Pattern matching in bioinformatics computing

Pattern matching is a difficult task in bioinformatics. Pattern matching involves finding one or more matches quickly from large databases by employing the use of minimum hardware. Pattern matching finds wide applications in bioinformatics. Some of the applications are in the construction of controlled vocabularies, data mining, genome sequencing, functional proteomics, functional genomics, natural language processing, homologous gene identification, homologous protein identification, neural network based structure classifiers, nucleotide sequence alignment, protein sequence alignment, rule-based structure classifiers and protein structure prediction. The major task in the field of pattern matching is the sequence alignment. There are three categories here- pairwise sequence alignment, local versus global alignment and multiple sequence alignment. In pairwise sequence alignment, natching of two sequences,, one pair of elements at a time is carried out. The different computational methods used for sequence alignment are Bayesian methods, dot matrix method, dynamic programming method, genetic algorithms method, Hidden Markov models method, neural networks method, word based methods and scoring matrices method.