Bioinformatics
BIOINFORMATICS
-By Siddhant Kolke
Bioinformatics not only represents the union of biology and information, but brings forth a rather uncommon overlap between biochemistry, programming, discrete mathematics, modelling and statistics.
What if I told you understanding complex biological mechanisms of DNA replication, protein folding and gene sequencing could be done without touching a test-tube? Bioinformatics solves it! The dilemma of nitty-grittiness that comes with working with life and living cells is resolved by reducing them to simpler computational problems. For instance, finding the origin of replication or oriC region in the genome of a bacterium [excerpts taken from 1]:- If you were a biologist then you could think about an experiment. For example, you can start cutting short pieces from DNA, and when you cut a piece and the cell suddenly loses the ability to replicate, it means that you probably cut out the origin of replication. To a computer scientist, this problem is ill-defined and lacks definition. The budding bioinformatician or geneticist looks to ask another question, ”How does the cell know to begin replication in a short oriC region?” There must be some hidden messages in the genome that tell the cell ”Start replication right here!” What are these hidden messages? Patterns of sequences on a string of course! This opens up numerous quantitative possibilities such as cytosine to guanine ratio change and most frequent k-mers in the genome string. The ”Hidden Message Problem” makes up a popular introductory dive into the deep sea of Bioinformatics. These very findings of patterns, analogues, using biochemical theory and research data to predict unforeseen outcomes with an algorithmic approach constitutes bioinformatics, which distinguishes itself as an upcoming and groundbreaking interdisciplinary field in the biology today.
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