Title |
Mathematical and computational modeling in biology at multiple scales
|
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Published in |
Theoretical Biology and Medical Modelling, December 2014
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DOI | 10.1186/1742-4682-11-52 |
Pubmed ID | |
Authors |
Jack A Tuszynski, Philip Winter, Diana White, Chih-Yuan Tseng, Kamlesh K Sahu, Francesco Gentile, Ivana Spasevska, Sara Ibrahim Omar, Niloofar Nayebi, Cassandra DM Churchill, Mariusz Klobukowski, Rabab M Abou El-Magd |
Abstract |
A variety of topics are reviewed in the area of mathematical and computational modeling in biology, covering the range of scales from populations of organisms to electrons in atoms. The use of maximum entropy as an inference tool in the fields of biology and drug discovery is discussed. Mathematical and computational methods and models in the areas of epidemiology, cell physiology and cancer are surveyed. The technique of molecular dynamics is covered, with special attention to force fields for protein simulations and methods for the calculation of solvation free energies. The utility of quantum mechanical methods in biophysical and biochemical modeling is explored. The field of computational enzymology is examined. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 33% |
Unknown | 4 | 67% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 2 | 33% |
Practitioners (doctors, other healthcare professionals) | 2 | 33% |
Members of the public | 2 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 3% |
France | 1 | 1% |
Korea, Republic of | 1 | 1% |
Unknown | 86 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 24 | 26% |
Student > Ph. D. Student | 11 | 12% |
Student > Master | 11 | 12% |
Student > Bachelor | 8 | 9% |
Student > Doctoral Student | 7 | 8% |
Other | 19 | 21% |
Unknown | 11 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 14 | 15% |
Agricultural and Biological Sciences | 14 | 15% |
Computer Science | 8 | 9% |
Medicine and Dentistry | 8 | 9% |
Engineering | 7 | 8% |
Other | 24 | 26% |
Unknown | 16 | 18% |