Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Big Data Analysis On Gene Mutation Detection For Bacterial Diseases

Author : Sharath Kumar S 1 Sanil A Jain 2 Veeresh Shenoy S 3 Vinith G 4 M Ravi Krishna 5

Date of Publication :20th April 2017

Abstract: Big data and analytics is a method of examining a lot of datasets to uncover hidden patterns, market trends, and other useful business information. In a human body, the gene will generate a significant amount of data; the real challenge here is to find, collect, analyze and manage information so that we can avoid the occurrence of the illness and be healthier. Nowadays many people are losing their lives because of bacterial diseases like MRSA, CRE, etc. So we are trying to collect the data sets of a particular disease and analyze it by detecting gene mutation, which helps people to find which gene is the actual cause of the particular disease. Here we will be finding which mutation is responsible for that drug resistance. This drug resistant gene will be found out in a large population. A mutation is the permanent change of the nucleotide sequence of an organism, genetic elements, virus or extrachromosomal DNA. Errors during DNA replication results in the mutation which further undergoes error-prone repair. Through genetic recombination, mutations can involve the duplication of vast sections of DNA

Reference :

    1. Min Li, XinDu and et.al, “MRSA epidemic linked to a quickly spreading colonization and virulence determinant,” NatureMedicine18,816–819(2012)doi:10.1038/nm.2692, 22 April 2012.
    2. IEEE Journal of Biomedical and Health Informatics (Volume: 19, Issue: 4, July 2015).
    3. M.J. Cunningham and et. genomics and proteomics: “The new millennium of drug discovery and development”. Journal of Pharmacological and Toxicological Methods, Volume 45, Issue 1, January–February 2001.
    4. Aisling O‟Driscoll, Jurate Daugelaite, Roy D. Sleator: “Big data, Hadoop and cloud computing in genomics”
    5. Matti Niemenmaa, Aleksi Kallio, André Schumacher, Petri Klemela, Eija Korpelainen and Keijo Heljanko, “Hadoop-BAM: directly manipulating next generation Sequencing data in the cloud”. Bioinformatics 2012, 28(6):876-877, doi:10.1093/bioinformatics/bts054

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