Introduction to Pattern Matching Algorithm to Human Genome:
This technique is used to identify the same pattern from the large databases, without any use of costly software or hardware. It can be done by using mathematical calculations that are formulated into the algorithms that can be used for the pattern matching technique. This technique is widely used in the DNA matching.
DNA is divided into two groves, major grove and minor grove. They are aligned in two ways, pair wise alignment and multiple sequence alignment. There are different techniques used for pattern matching like: dot matrix, substitution, dynamic programming, and words method.
Pair wise sequence alignment: they can be written in 3 combinations like:
(A) ATTCGGCATTCAGTGCTAGA, (B) ATTCGGCATTCAGTGCTAGA, (C) ATTCGGCATTCAGTGCTAGA
(D) ATTCGGCATTGCTAGA, (E) ATTCGGCATTCAGTGCTAGA, (F) ATTCGGCATT – – – – GCTAGA.
Multiple sequence alignment: (J) TCAGAGCGAGA, (K) ATCCGGCCGGCAGCGAGA
(L) CAAAATTCAGAGCGAGA, (M)ATCCGCAGAGCCCGGGGAGA, (N) CCCGGCAGCGAGA
(O) ATCCGTTTTTTTTTGAGA.
They generally use dot matrix technique for pattern matching. When the scan the pattern several green, pinks, and red dots are formed which indicate their values like: red-A-A, green-T-T, pink-C-C, and blue-G-G.
Words method: it uses two techniques;
– FASTA: first when the query is made it search the query from the hash table, if it founds then it align and score the matching segment.
– BLAST: it find each word from the query sequence by finding the list score a least T when score is using the pair score matrix.
Conclusion: these techniques are robust as they can be adopted to support current user and the challenges in computational world. It uses traditional methods like dot matrix analysis and some genetic algorithms.
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