RECOMB 2003 - PDF Preprint Papers

RECOMB 2003 Annual Conference on Research in Computational Molecular Biology

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RECOMB
2003
Springer

219views Computational Biology» more RECOMB 2003»

Combining phylogenetic and hidden Markov models in biosequence analysis

14 years 5 months ago

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A few models have appeared in recent years that consider not only the way substitutions occur through evolutionary history at each site of a genome, but also the way the process c...

Adam C. Siepel, David Haussler

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Id	Views	Title	Status

1	219	Combining phylogenetic and hidden Markov models in biosequence analysis	claim
2	181	An integrated probabilistic model for functional prediction of proteins	claim
3	174	Approximation of protein structure for fast similarity measures	claim
4	173	Engineering a scalable placement heuristic for DNA probe arrays
5	173	Physical network models and multi-source data integration	claim
6	169	Modeling dependencies in protein-DNA binding sites	claim
7	162	Whole-genome comparative annotation and regulatory motif discovery in multiple yeast species	claim
8	157	Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals	claim
9	156	Joint classifier and feature optimization for cancer diagnosis using gene expression data	claim
10	146	Phylogenetically and spatially conserved word pairs associated with gene expression changes in yeasts	claim
11	137	Transforming men into mice: the Nadeau-Taylor chromosomal breakage model revisited	claim
12	127	Designing seeds for similarity search in genomic DNA	claim
13	125	Accurate detection of very sparse sequence motifs	claim
14	123	Optimizing exact genetic linkage computations	claim
15	123	A multi-expert system for the automatic detection of protein domains from sequence information	claim
16	121	On de novo interpretation of tandem mass spectra for peptide identification	claim
17	113	Finding recurrent sources in sequences	claim
18	111	A complete and effective move set for simplified protein folding	claim
19	106	Gene selection criterion for discriminant microarray data analysis based on extreme value distributions	claim
20	104	Haplotypes and informative SNP selection algorithms: don't block out information	claim
21	104	Using a mixture of probabilistic decision trees for direct prediction of protein function	claim
22	103	Haplotype reconstruction from SNP alignment	claim
23	92	Efficient rule-based haplotyping algorithms for pedigree data	claim
24	87	Maximum likelihood on four taxa phylogenetic trees: analytic solutions	claim
25	86	Towards optimally multiplexed applications of universal DNA tag systems	claim
26	80	Large scale reconstruction of haplotypes from genotype data	claim

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