A sequence alignment algorithm with an arbitrary gap penalty function.
An algorithm for aligning biological sequences is presented that is an adaptation of the sequence generating function approach used in the statistical mechanics of biopolymers. This algorithm uses recursion relationships developed from a partition function formalism of alignment probabilities. It is implemented within a dynamic programming format that closely resembles the forward algorithm used in hidden Markov models (HMM). The algorithm aligns sequences or structures according to the statistically dominant alignment path and will be referred to as the SDP algorithm. An advantage of this method over previous ones is that it allows more complicated and physically realistic gap penalty functions to be incorporated into the algorithm in a facile manner. The performance of this algorithm in a case study of aligning the heavy and light chain from the variable region of an immunoglobulin is investigated.
Dewey
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Keck Graduate Institute of Applied Life Science, 535 Watson Drive, Claremont, CA 91711, USA. Greg_Dewey@Kgi.edu
D000465:Algorithms; D000595:Amino Acid Sequence; D007143:Immunoglobulin Heavy Chains; D007147:Immunoglobulin Light Chains; D007135:Immunoglobulin Variable Region; D008390:Markov Chains; D015233:Models, Statistical; D008969:Molecular Sequence Data; D016415:Sequence Alignment / Q000379:methods*
D007143:Immunoglobulin Heavy Chains; D007147:Immunoglobulin Light Chains; D007135:Immunoglobulin Variable Region