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PatternHunter
PatternHunter is a commercially available homology search instrument software that uses sequence alignment techniques. It was initially developed in the year 2002 by three scientists: Bin Ma, John Tramp and Ming Li.〔 These scientists were driven by the desire to solve the problem that many investigators face during studies that involve genomics and proteomics. These scientists realized that such studies greatly relied on homology studies that established short seed matches that were subsequently lengthened. Describing homologous genes was an essential part of most evolutionary studies and was crucial to the understanding of the evolution of gene families, the relationship between domains and families.〔 Homologous genes could only be studied effectively using search tools that established like portions or local placement between two proteins or nucleic acid sequences.〔 Homology was quantified by scores obtained from matching sequences, “mismatch and gap scores”.〔
== Development ==
In comparative genomics, for example, it is necessary to compare huge chromosomes such as those found in the human genome. However, the immense expansion of genomic data introduces a predicament in the available methods of carrying out homology searches. For instance, enlarging the seed size lowers sensitivity while reducing seed size reduces the speed of calculations. Several sequence alignment programs have been developed to determine homology between genes. These include FASTA, the BLAST family, QUASAR, MUMmer, SENSEI, SIM, and REPuter.〔 They mostly use Smith-Waterman alignment technique, which compares bases against other bases, but is too slow. BLAST makes an improvement to this technique by establishing brief, precise seed matches that it later joins up to form longer alignments.〔 However, when dealing with lengthy sequences, the above-mentioned techniques are extremely sluggish and required considerable memory sizes. SENSEI, however, is more efficient than the other methods, but is incompetent in other forms of alignment as its strength lies in handling ungapped alignments. The quality of the production from Megablast, on the other hand, is of poor quality and does not adapt well to large sequences. Techniques such as MUMmer and QUASAR employ suffix trees, which are supposed to handle exact matches. However, these methods can only apply to the comparison of sequences that display elevated similarities. All the above-mentioned problems necessitate the development of a fast reliable tool that can handle all types of sequences efficiently without consuming too many resources in a computer.
抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』
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