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Computational biology : a statistical mechanics perspective / Ralf Blossey.

By: Material type: TextTextSeries: Publisher: Boca Raton, Florida : CRC Press, [2020]Edition: Second editionDescription: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780429503672
  • 0429503679
  • 9780429994616
  • 0429994613
  • 9780429994593
  • 0429994591
  • 9780429994609
  • 0429994605
Subject(s): DDC classification:
  • 572.80285 23
LOC classification:
  • QH506 .B57 2020eb
Online resources:
Contents:
Part 1: Equilibrium statistical mechanics -- Equilbrim statistical mechanics -- Biomolecular structure: DNA, RNA, proteins -- Phase transitions in RNA -- Soft matter electrostatics -- Part 2: Non-equilibrium statistical mechanics -- Back to P: probabilities over time -- Fluctuation theorems -- Dynamics of biological networks -- Biological networks: space.
Summary: Computational biology has developed rapidly during the last two decades following the genomic revolution which culminated in the sequencing of the human genome. More than ever it has developed into a field which embraces computational methods from different branches of the exact sciences: pure and applied mathematics, computer science, theoretical physics. This Second Edition provides a solid introduction to the techniques of statistical mechanics for graduate students and researchers in computational biology and biophysics. Material has been reorganized to clarify equilbrium and nonequilibrium aspects of biomolecular systems Content has been expanded, in particular in the treatment of the electrostatic interactions of biomolecules and the application of non-equilibrium statistical mechanics to biomolecules New network-based approaches for the study of proteins are presented. All treated topics are put firmly in the context of the current research literature, allowing the reader to easily follow an individual path into a specific research field. Exercises and Tasks accompany the presentations of the topics with the intention of enabling the readers to test their comprehension of the developed basic concepts.
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Part 1: Equilibrium statistical mechanics -- Equilbrim statistical mechanics -- Biomolecular structure: DNA, RNA, proteins -- Phase transitions in RNA -- Soft matter electrostatics -- Part 2: Non-equilibrium statistical mechanics -- Back to P: probabilities over time -- Fluctuation theorems -- Dynamics of biological networks -- Biological networks: space.

Computational biology has developed rapidly during the last two decades following the genomic revolution which culminated in the sequencing of the human genome. More than ever it has developed into a field which embraces computational methods from different branches of the exact sciences: pure and applied mathematics, computer science, theoretical physics. This Second Edition provides a solid introduction to the techniques of statistical mechanics for graduate students and researchers in computational biology and biophysics. Material has been reorganized to clarify equilbrium and nonequilibrium aspects of biomolecular systems Content has been expanded, in particular in the treatment of the electrostatic interactions of biomolecules and the application of non-equilibrium statistical mechanics to biomolecules New network-based approaches for the study of proteins are presented. All treated topics are put firmly in the context of the current research literature, allowing the reader to easily follow an individual path into a specific research field. Exercises and Tasks accompany the presentations of the topics with the intention of enabling the readers to test their comprehension of the developed basic concepts.

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