Dr.Hassan mathkour-16-journalx

throneharshBiotechnology

Oct 2, 2013 (3 years and 8 months ago)

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قفرم
1

ةيثحبلا تاصخلملل جذومن :

يزيلجنإ

.


Title

An integrated statistical comparative analysis between variant genetic
datasets of Mus musculus,
.

Author
-
s

Hassan Mathkour, Muneer Ahmad, Hassan Mehmood Khan

Contact
lnfo

Mathkour@KSU.EDU.SA
,


Department

Computer science

Major


citation

International Journal of Computational Intelligence in Bioinformatics and
Systems Biology (IJCIBSB)
,

Volume 1, Number 2

,

Pages:


163
-

176 ,

2009

Year of
Publication

2009

Publisher

IJCIBSB

Sponsor


Type of
Publication

Journal

ISSN


URI/DOI

http://inderscience.metapress.com/app/home/contribution.asp?referrer=parent&backto=issu
e,3,5;journal,3,4;linkingpublicationresults,1:121417,1

Full
Text
(Yes,No)

No

Key words

Mus musculus, comparative analysis, genetic datasets, nucleotide, codon,
trimer, sequence analysis, genetic diversity, feature comparison, NP hard,
genomic sequences, peptide translations, DNA, bioinformatics

Abstract



Comparative genomic analysis between variant datasets of same specie is
considered to be vital to discover the degree of relevancy in them. This
analysis helps in the categorisation of diversity of features in species. An
immense need was felt to build sop
histicated tools for efficient and robust
comparative analysis. The accuracy of methodologies is directly
proportional to sensitivity involved in comparing datasets for optimality.
This paper is a depiction of an effort for the discovery of variant feature
s
between genetic datasets of Mus musculus. The approach described is
demonstrated phase
-
wise with the inclusion of specific filters at each stage.
At first instance, cleansing filter refines the datasets. Further series of filters
depict the layered proce
ss for comprehensive comparative analysis.
Numerical results have been evaluated. The protein translation phase has
been introduced with conceptual demonstration of codon composition
phenomenon. Characteristics of density, nucleotide strengths and codon
co
mposition better reflect the relevancy in genetic datasets of Mus
musculus.