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Biomolecular Interactions Using Machine Learning
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Book Synopsis Machine Learning Methodologies To Study Molecular Interactions by : Elif Ozkirimli
Download or read book Machine Learning Methodologies To Study Molecular Interactions written by Elif Ozkirimli and published by Frontiers Media SA. This book was released on 2022-01-21 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dr. Elif Ozkirimli is a full time employee of F. Hoffmann-La Roche AG, Switzerland and Dr. Artur Yakimovich is a full time employee of Roche Products Limited, UK. All other Topic Editors declare no competing interests with regards to the Research Topic.
Book Synopsis Biomolecular Interactions Using Machine Learning by : Joel Robert Bock
Download or read book Biomolecular Interactions Using Machine Learning written by Joel Robert Bock and published by . This book was released on 2003 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Biomolecular Interfaces by : Ariel Fernández Stigliano
Download or read book Biomolecular Interfaces written by Ariel Fernández Stigliano and published by Springer. This book was released on 2015-04-20 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book focuses on the aqueous interface of biomolecules, a vital yet overlooked area of biophysical research. Most biological phenomena cannot be fully understood at the molecular level without considering interfacial behavior. The author presents conceptual advances in molecular biophysics that herald the advent of a new discipline, epistructural biology, centered on the interactions of water and bio molecular structures across the interface. The author introduces powerful theoretical and computational resources in order to address fundamental topics such as protein folding, the physico-chemical basis of enzyme catalysis and protein associations. On the basis of this information, a multi-disciplinary approach is used to engineer therapeutic drugs and to allow substantive advances in targeted molecular medicine. This book will be of interest to scientists, students and practitioners in the fields of chemistry, biophysics and biomedical engineering.
Book Synopsis Biomolecular Interactions Part A by :
Download or read book Biomolecular Interactions Part A written by and published by Academic Press. This book was released on 2021-10-29 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biomolecular Interactions: Part A, Volume 166, the latest release in the Methods in Cell Biology series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics in cell biology. Each chapter is written by an international board of authors. - Provides the authority and expertise of leading contributors from an international board of authors - Presents the latest release in the Methods in Cell Biology series - Updated release includes the latest information on biomolecular interactions instead of protein-protein interactions
Book Synopsis Biological Data Mining in Protein Interaction Networks by : Li, Xiao-Li
Download or read book Biological Data Mining in Protein Interaction Networks written by Li, Xiao-Li and published by IGI Global. This book was released on 2009-05-31 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The goal of this book is to disseminate research results and best practices from cross-disciplinary researchers and practitioners interested in, and working on bioinformatics, data mining, and proteomics"--Provided by publisher.
Book Synopsis Biomolecular Interactions Part B by :
Download or read book Biomolecular Interactions Part B written by and published by Academic Press. This book was released on 2022-05-25 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biomolecular Interactions: Part A, Volume 169, the latest release in the Methods in Cell Biology series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Emerging Mechanisms of Targeted Protein Degradation by Molecular Glues, Design and use of programmable DNA Hydrogels, Oligomerization of membrane receptors: Approaches to measure in live cells, Interactions of alpha-synuclein with biomolecules, Gel-electrophoresis based method for biomolecular interaction, Recombinant centrosome expression in bacterial system, Reconstituting CCL5-CCR5 complex for structural and mechanistic analysis, Protein engineering and design in ion channel receptors, and much more. - Provides the authority and expertise of leading contributors from an international board of authors - Presents the latest release in the Methods in Cell Biology series - Updated release includes the latest information on biomolecular interactions instead of protein-protein interactions
Book Synopsis Protein-Nucleic Acid Interactions by : Phoebe A. Rice
Download or read book Protein-Nucleic Acid Interactions written by Phoebe A. Rice and published by Royal Society of Chemistry. This book was released on 2008-05-22 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides both in-depth background and up-to-date information in this area. The chapters are organized by general themes and principles, written by experts who illustrate topics with current findings. Topics covered include: - the role of ions and hydration in protein-nucleic acid interactions - transcription factors and combinatorial specificity - indirect readout of DNA sequence - single-stranded nucleic acid binding proteins - nucleic acid junctions and proteins, - RNA protein recognition - recognition of DNA damage. It will be a key reference for both advanced students and established scientists wishing to broaden their horizons.
Book Synopsis Explainable AI: Interpreting, Explaining and Visualizing Deep Learning by : Wojciech Samek
Download or read book Explainable AI: Interpreting, Explaining and Visualizing Deep Learning written by Wojciech Samek and published by Springer Nature. This book was released on 2019-09-10 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.
Book Synopsis Biomolecular Networks by : Luonan Chen
Download or read book Biomolecular Networks written by Luonan Chen and published by John Wiley & Sons. This book was released on 2009-06-29 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Alternative techniques and tools for analyzing biomolecular networks With the recent rapid advances in molecular biology, high-throughput experimental methods have resulted in enormous amounts of data that can be used to study biomolecular networks in living organisms. With this development has come recognition of the fact that a complicated living organism cannot be fully understood by merely analyzing individual components. Rather, it is the interactions of components or biomolecular networks that are ultimately responsible for an organism's form and function. This book addresses the important need for a new set of computational tools to reveal essential biological mechanisms from a systems biology approach. Readers will get comprehensive coverage of analyzing biomolecular networks in cellular systems based on available experimental data with an emphasis on the aspects of network, system, integration, and engineering. Each topic is treated in depth with specific biological problems and novel computational methods: GENE NETWORKS—Transcriptional regulation; reconstruction of gene regulatory networks; and inference of transcriptional regulatory networks PROTEIN INTERACTION NETWORKS—Prediction of protein-protein interactions; topological structure of biomolecular networks; alignment of biomolecular networks; and network-based prediction of protein function METABOLIC NETWORKS AND SIGNALING NETWORKS—Analysis, reconstruction, and applications of metabolic networks; modeling and inference of signaling networks; and other topics and new trends In addition to theoretical results and methods, many computational software tools are referenced and available from the authors' Web sites. Biomolecular Networks is an indispensable reference for researchers and graduate students in bioinformatics, computational biology, systems biology, computer science, and applied mathematics.
Book Synopsis Statistical and Machine Learning Approaches for Network Analysis by : Matthias Dehmer
Download or read book Statistical and Machine Learning Approaches for Network Analysis written by Matthias Dehmer and published by John Wiley & Sons. This book was released on 2012-06-26 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internationally renowned researchers in the field of interdisciplinary network theory, the book presents current and classical methods to analyze networks statistically. Methods from machine learning, data mining, and information theory are strongly emphasized throughout. Real data sets are used to showcase the discussed methods and topics, which include: A survey of computational approaches to reconstruct and partition biological networks An introduction to complex networks—measures, statistical properties, and models Modeling for evolving biological networks The structure of an evolving random bipartite graph Density-based enumeration in structured data Hyponym extraction employing a weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross-disciplinary courses in applied discrete mathematics, bioinformatics, pattern recognition, and computer science. The book is also a valuable reference for researchers and practitioners in the fields of applied discrete mathematics, machine learning, data mining, and biostatistics.
Book Synopsis Molecular Docking for Computer-Aided Drug Design by : Mohane S. Coumar
Download or read book Molecular Docking for Computer-Aided Drug Design written by Mohane S. Coumar and published by Academic Press. This book was released on 2021-02-17 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: Molecular Docking for Computer-Aided Drug Design: Fundamentals, Techniques, Resources and Applications offers in-depth coverage on the use of molecular docking for drug design. The book is divided into three main sections that cover basic techniques, tools, web servers and applications. It is an essential reference for students and researchers involved in drug design and discovery. - Covers the latest information and state-of-the-art trends in structure-based drug design methodologies - Includes case studies that complement learning - Consolidates fundamental concepts and current practice of molecular docking into one convenient resource
Book Synopsis Methods and Algorithms for Molecular Docking-Based Drug Design and Discovery by : Dastmalchi, Siavoush
Download or read book Methods and Algorithms for Molecular Docking-Based Drug Design and Discovery written by Dastmalchi, Siavoush and published by IGI Global. This book was released on 2016-05-03 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: The role of technology in the medical field has resulted in significant developments within the pharmaceutical industry. Computational approaches have emerged as a crucial method in further advancing drug design and development. Methods and Algorithms for Molecular Docking-Based Drug Design and Discovery presents emerging research on the application of computer-assisted design methods for drugs, emphasizing the benefits and improvements that molecular docking has caused within the pharmaceutical industry. Focusing on validation methods, search algorithms, and scoring functions, this book is a pivotal resource for professionals, researchers, students, and practitioners in the field of theoretical and computational chemistry.
Book Synopsis Molecular advances and applications of machine learning in understanding autism and comorbid psychiatric disorders by : Salam Salloum-Asfar
Download or read book Molecular advances and applications of machine learning in understanding autism and comorbid psychiatric disorders written by Salam Salloum-Asfar and published by Frontiers Media SA. This book was released on 2023-07-24 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Modeling and Machine Learning for Molecular Biology by : Alan Moses
Download or read book Statistical Modeling and Machine Learning for Molecular Biology written by Alan Moses and published by CRC Press. This book was released on 2017-01-06 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: • Assumes no background in statistics or computers • Covers most major types of molecular biological data • Covers the statistical and machine learning concepts of most practical utility (P-values, clustering, regression, regularization and classification) • Intended for graduate students beginning careers in molecular biology, systems biology, bioengineering and genetics
Book Synopsis Advances in Molecular Docking and Structure-Based Modelling by : Alexandre G. De Brevern
Download or read book Advances in Molecular Docking and Structure-Based Modelling written by Alexandre G. De Brevern and published by Frontiers Media SA. This book was released on 2022-02-24 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Advances in Protein Molecular and Structural Biology Methods by : Timir Tripathi
Download or read book Advances in Protein Molecular and Structural Biology Methods written by Timir Tripathi and published by Academic Press. This book was released on 2022-01-14 with total page 716 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Protein Molecular and Structural Biology Methods offers a complete overview of the latest tools and methods applicable to the study of proteins at the molecular and structural level. The book begins with sections exploring tools to optimize recombinant protein expression and biophysical techniques such as fluorescence spectroscopy, NMR, mass spectrometry, cryo-electron microscopy, and X-ray crystallography. It then moves towards computational approaches, considering structural bioinformatics, molecular dynamics simulations, and deep machine learning technologies. The book also covers methods applied to intrinsically disordered proteins (IDPs)followed by chapters on protein interaction networks, protein function, and protein design and engineering. It provides researchers with an extensive toolkit of methods and techniques to draw from when conducting their own experimental work, taking them from foundational concepts to practical application. - Presents a thorough overview of the latest and emerging methods and technologies for protein study - Explores biophysical techniques, including nuclear magnetic resonance, X-ray crystallography, and cryo-electron microscopy - Includes computational and machine learning methods - Features a section dedicated to tools and techniques specific to studying intrinsically disordered proteins
Book Synopsis Reverse Engineering of Regulatory Networks by : Sudip Mandal
Download or read book Reverse Engineering of Regulatory Networks written by Sudip Mandal and published by Springer Nature. This book was released on 2023-11-07 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume details the development of updated dry lab and wet lab based methods for the reconstruction of Gene regulatory networks (GRN). Chapters guide readers through culprit genes, in-silico drug discovery techniques, genome-wide ChIP-X data, high-Throughput Transcriptomic Data Exome Sequencing, Next-Generation Sequencing, Fuorescence Spectroscopy, data analysis in Bioinformatics, Computational Biology, and S-system based modeling of GRN. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Reverse Engineering of Regulatory Networks aims to be a useful and practical guide to new researchers and experts looking to expand their knowledge.
