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Books on the topic 'Biophysical modelling'

Author: Grafiati

Published: 4 June 2021

Last updated: 18 June 2025

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1

1937-, Chadwick K. H., Moschini G, Varma Matesh N, Istituto nazionale di fisica nucleare., United States. Dept. of Energy. Office of Health and Environmental Research., and Commission of the European Communities., eds. Biophysical modelling of radiation effects. A. Hilger, 1992.

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2

Michael, Kraus. Structured biological modelling: A new approach to biophysical cell biology. CRC Press, 1995.

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3

Dössel, Olaf. World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany: Vol. 25/4 Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics. Springer-Verlag Berlin Heidelberg, 2009.

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4

International Symposium on Mathematical and Computational Biology. BIOMAT 2006: International Symposium on Mathematical and Computational Biology, Manaus, Brazil, 27-30 November 2006. World Scientific, 2007.

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5

L, Rivail J., and Société française de chimie. Division de chimie physique., eds. Modelling of molecular structures and properties: Proceedings of the 44th International Meeting of Physical Chemistry on modeling of molecular structures and properties in physical chemistry and biophysics. Elsevier, 1990.

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6

Huffaker, Ray, Marco Bittelli, and Rodolfo Rosa. Phenomenological Modelling. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198782933.003.0009.

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Detecting causal interactions among climatic, environmental, and human forces in complex biophysical systems is essential for understanding how these systems function and how public policies can be devised that protect the flow of essential services to biological diversity, agriculture, and other core economic activities. Convergent Cross Mapping (CCM) detects causal networks in real-world systems diagnosed with deterministic, low-dimension, and nonlinear dynamics. If CCM detects correspondence between phase spaces reconstructed from observed time series variables, then the variables are determined to causally interact in the same dynamic system. CCM can give false positives by misconstruing synchronized variables as causally interactive. Extended (delayed) CCM screens for false positives among synchronized variables.

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7

Biophysical Approaches Determining Ligand Binding to Biomolecular Targets: Detection, Measurement and Modelling. Royal Society of Chemistry, The, 2011.

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8

Clarke, Andrew. Energy flow in organisms. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199551668.003.0004.

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An organism is an open thermodynamic system exchanging both energy and materials with its environment. Organisms exchange energy with their environment by radiation, conduction, convection and evaporation of water. The relative importance of these varies with the organism and its situation. Newton’s Law of Cooling is a simplification that is useful only for warm endotherms in a still, cool environment. For all other circumstances a full biophysical treatment is necessary. Flows of chemical potential energy can be captured by a balanced energy budget. A full description of the energy balance of an organism requires the coupling of a biophysical model of heat flow with an energy budget model. This combination provides a powerful tool for modelling the thermal and energetic niches of organisms, and to predict how these might change in the future.

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9

(Editor), G. Moschini, K. H. Chadwick (Editor), Istituto Nazionale Di Fisica Nucleare (Corporate Author), United States Department of Energy Office of Health and Environmental Research (Corporate Author), and Matesh N. Varma (Editor), eds. Biophysical Modelling of Radiation Effects: Commission of the European Communities Us Department O F Energy Istituto Nazionale Di Fisica Nucleare (Eur (Series), No. 13848 En.). Institute of Physics Publishing, 1992.

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10

Protein modelling with bioinformatics and biophysics. Springer, 2006.

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11

Limbert, Georges. Skin Biophysics: From Experimental Characterisation to Advanced Modelling. Springer, 2019.

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12

Limbert, Georges. Skin Biophysics: From Experimental Characterisation to Advanced Modelling. Springer International Publishing AG, 2020.

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13

Rouzine, Igor M. Mathematical Modelling of Evolution : Vol. 1: One-Locus and Multi-Locus Theory and Recombination. de Gruyter GmbH, Walter, 2020.

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14

Rouzine, Igor M. Mathematical Modelling of Evolution : Vol. 1: One-Locus and Multi-Locus Theory and Recombination. de Gruyter GmbH, Walter, 2020.

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15

Tass, Peter A. Phase Resetting in Medicine and Biology: Stochastic Modelling and Data Analysis. Springer London, Limited, 2007.

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16

Ouldridge, Thomas E. Coarse-Grained Modelling of DNA and DNA Self-Assembly. Springer Berlin / Heidelberg, 2014.

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17

Appasani, Krishnarao, and Raghu Kiran Appasani, eds. Single-Molecule Science. Cambridge University Press, 2022. http://dx.doi.org/10.1017/9781108525909.

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Single Molecule Science (SMS) has emerged from developing, using and combining technologies such as super-resolution microscopy, atomic force microscopy, and optical and magnetic tweezers, alongside sophisticated computational and modelling techniques. This comprehensive, edited volume brings together authoritative overviews of these methods from a biological perspective, and highlights how they can be used to observe and track individual molecules and monitor molecular interactions in living cells. Pioneers in this fast-moving field cover topics such as single molecule optical maps, nanomachines, and protein folding and dynamics. A particular emphasis is also given to mapping DNA molecules for diagnostic purposes, and the study of gene expression. With numerous illustrations, this book reveals how SMS has presented us with a new way of understanding life processes. A must-have for researchers and graduate students, as well as those working in industry, primarily in the areas of biophysics, biological imaging, genomics and structural biology.

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18

Phase Resetting in Medicine and Biology: Stochastic Modelling and Data Analysis (Springer Series in Synergetics). Springer, 2006.

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19

Phase Resetting in Medicine and Biology: Stochastic Modelling and Data Analysis (Springer Series in Synergetics). Springer-Verlag Telos, 1999.

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20

Biomat 2006: International Sysposium on Mathematical and Computational Biology, Manaus, Brazil, 27-30 November 2006. World Scientific Publishing Company, 2007.

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21

Biomat 2006: International Symposium on Mathematical and Computational Biology. World Scientific Publishing Co Pte Ltd, 2007.

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22

Biomat 2006: International Symposium on Mathematical and Computational Biology. World Scientific Publishing Co Pte Ltd, 2007.

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