Computer simulation and data analysis in molecular biology and biophysics
Collection : Biological and medical physics, biomedical engineering. Mention d'édition :2009th ed. Publié par : Springer (New York) Détails physiques : xvi, 321 p. 24 cm. ISBN :1441900845 (hardcover); 9781441900845 (hardcover).| Type de document | Site actuel | Cote | Statut | Date de retour prévue | Code à barres | Réservations |
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| Livre | La bibliothèque des Sciences Exactes et Naturelles | 571.401 13 BLO (Parcourir l'étagère) | Disponible | 0000000018352 |
Survol La bibliothèque des Sciences Exactes et Naturelles Étagères Fermer l'étagère
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| 571.4 NOL Methods in modern biophysics / | 571.4 RAI Integrated molecular and cellular biophysics | 571.4 THO Bases de biophysique générale pour les sciences de la vie | 571.401 13 BLO Computer simulation and data analysis in molecular biology and biophysics | 571.403 ROB VOL.1 Encyclopedia of biophysics | 571.403 ROB VOL.2 Encyclopedia of biophysics | 571.403 ROB VOL.3 Encyclopedia of biophysics |
This book provides an introduction, suitable for advanced undergraduates and beginning graduate students, to two important aspects of molecular biology and biophysics: computer simulation and data analysis. It introduces tools to enable readers to learn and use fundamental methods for constructing quantitative models of biological mechanisms, both deterministic and with some elements of randomness, including complex reaction equilibria and kinetics, population models, and regulation of metabolism and development; to understand how concepts of probability can help in explaining important features of DNA sequences; and to apply a useful set of statistical methods to analysis of experimental data from spectroscopic, genomic, and proteomic sources. These quantitative tools are implemented using the free, open source software program R. R provides an excellent environment for general numerical and statistical computing and graphics, with capabilities similar to Matlab�. Since R is increasingly used in bioinformatics applications such as the BioConductor project, it can serve students as their basic quantitative, statistical, and graphics tool as they develop their careers.


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