Bioinformatics

 

Bioinformatics is an emerging interdisciplinary area of Science & Technology encompassing a systematic development and application of IT solutions to handle biological information by addressing biological data collection and warehousing, data mining, database searches, analyses, and interpretation, modeling, and product design. It is a subdiscipline of biology and computer science concerned with the acquisition, storage, analysis, and dissemination of biological data, most often DNA and amino acid sequences. As an interdisciplinary field of science, bioinformatics combines biology, computer science, information engineering, mathematics and statistics to analyze and interpret biological data. Bioinformatics has been used for in silico analyses of biological queries using mathematical and statistical techniques. The word ‘bioinformatics’ was first used in 1968 and its definition was first given in 1978. Bioinformatics has also been referred to as ‘computational biology’. However, strictly speaking, computational biology deals mainly with the modeling of biological systems. The main components of bioinformatics are

 (1) the development of software tools and algorithms

(2) the analysis and interpretation of biological data by using a variety of software tools and particular algorithms.

Bioinformatics is fed by high-throughput data-generating experiments, including genomic sequence determinations and measurements of gene expression patterns. Database projects curate and annotate the data and then distribute it via the World Wide Web. Mining these data leads to scientific discoveries and to the identification of new clinical applications. In the field of medicine in particular, a number of important applications for bioinformatics have been discovered. For example, it is used to identify correlations between gene sequences and diseases, to predict protein structures from amino acid sequences, to aid in the design of novel drugs, and to tailor treatments to individual patients based on their DNA sequences.

The field of bioinformatics has three main objectives:

1.To organize vast reams of molecular biology data in an efficient manner

2. To develop tools that aid in the analysis of such data

3. To interpret the results accurately and meaningfully

The advent and rapid rise of bioinformatics have been due to the massive increases in computing power and laboratory technology. These advances have made it possible to process and analyze the digital information—DNA, genes, and genomes—at the heart of life itself.

Bioinformatics approaches are often used for major initiatives that generate large data sets. Two important large-scale activities that use bioinformatics are genomics and proteomics. Genomics refers to the analysis of genomes. A genome can be thought of as the complete set of DNA sequences that codes for the hereditary material that is passed on from generation to generation. These DNA sequences include all of the genes (the functional and physical unit of heredity passed from parent to offspring) and transcripts (the RNA copies that are the initial step in decoding the genetic information) included within the genome. Thus, genomics refers to the sequencing and analysis of all of these genomic entities, including genes and transcripts, in an organism. Proteomics, on the other hand, refers to the analysis of the complete set of proteins or proteome. In addition to genomics and proteomics, there are many more areas of biology where bioinformatics is being applied (i.e., metabolomics, transcriptomics). Each of these important areas in bioinformatics aims to understand complex biological systems.

In general, the aims of bioinformatics are three-fold. First, at its simplest bioinformatics organizes data in a way that allows researchers to access existing information and to submit new entries as they are produced. The second aim is to develop tools and resources that aid in the analysis of data. The development of such resources dictates expertise in computational theory, as well as a thorough understanding of biology. The third aim is to use these tools to analyze the data and interpret the results in a biologically meaningful manner. Some of the well-known databases include GenBank (Genetic Data Bank), SWISS-PROT, PDB (Protein Data Bank), PIR (Protein Information Resource), SCOP (Familial and Structural Protein Relationships), CATH (Hierarchical Classification of Protein Domain Structures), etc. These databases are available as public domain1information and hosted on various Internet servers across the world. Basic research and modeling is done using these databases with the help sequence analysis tools like BLAST(Basic Local Alignment Search Tool), FASTA(Fast-All), CLUSTALW, etc., and the modeled structures are visualized using visualization tools such as WebLab, MOLMOL, Rasmol, etc.

There is a tremendous application of bioinformatics in the field of homology and similarity tools, protein function analysis, personalized medicine, Gene therapy, Drug development, Comparative Studies, and also climate change studies.