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Computational biology is a relatively new branch of modern biology. It employs aspects of biology, computer science, and mathematics to solve problems that are unworkable with traditional biological techniques. It is only in the last 30 years that the tools needed by computational biologist have been available. With the advent and advancement of complex data processing systems, computational biology has emerged.
The term “computational biology” is often confused with “bioinformatics” because of the similarity of tools which are employed to solve problems in their respective areas. Both use advanced computational processing and mathematical modeling to explain phenomena and predict outcomes. They both involve the use of techniques from computer science, statistics, and applied mathematics to model living systems and solve biological problems. The primary difference between computational biology and bioinformatics is that the former tends to focus on the testing of hypotheses and new discoveries within the realm of biology and the latter tends to focus on the development of mathematical techniques and algorithms that can be applied to the simulation of biological systems (Ouzounis, 2012).
The field of computational biology offers a nontraditional approach to investigating complex biological problems. Typical topics within the field include gene finding, genome assembly, protein structure prediction and alignment, and the modeling of biological systems and processes over long periods of time. Examples of processes over time suitable for such models would include evolutionary trends, gene expression through multiple generations, and perhaps long-term biological consequences of climate change (Ouzounis, 2012).
Computational biology includes many traditional areas such as systems biology, molecular biology, biochemistry, biophysics, statistics, and computer science as well as recently developed disciplines including bioinformatics and computational genomics. Algorithms which are able to closely model biological behavior help to validate the medical understanding of the observed processes and can be used to model scenarios that might not be able to be physically reproduced.
The ultimate goal of computational biology would be to create a high level software based organism that is comprised of a collection of biological subsystems which would include circulatory, digestive, endocrine, integumentary, lymphatic, muscular, nervous, reproductive, respiratory, skeletal, reproductive, and urinary systems. Within each of these systems, software based cells and their biological, mechanical, and chemical behaviors would be programmed to interact with the environment and subsystems with which the cell functions.