Open AccessFrequent Sequential Patterns (FSP) Algorithm for Finding Mutations in BRCA2 Gene
Author(s) -
Jawahar. S*,
S Reshmi.,
Ahamed Johnsha Ali. S
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c6507.098319
Subject(s) - suffix , sequence (biology) , gene , mutation , algorithm , computational biology , computer science , genetics , value (mathematics) , biology , data mining , machine learning , philosophy , linguistics
The Sequential Pattern Mining (SPM) is a fundamental task in data mining. The SPM mines subsequences from given sequence which can be used for various analyses. This paper aims to propose an efficient method for mining frequent sequential patterns in biological data. It also includes the k-mer for decomposing the sequence according to the user defined threshold value. The input data used is breast cancer gene BRCA2 normal and mutated BRCA2 gene. The parameters used for analyses are suffix, candidate pattern and frequent pattern. The suffix value is increased for mono-,di and trinucleotide in mutated gene and in frequent pattern tri-nucleotide has increased nucleotide in mutated gene. So this abnormal increase in pattern may leads to cancer in the human