Bioinformatics refers to the creation and advancement of algorithms, computational and statistical techniques, and theory to solve formal and practical problems arising from the management and analysis of biological data. It is the application of computer technology to the management of biological information. This program use the computers to store, search and characterize the genetic code of genes, the proteins linked to each gene and their associated functions. Bioinformatics plays an important role as an adjunct to genomics research, because of the large amount of complex data this research generates. Recent years have seen an explosive growth in biological data which is coped by the bioinformatics program. Large sequencing projects are producing increasing quantities of nucleotide sequences. The contents of nucleotide databases are doubling in size approximately every 14 months. The latest release of GenBank exceeded one billion base pairs. 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. Major research efforts in the field include sequence alignment, gene finding, genome assembly, protein structure alignment, protein structure prediction, prediction of gene expression and protein-protein interactions, and the modeling of evolution.
The terms bioinformatics and computational biology are closely related to each other where the former is concerned with the information while computational biology is concerned with the hypotheses. However Computational biology is the hypothesis-driven investigation of a specific biological problem using computers, carried out with experimental or simulated data, with the primary goal of discovery and the advancement of biological knowledge. A representative problem in bioinformatics is the assembly of high-quality genome sequences from fragmentary "shotgun" DNA sequencing. They also study gene regulation to perform expression profiling using data from micro arrays or mass spectrometry.
Thus the science behind Bioinformatics is the melding of molecular biology with computer science, in understanding human diseases and in the identification of new molecular targets for drug discovery with the use of genomic information. In recognition of this, many universities, government institutions and pharmaceutical firms have formed bioinformatics groups, consisting of computational biologists and bioinformatics computer scientists.
The career prospects in Bioinformatics have been steadily increasing with more and more use of information technology in the field of molecular biology. Job prospects are in all sectors of biotechnology, pharmaceutical and biomedical sciences, in research institutions, hospital and industry. Some of the specific career areas that fall within the scope of bioinformatics include Sequence assembly, Database design and maintenance, Sequence analysis, Proteomics, Pharmacogenomics, Pharma-cology,Clinical pharmacologist, Informatics developer; Computational chemist, Bio-analytics and Analytics etc. One can find work in Pharmaceutical and Biotech Companies where bioinformatics technologies are applied throughout the drug discovery process. One can also take up teaching jobs in public institutions if you have a skill in teaching.
PIONEER IN THE FIELD OF BIOINFORMATICS
RICHARD A. LERNER
Dr. Margaret Belle Dayhoff was an American physical chemist and a pioneer in the field of bioinformatics. She was the first woman to hold office in the Biophysical Society, first as Secretary and eventually President. She originated one of the first substitution matrices, Point accepted mutations or (PAM).
Dayhoff was born an only child in Philadelphia, but moved to New York City as a child. Her academic promise was evident from the outset; she was valedictorian (class of 1942) at Bayside High School, Bayside, New York and from there received a scholarship to Washington Square College of New York University, graduating magna cum laude in mathematics in 1945. Dayhoff went on to pioneer the development of programmable computer methods for use in comparing protein sequences and deriving their evolutionary histories from their sequence alignments. Though this was before the days of massive outputs of sequence information by automated and other methods, Margaret Dayhoff anticipated the potential of computers to the current theories of Zuckerkandl & Pauling and the method which Sanger had engineered.
With Richard Eck, she published the first reconstruction of a phylogeny by computers from molecular sequences, using a maximum parsimony method. She also formulated the first probability model of protein evolution, the PAM model, in 1966. She initiated the collection of protein sequences in the Atlas of Protein Sequence and Structure, a book collecting all known protein sequences that she published in 1965. It was subsequently republished in several editions. This led to the Protein Information Resource database of protein sequences, which was developed by her group. It and the parallel effort by Walter Goad which led to the GenBank database of nucleic acid sequences are the twin origins of the modern databases of molecular sequences. The Atlas was organized by gene families, and she is regarded as a pioneer in their recognition. Her approach to proteins was always determinedly evolutionary.
GENOME OF SIMPLEST ANIMAL REVEALS SNCIENT LINEAGE CONFOUNDING ARRAY OF COMPLEX CAPABILITIES
PAs Aesop said, appearances are deceiving-even in life's tiniest critters. From first detection in the 1880s, clinging to the sides of an aquarium, to its recent characterization by the U.S. Department of Energy Joint Genome Institute (DOE JGI), a simple and primitive animal, Trichoplax adhaerens, appears to harbor a far more complex suite of capabilities than meets the eye. The findings, reported in the August 21 online edition of the journal Nature, establish a group of organisms as a branching point of animal evolution and identify sets of genes, or a "parts list," employed by organisms that have evolved along particular branches.
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