Published in Proteins Structure Function and Bioinformatics
The SAM-T04 method for predicting protein structures uses a single protocol across the entire range of targets, from comparative modeling to new folds. This protocol is similar to the SAM-T02 protocol used in CASP5, but has improvements in the iterative search for similar sequences in finding and aligning templates, in creating fragment libraries, ...
Published in Cytometry Part A
Published in Proteins Structure Function and Bioinformatics
We discuss how methods based on hidden Markov models performed in the fold-recognition section of the CASP2 experiment. Hidden Markov models were built for a representative set of just over 1,000 structures from the Protein Data Bank (PDB). Each CASP2 target sequence was scored against this library of HMMs. In addition, an HMM was built for each of...
Published in International Conference on Intelligent Systems for Molecular Biology
A new method of discovering the common secondary structure of a family of homologous RNA sequences using Gibbs sampling and stochastic context-free grammars is proposed. Given an unaligned set of sequences, a Gibbs sampling step simultaneously estimates the secondary structure of each sequence and a set of statistical parameters describing the comm...
Published in Nucleic Acids Research
Stochastic context-free grammars (SCFGs) are applied to the problems of folding, aligning and modeling families of tRNA sequences. SCFGs capture the sequences common primary and secondary structure and generalize the hidden Markov models (HMMs) used in related work on protein and DNA. Results show that after having been trained on as few as 20 tRN...
Published in Bioinformatics
Published in Proteins Structure Function and Bioinformatics
This article presents an overview of the SAM-T02 method for protein fold recognition and the UNDERTAKER program for ab initio predictions. The SAM-T02 server is an automatic method that uses two-track hidden Markov models (HMMS) to find and align template proteins from PDB to the target protein. The two-track HMMs use an amino acid alphabet and one...
Published in Bioinformatics
Published in Bioinformatics
Published in Bioinformatics
Published in Cytometry Part A
Published in Computer applications in the biosciences : CABIOS
We present a method for condensing the information in multiple alignments of proteins into a mixture of Dirichlet densities over amino acid distributions. Dirichlet mixture densities are designed to be combined with observed amino acid frequencies to form estimates of expected amino acid probabilities at each position in a profile, hidden Markov mo...
Published in Journal of Molecular Biology
The sequences of related proteins can diverge beyond the point where their relationship can be recognised by pairwise sequence comparisons. In attempts to overcome this limitation, methods have been developed that use as a query, not a single sequence, but sets of related sequences or a representation of the characteristics shared by related sequen...
Published in International Conference on Intelligent Systems for Molecular Biology
A Bayesian method for estimating the amino acid distributions in the states of a hidden Markov model (HMM) for a protein family or the columns of a multiple alignment of that family is introduced. This method uses Dirichlet mixture densities as priors over amino acid distributions. These mixture densities are determined from examination of previous...
Published in International Conference on Intelligent Systems for Molecular Biology
A Bayesian method for estimating the amino acid distributions in the states of a hidden Markov model (HMM) for a protein family or the columns of a multiple alignment of that family is introduced. This method uses Dirichlet mixture densities as priors over amino acid distributions. These mixture densities are determined from examination of previous...
Published in International Conference on Intelligent Systems for Molecular Biology
A new method of discovering the common secondary structure of a family of homologous RNA sequences using Gibbs sampling and stochastic context-free grammars is proposed. Given an unaligned set of sequences, a Gibbs sampling step simultaneously estimates the secondary structure of each sequence and a set of statistical parameters describing the comm...
Published in Computer applications in the biosciences : CABIOS
We present a method for condensing the information in multiple alignments of proteins into a mixture of Dirichlet densities over amino acid distributions. Dirichlet mixture densities are designed to be combined with observed amino acid frequencies to form estimates of expected amino acid probabilities at each position in a profile, hidden Markov mo...
Published in Proteins Structure Function and Bioinformatics
We discuss how methods based on hidden Markov models performed in the fold-recognition section of the CASP2 experiment. Hidden Markov models were built for a representative set of just over 1,000 structures from the Protein Data Bank (PDB). Each CASP2 target sequence was scored against this library of HMMs. In addition, an HMM was built for each of...
Published in Proteins Structure Function and Bioinformatics
This article presents an overview of the SAM-T02 method for protein fold recognition and the UNDERTAKER program for ab initio predictions. The SAM-T02 server is an automatic method that uses two-track hidden Markov models (HMMS) to find and align template proteins from PDB to the target protein. The two-track HMMs use an amino acid alphabet and one...
Published in Proteins Structure Function and Bioinformatics
The SAM-T04 method for predicting protein structures uses a single protocol across the entire range of targets, from comparative modeling to new folds. This protocol is similar to the SAM-T02 protocol used in CASP5, but has improvements in the iterative search for similar sequences in finding and aligning templates, in creating fragment libraries, ...
