论文信息 - A branch and bound algorithm for local multiple alignment.

A branch and bound algorithm for local multiple alignment.

A Branch and Bound Algorithm has been developed to find a set of window positions in a compilation of sequences with globally maximal information content. We have also developed an algorithm for brute force evaluation of solutions which is faster by a factor of the length of the windows than the naïve brute force algorithm. The combination of these two algorithms allows us to solve problems to optimality that were previously amenable only to heuristic algorithms.

P Horton

[1] G. Stormo,et al. Identifying protein-binding sites from unaligned DNA fragments. , 1989, Proceedings of the National Academy of Sciences of the United States of America.

[2] D. A. Bell,et al. Information Theory and Reliable Communication , 1969 .

[3] A. A. Reilly,et al. An expectation maximization (EM) algorithm for the identification and characterization of common sites in unaligned biopolymer sequences , 1990, Proteins.

[4] Kevin Karplus,et al. Evaluating Regularizers for Estimating Distributions of Amino Acids , 1995, ISMB.

[5] Charles Elkan,et al. The Value of Prior Knowledge in Discovering Motifs with MEME , 1995, ISMB.

[6] Jun S. Liu,et al. Detecting subtle sequence signals: a Gibbs sampling strategy for multiple alignment. , 1993, Science.

[7] T. D. Schneider,et al. Information content of binding sites on nucleotide sequences. , 1986, Journal of molecular biology.

[8] John D. Kececioglu,et al. The Maximum Weight Trace Problem in Multiple Sequence Alignment , 1993, CPM.

[9] Gary D. Stormo,et al. Identification of consensus patterns in unaligned DNA sequences known to be functionally related , 1990, Comput. Appl. Biosci..