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Books on the topic 'Algorithms- Protein'

Author: Grafiati

Published: 6 September 2023

Last updated: 31 July 2025

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1

Rangwala, Huzefa. Introduction to protein structure prediction: Methods and algorithms. Wiley, 2010.

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2

Rangwala, Huzefa, G. Karypis, and G. Karypis. Introduction to protein structure prediction: Methods and algorithms. Wiley, 2010.

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3

Pan, Yi, Jianxin Wang, and Min Li. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118567869.

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4

Donald, Bruce R. Algorithms in structural molecular biology. MIT Press, 2011.

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5

Inge, Jonassen, and Taylor W. R, eds. Protein bioinformatics: An algorithmic approach to sequence and structure analysis. J. Wiley & Sons, 2004.

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6

Gelʹfand, M. S. Predskazanie belok-kodirui͡ushchikh oblasteĭ v nukleotidnykh posledovatelʹnosti͡akh. Nauchnyĭ t͡sentr biologicheskikh issledovaniĭ AN SSSR, 1990.

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7

M, Sansano Allen, and Langley Research Center, eds. Minimizing overhead in parallel algorithms through overlapping communication/computation. National Aeronautics and Space Administration, Langley Research Center, 1997.

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8

Sokolov, Artem, and Oleg Zhdanov. Cryptographic constructions on the basis of functions of multivalued logic. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1045434.

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Symmetric encryption algorithms have been successfully used to protect information during transmission on an open channel. The classical approach to the synthesis of modern cryptographic algorithms and cryptographic primitives on which they are based, is the use of mathematical apparatus of Boolean functions. The authors demonstrate that the use to solve this problem of functions of multivalued logic (FML) allows to largely improve the durability of the cryptographic algorithms and to extend the used algebraic structures. On the other hand, the study of functions of multivalued logic in crypto

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9

Kostyukov, Viktor. Molecular mechanics of biopolymers. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1010677.

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The monograph is devoted to molecular mechanics simulations of biologically important polymers like proteins and nucleic acids. It is shown that the algorithms based on the classical laws of motion of Newton, with high-quality parameterization and sufficient computing resources is able to correctly reproduce and predict the structure and dynamics of macromolecules in aqueous solution. Summarized the development path of biopolymers molecular mechanics, its theoretical basis, current status and prospects for further progress.  It may be useful to researchers specializing in molecular Bioph

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10

Karypis, George, and Huzefa Rangwala. Introduction to Protein Structure Prediction: Methods and Algorithms. Wiley & Sons, Incorporated, John, 2011.

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11

Karypis, George, and Huzefa Rangwala. Introduction to Protein Structure Prediction: Methods and Algorithms. Wiley & Sons, Incorporated, John, 2011.

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12

Karypis, George, and Huzefa Rangwala. Introduction to Protein Structure Prediction: Methods and Algorithms. Wiley & Sons, Incorporated, John, 2010.

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13

Karypis, George, and Huzefa Rangwala. Introduction to Protein Structure Prediction: Methods and Algorithms. Wiley & Sons, Incorporated, John, 2010.

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14

Protein Structure Prediction Using Parallel Linkage Investigating Genetic Algorithms. Storming Media, 1999.

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15

Kurgan, Lukasz. Machine Learning in Bioinformatics of Protein Sequences: Algorithms, Databases and Resources for Modern Protein Bioinformatics. World Scientific Publishing Co Pte Ltd, 2022.

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16

Bonn, Universität, ed. Efficient Approximation Algorithms for Protein Folding in the Hydrophobic-Hydrophilic Model. 2004.

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17

Das, Swagatam, Nanda Dulal Jana, and Jaya Sil. A Metaheuristic Approach to Protein Structure Prediction: Algorithms and Insights from Fitness Landscape Analysis. Springer, 2018.

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18

Das, Swagatam, Nanda Dulal Jana, and Jaya Sil. A Metaheuristic Approach to Protein Structure Prediction: Algorithms and Insights from Fitness Landscape Analysis. Springer, 2018.

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19

Solving the Protein Structure Prediction Problem With Fast Messy Genetic Algorithms (Scaling the Fast Messy Genetic Algorithm to Medium-Sized Peptides by Detecting Secondary Structures). Storming Media, 2001.

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20

Algorithmic and artificial intelligence methods for protein bioinformatics. Wiley, IEEE Computer Society, 2014.

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21

Pan, Yi, Jianxin Wang, and Min Li. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics. Wiley & Sons, Limited, John, 2013.

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22

Pan, Yi, Jianxin Wang, and Min Li. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics. IEEE Computer Society Press, 2013.

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23

Pan, Yi, Jianxin Wang, and Min Li. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics. IEEE Computer Society Press, 2013.

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24

Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics. IEEE Computer Society Press, 2013.

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25

Donald, Bruce R. Algorithms in Structural Molecular Biology. MIT Press, 2011.

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26

Eidhammer, Ingvar, Inge Jonassen, and William R. Taylor. Protein Bioinformatics: An Algorithmic Approach to Sequence and Structure Analysis. Wiley & Sons, Limited, John, 2012.

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27

Ghalayini, Iman. IMPROVED SCATTER SEARCH ALGORITHM FOR PREDICTING PROTEIN STRUCTURES: All-Atoms Model. VDM Verlag Dr. Müller, 2011.

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28

Wang, Jason T. L., Bruce A. Shapiro, and Dennis Shasha, eds. Pattern Discovery in Biomolecular Data. Oxford University Press, 1999. http://dx.doi.org/10.1093/oso/9780195119404.001.0001.

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Finding patterns in biomolecular data, particularly in DNA and RNA, is at the center of modern biological research. These data are complex and growing rapidly, so the search for patterns requires increasingly sophisticated computer methods. Pattern Discovery in Biomolecular Data provides a clear, up-to-date summary of the principal techniques. Each chapter is self-contained, and the techniques are drawn from many fields, including graph theory, information theory, statistics, genetic algorithms, computer visualization, and vision. Since pattern searches often benefit from multiple approaches,

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29

Minimizing overhead in parallel algorithms through overlapping communication/computation. National Aeronautics and Space Administration, Langley Research Center, 1997.

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30

Wexlberger, Simone. Entwicklung Einer Optimierungsmethode Zum Auswerten Von Protein-Nmr-Spektren Mit Hilfe Eines Genetischen Algorithmus. GRIN Verlag GmbH, 2003.

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31

Petersen, Jennifer. How Machines Came to Speak. Duke University Press, 2022. http://dx.doi.org/10.1215/9781478021827.

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In How Machines Came to Speak Jennifer Petersen constructs a genealogy of how legal conceptions of “speech” have transformed over the last century in response to new media technologies. Drawing on media and legal history, Petersen shows that the legal category of speech has varied considerably, evolving from a narrow category of oratory and print publication to a broad, abstract conception encompassing expressive nonverbal actions, algorithms, and data. She examines a series of pivotal US court cases in which new media technologies—such as phonographs, radio, film, and computer code—were integ

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32

Hybrid Media Activism: Ecologies, Imaginaries, Algorithms. Routledge, 2018.

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33

Treré, Emiliano. Hybrid Media Activism: Ecologies, Imaginaries, Algorithms. Taylor & Francis Group, 2018.

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34

Treré, Emiliano. Hybrid Media Activism: Ecologies, Imaginaries, Algorithms. Taylor & Francis Group, 2018.

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35

Treré, Emiliano. Hybrid Media Activism: Ecologies, Imaginaries, Algorithms. Taylor & Francis Group, 2018.

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36

Treré, Emiliano. Hybrid Media Activism: Ecologies, Imaginaries, Algorithms. Taylor & Francis Group, 2018.

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37

Ford, Roger Allan. Trade Secrets and Information Security in the Age of Sports Analytics. Edited by Michael A. McCann. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190465957.013.30.

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The growth of sports analytics has made professional teams more and more reliant on proprietary data and algorithms, which are only valuable as long as they remain unknown to competitors. Teams are, however, relatively poorly equipped to protect these secrets. This chapter reviews five options available to teams looking to protect their secret information: league rules and norms, nondisclosure and noncompete agreements, trade-secrecy law, criminal law, and information-security efforts. None of the legal options are perfect, since breaches can be difficult to detect and legal remedies expose te

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38

Baracos, Vickie E., Sharon M. Watanabe, and Kenneth C. H. Fearon. Aetiology, classification, assessment, and treatment of the anorexia-cachexia syndrome. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199656097.003.0205.

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Anorexia-cachexia is a heterogeneous and multifactorial syndrome most likely driven by systemic inflammation and neuroendocrine activation. Key diagnostic features include reduced appetite, weight loss, and muscle wasting. Key clinical problems include management of anorexia without resort to artificial nutritional support, and muscle wasting that cannot be completely arrested/reversed even with such intervention. Assessment should cover domains such as body stores of energy and protein, food intake, performance status, and factors resulting in excess catabolism. Intervention should be early r

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39

Schäfer, Andreas, and David Meiering, eds. (Ent-)Politisierung? Nomos Verlagsgesellschaft mbH & Co. KG, 2020. http://dx.doi.org/10.5771/9783748904076.

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Contradictory trends of depoliticisation and (re-)politicisation seem to characterise current democratic society. Protest movements and populism polarise opinions on both the streets and social media, while anonymous algorithms or scientific expertise threaten to technocratise political decision-making. At the same time, these phenomena raise the question of democratic theoretical standards of evaluation. This special volume provides a conceptual framework for the analysis and interpretation of these processes and relates previously unconnected fields of research. Theoretical perspectives and

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40

Becker Castellaro, Sebastian, Mariana Carvalho, Alberto Fernandez Gibaja, et al. Artificial Intelligence and Information Integrity: Latin American experiences. Policy Paper No. 34, 2025. International Institute for Democracy and Electoral Assistance (International IDEA) and Fundação Getulio Vargas—Comunicação, 2025. https://doi.org/10.31752/idea.2025.39.

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This policy paper examines the impact of artificial intelligence (AI) on information integrity in electoral contexts across Latin America. Drawing on case studies from Brazil’s and Mexico’s 2024 elections, it analyses how AI tools are used to create, curate and moderate political content online, with particular attention to their effects on marginalized groups such as women, Indigenous communities and LGBTQIA+ individuals. While the use of generative AI in elections remains limited, its potential to undermine democratic discourse and amplify harmful content demands urgent attention. To protect

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41

Carter, Joshua D., Chenxiang Lin, Yan Liu, Hao Yan, and Thomas H. LaBean. DNA-based self-assembly of nanostructures. Edited by A. V. Narlikar and Y. Y. Fu. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199533053.013.24.

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This article examines the DNA-based self-assembly of nanostructures. It first reviews the development of DNA self-assembly and DNA-directed assembly, focusing on the main strategies and building blocks available in the modern molecular construction toolbox, including the design, construction, and analysis of nanostructures composed entirely of synthetic DNA, as well as origami nanostructures formed from a mixture of synthetic and biological DNA. In particular, it considers the stepwise covalent synthesis of DNA nanomaterials, unmediated assembly of DNA nanomaterials, hierarchical assembly, nuc

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42

Garfinkel, Simson L. Differential Privacy. The MIT Press, 2025. https://doi.org/10.7551/mitpress/15354.001.0001.

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A robust yet accessible introduction to the idea, history, and key applications of differential privacy—the gold standard of algorithmic privacy protection. Differential privacy (DP) is an increasingly popular, though controversial, approach to protecting personal data. DP protects confidential data by introducing carefully calibrated random numbers, called statistical noise, when the data is used. Google, Apple, and Microsoft have all integrated the technology into their software, and the US Census Bureau used DP to protect data collected in the 2020 census. In this book, Simson Garfinkel pre

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43

Lattman, Eaton E., Thomas D. Grant, and Edward H. Snell. Biological Small Angle Scattering. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199670871.001.0001.

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The technique of small angle solution scattering has been revolutionized in the last two decades. Exponential increases in computing power, parallel algorithm development, and the development of synchrotron, free-electron X-ray sources, and neutron sources, have combined to allow new classes of studies for biological specimens. These include time-resolved experiments in which functional motions of proteins are monitored on a picosecond timescale, and the first steps towards determining actual electron density fluctuations within particles. In addition, more traditional experiments involving th

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44

Prassl, Jeremias. Humans as a Service. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198797012.001.0001.

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The rise of the gig economy is disrupting business models across the globe. Platforms’ digital work intermediation has had a profound impact on traditional conceptions of the employment relationship. The completion of ‘tasks’, ‘gigs’, or ‘rides’ in the (digital) crowd fundamentally challenges our understanding of work in modern labour markets: gone are the stable employment relationships between firms and workers, replaced by a world in which everybody can be ‘their own boss’ and enjoy the rewards—and face the risks—of independent businesses. Is this the future of work? What are the benefits a

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