Computational biology

Computational biology

Computational biology involves the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems.[1] The field is widely defined and includes foundations in computer science, applied mathematics, statistics, biochemistry, chemistry, biophysics, molecular biology, genetics, ecology, evolution, anatomy, neuroscience, and visualization.[2]

Contents

Centers/Institutions and leading providers of Computational Biology Resources

Professional Societies and Relevant Organizations

Relevant Journals

Notable Conferences in Computational Biology

Notable Bioinformatics/Computational Biology Databases

Subfields

Computational biomodeling

Computational biomodeling, a field concerned with building computer models of biological systems.

Computational genomics

Computational genomics, a field within genomics which studies the genomes of cells and organisms. High-throughput genome sequencing produces lots of data, which requires extensive post-processing (sequence assembly) and uses DNA microarray technologies to perform statistical analyses on the genes expressed in individual cell types. This can help find genes of interest for certain diseases or conditions. This field also studies the mathematical foundations of sequencing. Advances in many areas of genomics research are heavily rooted in engineering technology, from the capillary electrophoresis units used in large-scale DNA sequencing projects.

Computational neuroscience

Computational neuroscience is the study of brain function in terms of the information processing properties of the structures that make up the nervous system.

Computational biology vs. Bioinformatics

Bioinformatics and computational biology are rooted in life sciences as well as computer and information sciences and technologies. Both of these interdisciplinary approaches draw from specific disciplines such as mathematics, physics, statistics, computer science and engineering, biology, and behavioral science. Bioinformatics and computational biology each maintain close interactions with life sciences to realize their full potential. Bioinformatics applies principles of information sciences and technologies to make the vast, diverse, and complex life sciences data more understandable and useful. Computational biology uses mathematical and computational approaches to address theoretical and experimental questions in biology. Although bioinformatics and computational biology are distinct, there is also significant overlap and activity at their interface.[1]

Another opinion is that Bioinformatics relates to anything to do with analysis, visualization and management of biological sequences, while Computational Biology refers to that plus everything else that involves computers in the solving of biological problems.

See also

Related fields

References

  1. ^ a b http://www.bisti.nih.gov/docs/compubiodef.pdf
  2. ^ http://www.brown.edu/Research/CCMB/undergraduate.htm

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