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Genetic Algorithm For Ab Initio Protein Structure Prediction
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Book Synopsis Genetic Algorithm for Ab Initio Protein Structure Prediction by : Hoque Tamjidul
Download or read book Genetic Algorithm for Ab Initio Protein Structure Prediction written by Hoque Tamjidul and published by LAP Lambert Academic Publishing. This book was released on 2013 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Protein is a sequence of amino acids bounded into a linear chain that adopts a specific folded three-dimensional (3D) shape. This specific folded shape enables protein to perform specific tasks. Amongst various available computational methods, the protein structure prediction by the ab initio approach is promising and can help to unravel the relationship between sequence and its associated structure. This book is focused on the ab initio protein structure prediction (PSP), by developing novel Genetic Algorithm (GA) for an efficient and effective conformation search of low resolution models. The book also proposes a novel low resolution model, called hHPNX model providing more accurate predictions compared to the existing low resolution HP models. Extensions of these developed algorithms are very promising for high resolution models.
Book Synopsis Genetic Algorithm for Ab Initio Protein Structure Prediction Based on Low Resolution Models by : Md Tamjidul Hoque
Download or read book Genetic Algorithm for Ab Initio Protein Structure Prediction Based on Low Resolution Models written by Md Tamjidul Hoque and published by . This book was released on 2007 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis AB Initio Protein Tertiary Structure Prediction by :
Download or read book AB Initio Protein Tertiary Structure Prediction written by and published by . This book was released on 2001 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the period from September 1, 1998 until September 1, 2000 I was awarded a Sloan/DOE postdoctoral fellowship to work in collaboration with Professor John Moult at the Center for Advanced Research in Biotechnology (CARB). Our research project, ''Ab Initio Protein Tertiary Structure Prediction and a Comparative Genetic algorithm'', yielded promising initial results. In short, the project is designed to predict the native fold, or native tertiary structure, of a given protein by inputting only the primary sequence of the protein (one or three letter code). The algorithm is based on a general learning, or evolutionary algorithm and is called Genetic Algorithm (GAS). In our particular application of GAS, we search for native folds, or lowest energy structures, using two different descriptions for the interactions of the atoms and residues in a given protein sequence. One potential energy function is based on a free energy description, while the other function is a threading potential derived by Moult and Samudrala. This modified genetic algorithm was loosely termed a Comparative Genetic Algorithm and was designed to search for native folded structures on both potential energy surfaces, simultaneously. We tested the algorithm on a series of peptides ranging from 11 to 15 residues in length, which are thought to be independent folding units and thereby will fold to native structures independent of the larger protein environment. Our initial results indicated a modest increase in accuracy, as compared to a standard Genetic Algorithm. We are now in the process of improving the algorithm to increase the sensitivity to other inputs, such as secondary structure requirements. The project did not involve additional students and as of yet, the work has not been published.
Book Synopsis Protein Structure Prediction by : David Webster
Download or read book Protein Structure Prediction written by David Webster and published by Springer Science & Business Media. This book was released on 2008-02-03 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: The number of protein sequences grows each year, yet the number of structures deposited in the Protein Data Bank remains relatively small. The importance of protein structure prediction cannot be overemphasized, and this volume is a timely addition to the literature in this field. Protein Structure Prediction: Methods and Protocols is a departure from the normal Methods in Molecular Biology series format. By its very nature, protein structure prediction demands that there be a greater mix of theoretical and practical aspects than is normally seen in this series. This book is aimed at both the novice and the experienced researcher who wish for detailed inf- mation in the field of protein structure prediction; a major intention here is to include important information that is needed in the day-to-day work of a research scientist, important information that is not always decipherable in scientific literature. Protein Structure Prediction: Methods and Protocols covers the topic of protein structure prediction in an eclectic fashion, detailing aspects of pred- tion that range from sequence analysis (a starting point for many algorithms) to secondary and tertiary methods, on into the prediction of docked complexes (an essential point in order to fully understand biological function). As this volume progresses, the authors contribute their expert knowledge of protein structure prediction to many disciplines, such as the identification of motifs and domains, the comparative modeling of proteins, and ab initio approaches to protein loop, side chain, and protein prediction.
Book Synopsis A Metaheuristic Approach to Protein Structure Prediction by : Nanda Dulal Jana
Download or read book A Metaheuristic Approach to Protein Structure Prediction written by Nanda Dulal Jana and published by Springer. This book was released on 2018-03-05 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces characteristic features of the protein structure prediction (PSP) problem. It focuses on systematic selection and improvement of the most appropriate metaheuristic algorithm to solve the problem based on a fitness landscape analysis, rather than on the nature of the problem, which was the focus of methodologies in the past. Protein structure prediction is concerned with the question of how to determine the three-dimensional structure of a protein from its primary sequence. Recently a number of successful metaheuristic algorithms have been developed to determine the native structure, which plays an important role in medicine, drug design, and disease prediction. This interdisciplinary book consolidates the concepts most relevant to protein structure prediction (PSP) through global non-convex optimization. It is intended for graduate students from fields such as computer science, engineering, bioinformatics and as a reference for researchers and practitioners.
Book Synopsis 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) by : Steven R. Michaud
Download or read book 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) written by Steven R. Michaud and published by . This book was released on 2001-03-01 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ability to accurately predict a polypeptide's molecular structure given its amino acid sequence is important to numerous scientific, medical, and engineering applications. Studies have been conducted in the application of Genetic Algorithms (GAs) to this problem with promising initial results. In this thesis report, we use the fast messy Genetic Algorithm (fmGA) to attempt to find the minimization of an empirical CHARMM energy model and generation of the associated conformation. Previous work has shown that the fmGA provided favorable results, at least when applied to the pentapeptide Met-Enkephalin. We extend these results to a larger Polyalinine peptide by utilizing secondary structure information as both searching constraints and seeding the initial population. Additional efforts where conducted to improve the performance of the algorithm with respect to solving the Protein Structure Prediction (PSP) problem through a short-circuiting operator--where complete evaluation of the fitness function is halted if initial results are not promising, and by conducting additional searches on faster machines in a heterogeneous environment. Results indicate that, on average, this localized search tends to produce better final solutions. Finally, the fmGA as applied to the PSP problem is analyzed and shown to have improved performance and effectiveness.
Book Synopsis Evolutionary Algorithms in Molecular Design by : David E. Clark
Download or read book Evolutionary Algorithms in Molecular Design written by David E. Clark and published by John Wiley & Sons. This book was released on 2008-11-21 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: When trying to find new methods and problem-solving strategies for their research, scientists often turn to nature for inspiration. An excellent example of this is the application of Darwin's Theory of Evolution, particularly the notion of the 'survival of the fittest', in computer programs designed to search for optimal solutions to many kinds of problems. These 'evolutionary algorithms' start from a population of possible solutions to a given problem and, by applying evolutionary principles, evolve successive generations with improved characteristics until an optimal, or near-optimal, solution is obtained. This book highlights the versatility of evolutionary algorithms in areas of relevance to molecular design with a particular focus on drug design. The authors, all of whom are experts in their field, discuss the application of these computational methods to a wide range of research problems including conformational analysis, chemometrics and quantitative structure-activity relationships, de novo molecular design, chemical structure handling, combinatorial library design, and the study of protein folding. In addition, the use of evolutionary algorithms in the determination of structures by X-ray crystallography and NMR spectroscopy is also covered. These state-of-the-art reviews, together with a discussion of new techniques and future developments in the field, make this book a truly valuable and highly up-to-date resource for anyone engaged in the application or development of computer-assisted methods in scientific research.
Book Synopsis Protein Structure Prediction by : Anna Tramontano
Download or read book Protein Structure Prediction written by Anna Tramontano and published by John Wiley & Sons. This book was released on 2006-02-20 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: While most textbooks on bioinformatics focus on genetic algorithms and treat protein structure prediction only superficially, this course book assumes a novel and unique focus. Adopting a didactic approach, the author explains all the current methods in terms of their reliability, limitations and user-friendliness. She provides practical examples to help first-time users become familiar with the possibilities and pitfalls of computer-based structure prediction, making this a must-have for students and researchers.
Book Synopsis The Protein Folding Problem and Tertiary Structure Prediction by : Kenneth M.Jr. Merz
Download or read book The Protein Folding Problem and Tertiary Structure Prediction written by Kenneth M.Jr. Merz and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: A solution to the protein folding problem has eluded researchers for more than 30 years. The stakes are high. Such a solution will make 40,000 more tertiary structures available for immediate study by translating the DNA sequence information in the sequence databases into three-dimensional protein structures. This translation will be indispensable for the analy sis of results from the Human Genome Project, de novo protein design, and many other areas of biotechnological research. Finally, an in-depth study of the rules of protein folding should provide vital clues to the protein fold ing process. The search for these rules is therefore an important objective for theoretical molecular biology. Both experimental and theoretical ap proaches have been used in the search for a solution, with many promising results but no general solution. In recent years, there has been an exponen tial increase in the power of computers. This has triggered an incredible outburst of theoretical approaches to solving the protein folding problem ranging from molecular dynamics-based studies of proteins in solution to the actual prediction of protein structures from first principles. This volume attempts to present a concise overview of these advances. Adrian Roitberg and Ron Elber describe the locally enhanced sam pling/simulated annealing conformational search algorithm (Chapter 1), which is potentially useful for the rapid conformational search of larger molecular systems.
Book Synopsis Computational Methods in Genome Research by : Sándor Suhai
Download or read book Computational Methods in Genome Research written by Sándor Suhai and published by Springer Science & Business Media. This book was released on 1994 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapters originating as plenary lectures at the July 1992 symposium provide a bridge between experimental databases (information) on the one hand and theoretical concepts (biological and genetic knowledge) on the other. Among the topics: informatics and experiments for the Human Genome Project; the
Book Synopsis Implementation of Genetic Algorithms for Protein Structure Prediction Based on Lattice Models by : 李俍叡
Download or read book Implementation of Genetic Algorithms for Protein Structure Prediction Based on Lattice Models written by 李俍叡 and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis 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). by :
Download or read book 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). written by and published by . This book was released on 2001 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ability to accurately predict a polypeptide's molecular structure given its amino acid sequence is important to numerous scientific, medical, and engineering applications. Studies have been conducted in the application of Genetic Algorithms (GAs) to this problem with promising initial results. In this thesis report, we use the fast messy Genetic Algorithm (fmGA) to attempt to find the minimization of an empirical CHARMM energy model and generation of the associated conformation. Previous work has shown that the fmGA provided favorable results, at least when applied to the pentapeptide Met-Enkephalin. We extend these results to a larger Polyalinine peptide by utilizing secondary structure information as both searching constraints and seeding the initial population. Additional efforts where conducted to improve the performance of the algorithm with respect to solving the Protein Structure Prediction (PSP) problem through a short-circuiting operator--where complete evaluation of the fitness function is halted if initial results are not promising, and by conducting additional searches on faster machines in a heterogeneous environment. Results indicate that, on average, this localized search tends to produce better final solutions. Finally, the fmGA as applied to the PSP problem is analyzed and shown to have improved performance and effectiveness.
Book Synopsis Search Algorithms and Applications by : Nashat Mansour
Download or read book Search Algorithms and Applications written by Nashat Mansour and published by IntechOpen. This book was released on 2011-04-26 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: Search algorithms aim to find solutions or objects with specified properties and constraints in a large solution search space or among a collection of objects. A solution can be a set of value assignments to variables that will satisfy the constraints or a sub-structure of a given discrete structure. In addition, there are search algorithms, mostly probabilistic, that are designed for the prospective quantum computer. This book demonstrates the wide applicability of search algorithms for the purpose of developing useful and practical solutions to problems that arise in a variety of problem domains. Although it is targeted to a wide group of readers: researchers, graduate students, and practitioners, it does not offer an exhaustive coverage of search algorithms and applications. The chapters are organized into three parts: Population-based and quantum search algorithms, Search algorithms for image and video processing, and Search algorithms for engineering applications.
Book Synopsis Bioinformatics and Computational Biology by : Tiratha Raj Singh
Download or read book Bioinformatics and Computational Biology written by Tiratha Raj Singh and published by CRC Press. This book was released on 2023-12-13 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bioinformatics and Computational Biology: Technological Advancements, Applications and Opportunities is an invaluable resource for general and applied researchers who analyze biological data that is generated, at an unprecedented rate, at the global level. After careful evaluation of the requirements for current trends in bioinformatics and computational biology, it is anticipated that the book will provide an insightful resource to the academic and scientific community. Through a myriad of computational resources, algorithms, and methods, it equips readers with the confidence to both analyze biological data and estimate predictions. The book offers comprehensive coverage of the most essential and emerging topics: Cloud-based monitoring of bioinformatics multivariate data with cloud platforms Machine learning and deep learning in bioinformatics Quantum machine learning for biological applications Integrating machine learning strategies with multiomics to augment prognosis in chronic diseases Biomedical engineering Next generation sequencing techniques and applications Computational systems biology and molecular evolution While other books may touch on some of the same issues and nuances of biological data analysis, they neglect to feature bioinformatics and computational biology exclusively, and as exhaustively. This book's abundance of several subtopics related to almost all of the regulatory activities of biomolecules from where real data is being generated brings an added dimension.
Book Synopsis Pattern Recognition in Bioinformatics by : Madhu Chetty
Download or read book Pattern Recognition in Bioinformatics written by Madhu Chetty and published by Springer Science & Business Media. This book was released on 2008-09-29 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the post-genomic era, a holistic understanding of biological systems and p- cesses,inalltheircomplexity,is criticalincomprehendingnature’schoreography of life. As a result, bioinformatics involving its two main disciplines, namely, the life sciences and the computational sciences, is fast becoming a very promising multidisciplinary research ?eld. With the ever-increasing application of lar- scalehigh-throughputtechnologies,suchasgeneorproteinmicroarraysandmass spectrometry methods, the enormous body of information is growing rapidly. Bioinformaticians are posed with a large number of di?cult problems to solve, arising not only due to the complexities in acquiring the molecular infor- tion but also due to the size and nature of the generated data sets and/or the limitations of the algorithms required for analyzing these data. Although the ?eld of bioinformatics is still in its embryonic stage, the recent advancements in computational and information-theoretic techniques are enabling us to c- ductvariousinsilicotestingandscreeningofmanylab-basedexperimentsbefore these are actually performed in vitro or in vivo. These in silico investigations are providing new insights for interpretation and establishing a new direction for a deeper understanding. Among the various advanced computational methods currently being applied to such studies, the pattern recognition techniques are mostly found to be at the core of the whole discovery process for apprehending the underlying biological knowledge. Thus, we can safely surmise that the - going bioinformatics revolution may, in future, inevitably play a major role in many aspects of medical practice and/or the discipline of life sciences.
Book Synopsis Parallel Genetic Algorithms by : Joachim Stender
Download or read book Parallel Genetic Algorithms written by Joachim Stender and published by IOS Press. This book was released on 1993 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Finding a Fitness Function to be Used with Genetic Algorithms to Solve a Protein Folding Problem by : Noni McCullough Bohonak
Download or read book Finding a Fitness Function to be Used with Genetic Algorithms to Solve a Protein Folding Problem written by Noni McCullough Bohonak and published by . This book was released on 2000 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt:
