What is Computational Systems Biology?

Computational systems biology is the use of mathematical and systems biology. It aims to develop efficient algorithms, visualization, and communication tools and data structures with the goal of modeling biological systems. Generally, computational systems biology uses simulations of biological systems.
Today, technological advances have a major impact on molecular biology. Developments in experimental methods mean a large volume of sequence, localization and expression data are now gathered by individual investigators. Additionally, large amounts of these data are kept in many private and public databases. At the same time, access to large-scale computing resources is becoming more common in laboratories of molecular biology. Computational systems biology helps us to learn how to leverage these advances in both computational and experimental resources.
To comprehensively understand biological systems, the integration of computational and experimental research is required. Through theoretical exploration and pragmatic modeling, computational biology provides a foundation from which to address scientific questions head-on. A study in computational systems biology allows individuals to solve biological challenges by combining computing, math and a strong base of biological concepts and knowledge. Individuals learn to approach challenges and formulate questions that span biological systems, from cells to genes to cells to ecology to medicine to evolution.
References
http://dbbs.wustl.edu/divprograms/compbio/Pages/default.aspx
http://www.csb.pitt.edu/
https://www.nature.com/nature/journal/v420/n6912/full/nature01254.html
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