Download or read book Machine Learning Meets Quantum Physics written by Kristof T. Schütt and published by Springer Nature. This book was released on 2020-06-03 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designing molecules and materials with desired properties is an important prerequisite for advancing technology in our modern societies. This requires both the ability to calculate accurate microscopic properties, such as energies, forces and electrostatic multipoles of specific configurations, as well as efficient sampling of potential energy surfaces to obtain corresponding macroscopic properties. Tools that can provide this are accurate first-principles calculations rooted in quantum mechanics, and statistical mechanics, respectively. Unfortunately, they come at a high computational cost that prohibits calculations for large systems and long time-scales, thus presenting a severe bottleneck both for searching the vast chemical compound space and the stupendously many dynamical configurations that a molecule can assume. To overcome this challenge, recently there have been increased efforts to accelerate quantum simulations with machine learning (ML). This emerging interdisciplinary community encompasses chemists, material scientists, physicists, mathematicians and computer scientists, joining forces to contribute to the exciting hot topic of progressing machine learning and AI for molecules and materials. The book that has emerged from a series of workshops provides a snapshot of this rapidly developing field. It contains tutorial material explaining the relevant foundations needed in chemistry, physics as well as machine learning to give an easy starting point for interested readers. In addition, a number of research papers defining the current state-of-the-art are included. The book has five parts (Fundamentals, Incorporating Prior Knowledge, Deep Learning of Atomistic Representations, Atomistic Simulations and Discovery and Design), each prefaced by editorial commentary that puts the respective parts into a broader scientific context.

Download or read book Prediction of Protein Secondary Structure written by Yaoqi Zhou and published by Humana. This book was released on 2016-10-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thorough volume explores predicting one-dimensional functional properties, functional sites in particular, from protein sequences, an area which is getting more and more attention. Beginning with secondary structure prediction based on sequence only, the book continues by exploring secondary structure prediction based on evolution information, prediction of solvent accessible surface areas and backbone torsion angles, model building, global structural properties, functional properties, as well as visualizing interior and protruding regions in proteins. Written for the highly successful Methods in Molecular Biology series, the chapters include the kind of detail and implementation advice to ensure success in the laboratory. Practical and authoritative, Prediction of Protein Secondary Structure serves as a vital guide to numerous state-of-the-art techniques that are useful for computational and experimental biologists.

Download or read book Homology Molecular Modeling written by Rafael Trindade Maia and published by BoD – Books on Demand. This book was released on 2021-03-10 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: Homology modeling is an extremely useful and versatile technique that is gaining more and more space and demand in research in computational and theoretical biology. This book, “Homology Molecular Modeling - Perspectives and Applications”, brings together unpublished chapters on this technique. In this book, 7 chapters are intimately related to the theme of molecular modeling, carefully selected and edited for academic and scientific readers. It is an indispensable read for anyone interested in the areas of bioinformatics and computational biology. Divided into 4 sections, the reader will have a didactic and comprehensive view of the theme, with updated and relevant concepts on the subject. This book was organized from researchers to researchers with the aim of spreading the fascinating area of molecular modeling by homology.

Download or read book Molecular Biology of the Cell written by and published by . This book was released on 2002 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computational Protein Design written by Ilan Samish and published by Humana. This book was released on 2016-12-03 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim this volume is to present the methods, challenges, software, and applications of this widespread and yet still evolving and maturing field. Computational Protein Design, the first book with this title, guides readers through computational protein design approaches, software and tailored solutions to specific case-study targets. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Computational Protein Design aims to ensure successful results in the further study of this vital field.

Download or read book Protein Structure Prediction written by Mohammed Zaki and published by Springer Science & Business Media. This book was released on 2007-09-12 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers elements of both the data-driven comparative modeling approach to structure prediction and also recent attempts to simulate folding using explicit or simplified models. Despite the unsolved mystery of how a protein folds, advances are being made in predicting the interactions of proteins with other molecules. Also rapidly advancing are the methods for solving the inverse folding problem, the problem of finding a sequence to fit a structure. This book focuses on the various computational methods for prediction, their successes and their limitations, from the perspective of their most well known practitioners.

Download or read book Concepts and Experimental Protocols of Modelling and Informatics in Drug Design written by Om Silakari and published by Academic Press. This book was released on 2020-11-05 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Concepts and Experimental Protocols of Modelling and Informatics in Drug Design discusses each experimental protocol utilized in the field of bioinformatics, focusing especially on computer modeling for drug development. It helps the user in understanding the field of computer-aided molecular modeling (CAMM) by presenting solved exercises and examples. The book discusses topics such as fundamentals of molecular modeling, QSAR model generation, protein databases and how to use them to select and analyze protein structure, and pharmacophore modeling for drug targets. Additionally, it discusses data retrieval system, molecular surfaces, and freeware and online servers. The book is a valuable source for graduate students and researchers on bioinformatics, molecular modeling, biotechnology and several members of biomedical field who need to understand more about computer-aided molecular modeling. - Presents exercises with solutions to aid readers in validating their own protocol - Brings a thorough interpretation of results of each exercise to help readers compare them to their own study - Explains each parameter utilized in the algorithms to help readers understand and manipulate various features of molecules and target protein to design their study

Download or read book Understanding Bioinformatics written by Marketa J. Zvelebil and published by Garland Science. This book was released on 2008 with total page 804 pages. Available in PDF, EPUB and Kindle. Book excerpt: Suitable for advanced undergraduates & postgraduates, this book provides a definitive guide to bioinformatics. It takes a conceptual approach & guides the reader from first principles through to an understanding of the computational techniques & the key algorithms.

Download or read book Introduction to Computational Biology written by Michael S. Waterman and published by CRC Press. This book was released on 2018-05-02 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biology is in the midst of a era yielding many significant discoveries and promising many more. Unique to this era is the exponential growth in the size of information-packed databases. Inspired by a pressing need to analyze that data, Introduction to Computational Biology explores a new area of expertise that emerged from this fertile field- the combination of biological and information sciences. This introduction describes the mathematical structure of biological data, especially from sequences and chromosomes. After a brief survey of molecular biology, it studies restriction maps of DNA, rough landmark maps of the underlying sequences, and clones and clone maps. It examines problems associated with reading DNA sequences and comparing sequences to finding common patterns. The author then considers that statistics of pattern counts in sequences, RNA secondary structure, and the inference of evolutionary history of related sequences. Introduction to Computational Biology exposes the reader to the fascinating structure of biological data and explains how to treat related combinatorial and statistical problems. Written to describe mathematical formulation and development, this book helps set the stage for even more, truly interdisciplinary work in biology.

Download or read book Computational Methods for Protein Structure Prediction and Modeling written by Ying Xu and published by Springer Science & Business Media. This book was released on 2010-05-05 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume Two of this two-volume sequence presents a comprehensive overview of protein structure prediction methods and includes protein threading, De novo methods, applications to membrane proteins and protein complexes, structure-based drug design, as well as structure prediction as a systems problem. A series of appendices review the biological and chemical basics related to protein structure, computer science for structural informatics, and prerequisite mathematics and statistics.

Download or read book Computer Assisted Modeling written by National Research Council and published by National Academies Press. This book was released on 1987-02-01 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: In much of biology, the search for understanding the relation between structure and function is now taking place at the macromolecular level. Proteins, nucleic acids, and polysaccharides are macromolecule--polymers formed from families of simpler subunits. Because of their size and complexity, the polymers are capable of both inter- and intramolecular interactions. These interactions confer upon the polymers distinctive three-dimensional shapes. These tertiary configurations, in turn, determine the function of the macromolecule. Computers have become so inextricably involved in empirical studies of three-dimensional macromolecular structure that mathematical modeling, or theory, and experimental approaches are interrelated aspects of a single enterprise.

Download or read book From Protein Structure to Function with Bioinformatics written by Daniel John Rigden and published by Springer Science & Business Media. This book was released on 2008-12-11 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proteins lie at the heart of almost all biological processes and have an incredibly wide range of activities. Central to the function of all proteins is their ability to adopt, stably or sometimes transiently, structures that allow for interaction with other molecules. An understanding of the structure of a protein can therefore lead us to a much improved picture of its molecular function. This realisation has been a prime motivation of recent Structural Genomics projects, involving large-scale experimental determination of protein structures, often those of proteins about which little is known of function. These initiatives have, in turn, stimulated the massive development of novel methods for prediction of protein function from structure. Since model structures may also take advantage of new function prediction algorithms, the first part of the book deals with the various ways in which protein structures may be predicted or inferred, including specific treatment of membrane and intrinsically disordered proteins. A detailed consideration of current structure-based function prediction methodologies forms the second part of this book, which concludes with two chapters, focusing specifically on case studies, designed to illustrate the real-world application of these methods. With bang up-to-date texts from world experts, and abundant links to publicly available resources, this book will be invaluable to anyone who studies proteins and the endlessly fascinating relationship between their structure and function.

Download or read book Coarse Graining of Condensed Phase and Biomolecular Systems written by Gregory A. Voth and published by CRC Press. This book was released on 2008-09-22 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploring recent developments in the field, Coarse-Graining of Condensed Phase and Biomolecular Systems examines systematic ways of constructing coarse-grained representations for complex systems. It explains how this approach can be used in the simulation and modeling of condensed phase and biomolecular systems. Assembling some of the most influential, world-renowned researchers in the field, this book covers the latest developments in the coarse-grained molecular dynamics simulation and modeling of condensed phase and biomolecular systems. Each chapter focuses on specific examples of evolving coarse-graining methodologies and presents results for a variety of complex systems. The contributors discuss the minimalist, inversion, and multiscale approaches to coarse-graining, along with the emerging challenges of coarse-graining. They also connect atomic-level information with new coarse-grained representations of complex systems, such as lipid bilayers, proteins, peptides, and DNA.

Download or read book Biological Sequence Analysis written by Richard Durbin and published by Cambridge University Press. This book was released on 1998-04-23 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.

Download or read book On protein structure function and modularity from an evolutionary perspective written by Robert Pilstål and published by Linköping University Electronic Press. This book was released on 2018-05-31 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are compounded entities, given life by a complex molecular machinery. When studying these molecules we have to make sense of a diverse set of dynamical nanostructures with wast and intricate patterns of interactions. Protein polymers is one of the major groups of building blocks of such nanostructures which fold up into more or less distinct three dimensional structures. Due to their shape, dynamics and chemical properties proteins are able to perform a plethora of specific functions essential to all known cellular lifeforms. The connection between protein sequence, translated into protein structure and in the continuation into protein function is well accepted but poorly understood. Malfunction in the process of protein folding is known to be implicated in natural aging, cancer and degenerative diseases such as Alzheimer's. Protein folds are described hierarchically by structural ontologies such as SCOP, CATH and Pfam all which has yet to succeed in deciphering the natural language of protein function. These paradigmatic views centered on protein structure fail to describe more mutable entities, such as intrinsically disordered proteins (IDPs) which lack a clear defined structure. As of 2012, about two thirds of cancer patients was predicted to survive past 5 years of diagnosis. Despite this, about a third do not survive and numerous of successfully treated patients suffer from secondary conditions due to chemotherapy, surgery and the like. In order to handle cancer more efficiently we have to better understand the underlying molecular mechanisms. Elusive to standard methods of investigation, IDPs have a central role in pathology; dysfunction in IDPs are key factors in cellular system failures such as cancer, as many IDPs are hub regulators for major cell functions. These IDPs carry short conserved functional boxes, that are not described by known ontologies, which suggests the existence of a smaller entity. In an investigation of a pair of such boxes of c-MYC, a plausible structural model of its interacting with Pin1 emerged, but such a model still leaves the observer with a puzzle of understanding the actual function of that interaction. If the protein is represented as a graph and modeled as the interaction patterns instead of as a structural entity, another picture emerges. As a graph, there is a parable from that of the boxes of IDPs, to that of sectors of allosterically connected residues and the theory of foldons and folding units. Such a description is also useful in deciphering the implications of specific mutations. In order to render a functional description feasible for both structured and disordered proteins, there is a need of a model separate from form and structure. Realized as protein primes, patterns of interaction, which has a specific function that can be defined as prime interactions and context. With function defined as interactions, it might be possible that the discussion of proteins and their mechanisms is thereby simplified to the point rendering protein structural determination merely supplementary to understanding protein function. Människan byggs upp av celler, de i sin tur består av än mindre beståndsdelar; livets molekyler. Dessa fungerar som mekaniska byggstenar, likt maskiner och robotar som sliter vid fabrikens band; envar utförandes en absolut nödvändig funktion för cellens, och hela kroppens, fortsatta överlevnad. De av livets molekyler som beskrivs centralt i den här avhandling är proteiner, vilka i sin tur består utav en lång kedja, med olika typer av länkar, som likt garn lindar upp sig i ett nystan av en (mer eller mindre...) bestämd struktur som avgör dess roll och funktion i cellen. Intrinsiellt oordnade proteiner (IDP) går emot denna enkla åskådning; de är proteiner som saknar struktur och beter sig mer likt spaghetti i vatten än en maskin. IDP är ändå funktionella och bär på centrala roller i cellens maskineri; exempel är oncoproteinet c-Myc som agerar "gaspedal" för cellen - fel i c-Myc's funktion leder till att cellerna löper amok, delar sig hejdlöst och vi får cancer. Man har upptäckt att c-Myc har en ombytlig struktur vi inte kan se; studier av punktvisa förändringar, mutationer, i kedjan av byggstenar hos c-Myc visar att många länkar har viktiga roller i funktionen. Detta ger oss bättre förståelse om cancer men samtidigt är laboratoriearbetet både komplicerat och dyrt; här kan evolutionen vägleda oss och avslöja hemligheterna snabbare. Molekylär evolution studeras genom att beräkna variation i proteinkedjan mellan besläktade arter som finns lagrade i databaser; detta visar snabbt, via nätverksanalys och grafteori, vilka delar av proteinet som är centrala och kopplade till varandra av nödvändighet för artens fortlevnad. På så vis hjälper evolutionen oss att förstå proteinfunktioner via modeller baserade på proteinernas interaktioner snarare än deras struktur. Samma modeller kan nyttjas för att förstå dynamiska förlopp och skillnader mellan normala och patologiska varianter av proteiner; mutationer kan uppstå i vår arvsmassa som kan leda till sjukdom. Genom analys av proteinernas kopplingsnätverk i grafmodellerna kan man bättre förutsäga vilka mutationer som är farligare än andra. Dessutom har det visat sig att en sådan representation kan ge bättre förståelse för den normala funktionen hos ett protein än vad en proteinstruktur kan. Här introduceras även konceptet proteinprimärer, vilket är en abstrakt representation av proteiner centrerad på deras interaktiva mönster, snarare än på partikulär form och struktur. Det är en förhoppning att en sådan representation skall förenkla diskussionen anbelangande proteinfunktion så till den grad att strukturbestämmelse av proteiner, som är en mycket kostsam och tidskrävande process, till viss mån kan anses vara sekundär i betydelse jämfört med funktionellt modellerande baserat på evolutionära data extraherade ur våra sekvensdatabaser.

Download or read book Protein Actions Principles and Modeling written by Ivet Bahar and published by Garland Science. This book was released on 2017-02-14 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Protein Actions: Principles and Modeling is aimed at graduates, advanced undergraduates, and any professional who seeks an introduction to the biological, chemical, and physical properties of proteins. Broadly accessible to biophysicists and biochemists, it will be particularly useful to student and professional structural biologists and molecular biophysicists, bioinformaticians and computational biologists, biological chemists (particularly drug designers) and molecular bioengineers. The book begins by introducing the basic principles of protein structure and function. Some readers will be familiar with aspects of this, but the authors build up a more quantitative approach than their competitors. Emphasizing concepts and theory rather than experimental techniques, the book shows how proteins can be analyzed using the disciplines of elementary statistical mechanics, energetics, and kinetics. These chapters illuminate how proteins attain biologically active states and the properties of those states. The book ends with a synopsis the roles of computational biology and bioinformatics in protein science.

Download or read book Introduction to Protein Structure Prediction written by Huzefa Rangwala and published by John Wiley & Sons. This book was released on 2011-03-16 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: A look at the methods and algorithms used to predict protein structure A thorough knowledge of the function and structure of proteins is critical for the advancement of biology and the life sciences as well as the development of better drugs, higher-yield crops, and even synthetic bio-fuels. To that end, this reference sheds light on the methods used for protein structure prediction and reveals the key applications of modeled structures. This indispensable book covers the applications of modeled protein structures and unravels the relationship between pure sequence information and three-dimensional structure, which continues to be one of the greatest challenges in molecular biology. With this resource, readers will find an all-encompassing examination of the problems, methods, tools, servers, databases, and applications of protein structure prediction and they will acquire unique insight into the future applications of the modeled protein structures. The book begins with a thorough introduction to the protein structure prediction problem and is divided into four themes: a background on structure prediction, the prediction of structural elements, tertiary structure prediction, and functional insights. Within those four sections, the following topics are covered: Databases and resources that are commonly used for protein structure prediction The structure prediction flagship assessment (CASP) and the protein structure initiative (PSI) Definitions of recurring substructures and the computational approaches used for solving sequence problems Difficulties with contact map prediction and how sophisticated machine learning methods can solve those problems Structure prediction methods that rely on homology modeling, threading, and fragment assembly Hybrid methods that achieve high-resolution protein structures Parts of the protein structure that may be conserved and used to interact with other biomolecules How the loop prediction problem can be used for refinement of the modeled structures The computational model that detects the differences between protein structure and its modeled mutant Whether working in the field of bioinformatics or molecular biology research or taking courses in protein modeling, readers will find the content in this book invaluable.