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1

Lü, Jinhu, and Pei Wang. Modeling and Analysis of Bio-molecular Networks. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-9144-0.

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2

Protein-protein complexes: Analysis, modeling and drug design. London: Imperial College Press, 2010.

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3

author, Sarich Marco 1985, ed. Metastability and Markov state models in molecular dynamics: Modeling, analysis, algorithmic approaches. Providence, Rhode Island: American Mathematical Society, 2013.

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4

Institute for Computer Applications in Science and Engineering., ed. Ranges of applicability for the continuum-beam model in the constitutive analysis of carbon nanotubes: Nanotubes or nano-beams? Hampton, VA: ICASE, NASA Langley Research Center, 2001.

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5

Andriyanova, Mariya, Aslanli Aslanli, Nataliya Basova, Viktor Bykov, Sergey Varfolomeev, Konstantin Gorbunov, Valentin Gorelenkov, et al. ORGANOPHOSPHORUS NEUROTOXINS. ru: Publishing Center RIOR, 2020. http://dx.doi.org/10.29039/02026-5.

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The collective monograph is devoted to discussing the history of creation, studying the properties, neutralizing and using organophosphorus neurotoxins, which include chemical warfare agents, agricultural crop protection chemical agents (herbicides and insecticides) and medicines. The monograph summarizes the results of current scientific research and new prospects for the development of this field of knowledge in the 21st century, including the use of modern physicochemical methods for experimental study and theoretical analysis of biocatalysis and its mechanisms based on molecular modeling with supercomputer power. The book is intended for specialists who are interested in the current state of research in the field of organophosphorus neurotoxins. The monograph will be useful for students, graduate students, researchers specializing in the field of physical chemistry, physicochemical biology, chemical enzymology, toxicology, biochemistry, molecular biology and genetics, biotechnology, nanotechnology and biomedicine.
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6

Zhou, Xiaobo. Computational systems bioinformatics: Methods and biomedical applications. New Jersey: World Scientific, 2008.

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7

Wang, Pei, and Jinhu Lü. Modeling and Analysis of Bio-Molecular Networks. Springer Singapore Pte. Limited, 2020.

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8

Wang, Pei, and Jinhu Lü. Modeling and Analysis of Bio-Molecular Networks. Springer Singapore Pte. Limited, 2021.

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9

Nikoloski, Zoran, and Sergio Grimbs. Network-Based Molecular Biology: Data-Driven Modeling and Analysis. De Gruyter, Inc., 2016.

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10

Nikoloski, Zoran, and Sergio Grimbs. Network-Based Molecular Biology: Data-Driven Modeling and Analysis. De Gruyter, Inc., 2016.

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11

Nikoloski, Zoran, and Sergio Grimbs. Network-Based Molecular Biology: Data-Driven Modeling and Analysis. De Gruyter, Inc., 2014.

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12

Nikoloski, Zoran, and Sergio Grimbs. Network-Based Molecular Biology: Data-Driven Modeling and Analysis. De Gruyter, Inc., 2014.

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13

Zacharias, Martin. Protein-Protein Complexes: Analysis, Modeling and Drug Design. World Scientific Publishing Co Pte Ltd, 2010.

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14

Progress in Molecular and Environmental Bioengineering - From Analysis and Modeling to Technology Applications. 2011.

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15

Carpi, Angelo, ed. Progress in Molecular and Environmental Bioengineering - From Analysis and Modeling to Technology Applications. InTech, 2011. http://dx.doi.org/10.5772/771.

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16

Kaxiras, Efthimios, Rob Phillips, Vasily V. Bulatov, Nasr Ghoniem, and Tomas Diaz de la Rubia. Multiscale Modelling of Materials: Volume 538. University of Cambridge ESOL Examinations, 2014.

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17

(Editor), Vasily V. Bulatov, Efthimios Kaxiras (Editor), Nasr Ghoniem (Editor), Rob Phillips (Editor), and Thomas Diaz De LA Rubia (Editor), eds. Multiscale Modelling of Materials: Symposium Held November 30-December 3, 1998, Boston, Massachusets, U.S.A (Materials Research Society Symposia Proceedings, V. 538.). Materials Research Society, 1999.

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18

Zaheer Ul-Haq and Angela K. Wilson, eds. Frontiers in Computational Chemistry: Volume 6. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/97898150368481220601.

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Frontiers in Computational Chemistry presents contemporary research on molecular modeling techniques used in drug discovery and the drug development process: computer aided molecular design, drug discovery and development, lead generation, lead optimization, database management, computer and molecular graphics, and the development of new computational methods or efficient algorithms for the simulation of chemical phenomena including analyses of biological activity. The sixth volume of this series features these six different perspectives on the application of computational chemistry in rational drug design: 1. Computer-aided molecular design in computational chemistry 2. The role of ensemble conformational sampling using molecular docking & dynamics in drug discovery 3. Molecular dynamics applied to discover antiviral agents 4. Pharmacophore modeling approach in drug discovery against the tropical infectious disease malaria 5. Advances in computational network pharmacology for Traditional Chinese Medicine (TCM) research 6. Progress in electronic-structure based computational methods: from small molecules to large molecular systems of biological significance
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19

Green, Peter, Kanti Mardia, Vysaul Nyirongo, and Yann Ruffieux. Bayesian modelling for matching and alignment of biomolecules. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.2.

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This article describes Bayesian modelling for matching and alignment of biomolecules. One particular task where statistical modelling and inference can be useful in scientific understanding of protein structure is that of matching and alignment of two or more proteins. In this regard, statistical shape analysis potentially has something to offer in solving biomolecule matching and alignment problems. The article discusses the use of Bayesian methods for shape analysis to assist with understanding the three-dimensional structure of protein molecules, with a focus on the problem of matching instances of the same structure in the CoMFA (Comparative Molecular Field Analysis) database of steroid molecules. It introduces a Bayesian hierarchical model for pairwise matching and for alignment of multiple configurations before concluding with an overview of some advantages of the Bayesian approach to problems in protein bioinformatics, along with modelling and computation issues, alternative approaches, and directions for future research.
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20

Kahn, Olivier. Molecular Magnetism. Wiley & Sons, Incorporated, John, 1993.

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21

Molecular Magnetism. Dover Publications, Incorporated, 2020.

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22

Hanai, Toshihiko, and Roger M. Smith. Quantitative in Silico Chromatography: Computational Modelling of Molecular Interactions. Royal Society of Chemistry, The, 2014.

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23

Hanai, Toshihiko, and Roger M. Smith. Quantitative in Silico Chromatography: Computational Modelling of Molecular Interactions. Royal Society of Chemistry, The, 2014.

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24

Klinger, Bertram. Mathematical Modelling of Molecular Networks in Cancer Cells Using Modular Response Analysis. Logos Verlag Berlin, 2016.

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25

Schermann, Jean-Pierre. Spectroscopy and Modeling of Biomolecular Building Blocks. Elsevier Science & Technology Books, 2007.

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26

Schermann, Jean-Pierre. Spectroscopy and Modeling of Biomolecular Building Blocks. Elsevier Science, 2007.

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27

Biswas, S. K. Nanotribology. Edited by A. V. Narlikar and Y. Y. Fu. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199533046.013.13.

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This article provides an overview of nanotribology, with particular emphasis on the scalable regime where contact dimensions, topographical perturbations, confinement scale and molecular dimensions are of the same order. It first defines nanotribology and describes some of the instruments used to assess the physics and chemistry of materials in the contact region, including the atomic force microscope, surface force apparatus, and quartz crystal microbalance. It then considers the interfacial phenomena and interaction forces as well as the microscopic origins of friction, focusing on Amonton's Law at the single asperity, atomistic modelling of adhesion and friction, and analysis of coherence in molecular lubrication by means of the Eyring equation. The article also examines the problem of boundary lubrication in two cases: oil in confinement and self-assembled additives in confinement.
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28

Lattman, Eaton E., Thomas D. Grant, and Edward H. Snell. Making the Best Use of Beamtime. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199670871.003.0006.

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Extracting information from scattering data is very sensitive to the quality of the data. In this chapter data quality characterization is described, including initial data processing procedures to alert the user to potential data quality issues. Accurate buffer subtraction is crucial for correct modeling and analysis of SAS data, and mechanisms for identifying buffer subtraction errors are discussed. Examining SAS parameters such as a function of concentration or exposure is very useful for identifying concentration dependent artifacts or radiation damage that, if unnoticed, can be very detrimental to further analysis, including misinterpreting the results and drawing erroneous conclusions. SAS is often used for analyzing flexible molecules in solution that may be difficult to study with other structural techniques. Qualitative and quantitative assessments of flexibility are described.
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29

de Regt, Henk W. Models and Mechanisms. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190652913.003.0006.

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This chapter analyzes the role of mechanical modeling in nineteenth-century physics, showing how precisely mechanical models were used to enhance scientific understanding. It discusses the work and ideas of William Thomson (Lord Kelvin), James Clerk Maxwell, and Ludwig Boltzmann, who advanced explicit views on the function and status of mechanical models, in particular, on their role in providing understanding. A case study of the construction of molecular models to explain the so-called specific heat anomaly highlights the role of conceptual tools in achieving understanding and shows that intelligibility is an epistemically relevant feature of mechanical models. Next, the chapter examines Boltzmann’s Bildtheorie, an interpretation of mechanical models that he developed in response to problems and criticisms of the program of mechanical explanation, and his associated pragmatic conception of understanding. The final section discusses the limitations of mechanical models and Ernst Mach’s criticism of the mechanical program.
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30

Allen, Michael P., and Dominic J. Tildesley. Advanced Monte Carlo methods. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0009.

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This chapter describes the ways in which the Monte Carlo importance sampling method may be adapted to improve the calculation of ensemble averages, particularly those associated with free energy differences. These approaches include umbrella sampling, non-Boltzmann sampling, the Wang–Landau method, and nested sampling. In addition, a range of special techniques have been developed to accelerate the simulation of flexible molecules, such as polymers. These approaches are illustrated with scientific examples and program code. The chapter also explains the analysis of such simulations using techniques such as weighted histograms, and acceptance ratio calculations. Practical advice on selection of methods, parameters, and the direction in which to make comparisons, are given. Monte Carlo methods for modelling phase equilibria and chemical reactions at equilibrium are described.
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31

Computational Systems Bioinformatics U Methods and Biomedical Applications. World Scientific Publishing Company, 2008.

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32

Schmid-Hempel, Paul. Evolutionary Parasitology. 2nd ed. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198832140.001.0001.

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Parasites are ubiquitous and shape almost every aspect of their hosts, including physiology, behaviour, life histories, the structure of the microbiota, and entire communities. Hence, parasitism is one of the most potent forces in nature and, without parasites, the world would look very different. The book gives an overview over the parasite groups and the diversity of defences that hosts have evolved, such as immune systems. Principles of evolutionary biology and ecology analyse major elements of host–parasite interactions, including virulence, infection processes, tolerance, resistance, specificity, memory, polymorphisms, within-host dynamics, diseases spaces, and many other aspects. Genetics is always one of the key elements in these topics. Modelling, furthermore, can predict best strategies for host and parasites. Similarly, the spread of an infectious disease in epidemiology combines with molecular data and genomics. Furthermore, parasites have evolved ways to overcome defences and to manipulate their hosts. Hosts and parasites, therefore, continuously co-evolve, with changes sometimes occurring very rapidly, and sometimes requiring geological times. Many infectious diseases of humans have emerged from a zoonotic origin, in processes governed by the basic principles discussed in the different sections. Hence, this book integrates different fields to study the diversity of host–parasite processes and phenomena. It summarizes the essential topics for the study of evolutionary parasitology and will be useful for a broad audience.
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