How to become a expert bioinformatician

Large sequencing projects are producing increasing quantities of nucleotide sequences. The contents of nucleotide databases are doubling in size approximately every 14 months. Recent years have seen an explosive growth in biological data.Not only the size of sequence data is rapidly increasing, but also the number of characterized genes from many organisms and protein structures doubles about every two years.In order to cope with this great quantity of data, a new scientific discipline has emerged: bioinformatics, biocomputing or computational biology.

Bioinformatics combines the tools and techniques of mathematics, computer science and biology in order to understand the biological significance of a variety of data. So if you like to get into this new scientific field you should be fond of these 'classic' disciplines. Because the field is so new, almost everyone in it did something else before. Some biologist went into bioinformatics by picking up programming but others entered via the reverse route. The introductory courses in its bioinformatics program are similar to those of 'classical' computer science: algorithms and data structures, theoretical computer science, computer architecture, and programming practicals. You will also have mathematics courses on linear algebra, analysis, differential equations, applied maths, and statistics. Introductory biology courses are included as well. Later on the amount of biology courses increases, and the student will get also 'hands-on' experience in laboratory work. Here the student gets some sort of idea about the biologist's everyday work and sometimes realizes what computing tools are available and what tools are missing. The ideas for many of them were born during laboratory work! Inorder to become a expert in Bioinformatics students should must have good grasp over following languages and sotwares:
Languages: Perl, BioPerl, Java, BioJava, Bio++, BioPHP, R S-Plus, SAS, Ruby, BioRuby, MatLab, Python, BioPython
Sotware:VectorNTI, SAS, TANAGRA, Weka, SPD-Viewer,VMD, YASARA, Rasmol, Yale, Glide, HyperChem, etc.
Apart from above languages and softwares you need sound knowledge of Molecular biology, Biochemistry, and Stat.

Major Research Areas in Bioinformatics

Sequence analysis

Genome annotation

Computational evolutionary biology

Measuring biodiversity

Analysis of gene expression

Analysis of protein expression

Analysis of mutations in cancer

Prediction of protein structure

Comparative genomics

Protein-protein docking

Software and tools