Bioinformatics

It is said that bioinformatics is the marriage between biology and information technology.

the basics and the anatomy of information technology / computer science and biology / life sciences are completely different. But their combination has given the humans a new tool to explore the hidden mysteries of science.

Bio informatics has domains in biology, computer science, statistics, genetics, maths and various other fields.

The applications of bio informatics can range from

- accessing the internet to read literature
- manuscript preparation
- DNA sequence analysis
- protein modelling
- Using virtual reality experiments
- Running biological simulations

It's worth considering why such a field came into existence.

First nucleotide sequencing directly from DNA was performed in 1973. In late 1970s some on e could get a PHD by just sequencing any gene. By 1982 this became a very straight forward task.

Then accumulation of sequence data increased so rapidly with the Human Genome project which was started around 1990.

for example,

in 1999, 1.5Mb of human genomic sequences were deposited in genebank monthly. In 2001 15 billion bases of sequence information were deposited. So there's a very rapid growth curve of sequence information. It became virtually impossible to handle these information manually by humans or by simple computations. So there was need of extensive integration information technology with biological information handling. Bio informatics is a result of this integration.

Bioinformatics can be divided into two broad categories.

1. computational biology
2. analytical bio informatics

Computational biology uses formal algorithms and testable hypotheses if biology, then encode them into various programmes. Mainly considering the mathematics of biology. For example the development of tools like BLAST, FASTA are results of computational biology. So in this sense, computational biology is making tools.

Analytical bio informatics is using these tools.

ex: sequence retrieval from gene bank.

analysis of various regression using local statistical software.

With the expansion of internet and world wide web the tools and data became available to almost any one in the world. So using these resources is not a feat in any sense.

So what really matters is internet research skills to find where information is and to retrieve right kind of information for your purpose.

Once you retrieved your data, the researcher should be able to manipulate these data as he/she wish. There are large amount of pre-built tools to do what you need to do. But to truely exploit the capacity of data analysis tools, a researcher need to be able to at least use a scripting language and databases properly.