Applications of Computational Biology

Computational biology involves the application of mathematical modeling, computational simulation techniques, data analytics and theoretical methods to the study of behavioral, biological and social systems. When broadly defined, the field includes foundations in applied mathematics, computer science, chemistry, biochemistry, molecular biology, biophysics, genomics, genetics, evolution, ecology, neuroscience, anatomy, and visualization.
Initially, the study of computational biology focussed on the structure and sequence of biological molecules, mainly in an evolutionary context. However, beginning in the 1990s, it extended gradually to the analysis of function. Functional prediction focusses on the structural and sequence similarity between known and known proteins and analyses the interactions of proteins with other molecules. These analyses may be extensive, allowing computational biology to become aligned with systems biology.
Regulatory, biochemical, and genetic pathways are interleaved and branched, as well as dynamic. This calls for sophisticated computational methods for their modeling and analysis. Also, modern technology platforms for rapid generation of biological data have extended the traditional hypothesis-driven testing to data-driven analysis, allowing computational research to be performed on genome-wide databases of unparalleled scale. Many aspects of the study of biology, as a result, have become unthinkable without the power of computers and computer science methodologies.


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