Bioinformatics is a computational tool used to organize, analyze, and understand biomolecules. It visualizes and store information associated with biological macromolecules. Bioinformatics is a new emerging discipline that combines information science, mathematics, and biology to help answers related biological questions.
The history of Bioinformatics
The word ‘bioinformatics’ first used in 1968. Its definition first described in 1978. Bioinformatics has also been known as a ‘computational biology’. Nonetheless, strictly speaking, this computational biology involves mainly the modeling of the biological systems. The main parts of bioinformatics include the analysis and interpretation of biological data. By using a variety of software tools such as particular algorithms, and the development of software tools and algorithms, analysis and interpretation is done. Following illustrates a brief overview of the history of bioinformatics:
- Needleman Wunsch algorithm for comparing DNA or protein sequences
- First use of the term “Bioinformatics”
- PDB: The Protein Data Bank
- Smith-Waterman algorithm for sequence alignment
- The SWISSPROT database
- The FASTA algorithm for heuristic sequence comparison
- The BLAST algorithm for fast sequence similarity search
- EST for large-scale transcriptome sequencing
- Microarrays for large-scale gene expression profiling
- First draft of human genome
- Mouse and rat genomes published
- Chimpanzee genome published
Application of Bioinformatics
Bioinformatics is an emerging interdisciplinary area of science and technology. Basically, it is an interface between modern biology and informatics. A few major applications of bioinformatics involve:
- Database searches, data mining, modeling, product design, and analyses and interpretation
- Discovery, processing and implementation of the computational algorithms. Software tools facilitate an understanding of the biological systems that may serve, primarily, agriculture or other healthcare sectors with several different spinoffs.
- Genome Analysis
- DNA micro array data analysis is another research area for quantifying the levels of gene expression. It plays an important role such as in various tissues or at different stages for the development of diseases.
- Genome level comparisons of healthy individuals with those carrying some disorder can help identify drug targets
- Comparative genomics- Function for the establishment of the relation between two genes from different organisms.
- Functional genomics: For the identification of gene function.
- Protein Folding: Each protein possesses a characteristic three-dimensional shape and function which defines the sequence of amino acids constituting it. This in turn checks genetically by the sequences of several bases in DNA of the cell with the help of genetic code.
- Drug Design: Potential drugs can bind to DNA, RNA or proteins to suppress or enhance the action at any stage in the pathway. Structure based computational like drug design methods mainly focus on the design of molecules. The method functions for a target site/active sites with known three dimensional structure. This involves generation of candidate molecules, up gradation of the molecules for their drug-likeness, and checking of these molecules along with the target. It also orders molecules relative to their binding affinities.
Drug design also involves the further optimization of the molecules that improve binding features and studies on recently discovered drug or delivery methods. New principles are designed too in order to cut down on toxicity.
- Metabolomics: For the systemization and quantification of the myriad small molecules like present in the biological fluids under different conditions.
- Metabonomics: For the study of how the metabolic profile of a complex biological system such as changes in response to stresses like disease, toxic exposure, or dietary change.
- Nutrigenomics: A generalized term which links genomics, transcriptomics, proteomics and metabolomics to human nutrition.
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