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Using Signal Processing to study DNA
Wednesday, December 05, 2007
SooryaKiran Bioinformatics was the brainchild of the first batch of students
of MPhil Bioinformatics, at Centre for Bioinformatics, University of Kerala,
Thiruvananthapuram. It developed its first tool for the US-based company called
Argus Biosciences, and was called GEN-SNiP. The software helps research students
and bioscientists to compare a regular sequence of DNAs to one which may be
deformed. It determines the Single Nucleotide Polymorphism (SNP) in a set of
mitochondrial DNA sequence against a reference DNA sequence. This is an
effective way of identifying genetic disorders since these disorders occur due
to changes in the protein structure which in turn makes up the DNA structure.
The tool compares the sequence to a regular sequence and identifies the
particular protein which has disturbed the chain. The tool is available online
at
www.argusbio.com/sooryakiran/gensnip/gensnip.php.
Dr. Achuthsankar S Nair, Director, Centre for Bioinformatics, is following a
vision to compress DNA. This will sound as a bizarre statement to a
biotechnologist or genetics professional, but he says he has a scientific logic
for this. “DNA is a language, just like any other computer language”, he said.
“Scientists have only researched on the biological nature of the DNA, but there
is so much information hidden in it as well. If we do some fundamental enquiries
on the informational nature of the DNA, there is so much each gene can tell us.
This information no doubt can be used to understand the DNA further, but it can
also be effectively used to compress the DNA, and when that happens, it will
simplify genetics to a great extent”, he explained.
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Achuthsankar S Nair
Professor, Centre for Bioinformatics, University of Kerala |
As a first step towards this vision, he has incorporated the concept of
signal processing to molecular biology. At molecular level, the DNA comprises of
RNA, amino acids or proteins. Biologically, they form a chain in sequences of
various combinations of ACTG. If one were to consider that they convey data as
digital signals, it will enable scientists to identify a particular property of
the DNA. It will also identify where a particular gene, and will go a long way
in identifying deformities and differences from the reference structure. In
course of time, this institute also plans to extend signal processing to protein
sequences to address the diseases market. Since protein synthesis is the
backbone for study of diseases, signal processing of proteins will ensure that
one can identify 'hotspots' in proteins where irregularity is observed.
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