Computational Biology has gained significant importance in genome mapping and R&D applications in bioinformatics and neuroscience

 

Computational Biology

Computational biology refers to the combination of computer science, mathematics, and biology to solve biological problems. The field is broad, with applications in a variety of scientific disciplines. It is used to design and develop complex biological software and hardware. Computational biology covers a vast array of biology subjects, including molecular biology, physiology, genetics, zoology, botany, and immunology. Computational biology can be applied to a wide variety of problems, ranging from developing new drugs to sequencing a genome.

Computational biology is related to the field of computer sciences. There are many areas of overlap, including programming languages (such as C++ and Java), databases, hardware, and algorithms that are used in the analysis of biological data. Computational systems biology is concerned with the development of computer programs that solve biological problems. Computational genomics creates applications to study the effects of genetic modifications on natural populations. Computational Immunology produces diagnostic tools to detect and monitor allergic reactions. Computational systems biology started as an area of computer science, however, it quickly moved outside of the scientific community to include biology departments at major research universities. Many of these programs utilize modeling and simulation technologies to study complex biological processes. Computational population genetics applies techniques to studying human population genetics. Population genomics uses DNA sequences as well as genetic variation among humans to track disease risk.

Computational technology has been applied to a variety of scientific disciplines, as well. Computational biology has particularly seen an explosion of interest due to the publication of the human genome. In fact, the human brain was modeled by computer scientists in the early nineties, and the result was an entirely new area of study known as computational biology. Computational technologies have also seen applications outside of the scientific world, in areas such as business, medicine, and engineering. Some of the most common applications are in financial markets, including optimization of portfolio strategies and risk management.


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