ron Shamir