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Quantitative Understanding of Breast Cancer Genes

Published on May 2014 by Antara Sengupta, Sk. Sarif Hassan, Pabitra Pal Choudhury
journal_cover_thumbnail

National Conference cum Workshop on Bioinformatics and Computational Biology
Foundation of Computer Science USA
NCWBCB - Number 1
May 2014
Authors: Antara Sengupta, Sk. Sarif Hassan, Pabitra Pal Choudhury
4c54ffae-08aa-4577-ba77-86b4490e340d

Antara Sengupta, Sk. Sarif Hassan, Pabitra Pal Choudhury . Quantitative Understanding of Breast Cancer Genes. National Conference cum Workshop on Bioinformatics and Computational Biology. NCWBCB, 1 (May 2014), 15-17.

@article{
author = { Antara Sengupta, Sk. Sarif Hassan, Pabitra Pal Choudhury },
title = { Quantitative Understanding of Breast Cancer Genes },
journal = { National Conference cum Workshop on Bioinformatics and Computational Biology },
issue_date = { May 2014 },
volume = { NCWBCB },
number = { 1 },
month = { May },
year = { 2014 },
issn = 0975-8887,
pages = { 15-17 },
numpages = 3,
url = { /proceedings/ncwbcb/number1/16506-1406/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference cum Workshop on Bioinformatics and Computational Biology
%A Antara Sengupta
%A Sk. Sarif Hassan
%A Pabitra Pal Choudhury
%T Quantitative Understanding of Breast Cancer Genes
%J National Conference cum Workshop on Bioinformatics and Computational Biology
%@ 0975-8887
%V NCWBCB
%N 1
%P 15-17
%D 2014
%I International Journal of Computer Applications
Abstract

Characterization of oncogenes which are responsible for Breast Cancer can help us to understand the molecular signature of those genes. As it is known that the DNA molecules are nothing but the combinations of four nucleotides A, T, C and G which encodes the genetic instructions, here in this proposed paper firstly it is tried to make a quantitative understanding of DNAs which are responsible for breast cancer by comprehending their structures, characteristics, functions, evolutions etc. which can help to identify those DNAs among several nucleotide strings. Secondly, it is tried to recognize a given nucleotide string as a probable breast cancer DNA, without any conventional biological experiment. In this case, the nucleotide strings of DNAs of thirty seven have been taken and are classified and quantified by adapting some mathematical features.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Breast Cancer Dna Quantitative Analysis Chaos Game Representation Fractal Dimension.