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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
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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 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 Introduction to Genetic Algorithms by : S.N. Sivanandam
Download or read book Introduction to Genetic Algorithms written by S.N. Sivanandam and published by Springer Science & Business Media. This book was released on 2007-10-24 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a basic introduction to genetic algorithms. It provides a detailed explanation of genetic algorithm concepts and examines numerous genetic algorithm optimization problems. In addition, the book presents implementation of optimization problems using C and C++ as well as simulated solutions for genetic algorithm problems using MATLAB 7.0. It also includes application case studies on genetic algorithms in emerging fields.
Book Synopsis Parallel Computing for Bioinformatics and Computational Biology by : Albert Y. Zomaya
Download or read book Parallel Computing for Bioinformatics and Computational Biology written by Albert Y. Zomaya and published by John Wiley & Sons. This book was released on 2006-04-21 with total page 817 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover how to streamline complex bioinformatics applications with parallel computing This publication enables readers to handle more complex bioinformatics applications and larger and richer data sets. As the editor clearly shows, using powerful parallel computing tools can lead to significant breakthroughs in deciphering genomes, understanding genetic disease, designing customized drug therapies, and understanding evolution. A broad range of bioinformatics applications is covered with demonstrations on how each one can be parallelized to improve performance and gain faster rates of computation. Current parallel computing techniques and technologies are examined, including distributed computing and grid computing. Readers are provided with a mixture of algorithms, experiments, and simulations that provide not only qualitative but also quantitative insights into the dynamic field of bioinformatics. Parallel Computing for Bioinformatics and Computational Biology is a contributed work that serves as a repository of case studies, collectively demonstrating how parallel computing streamlines difficult problems in bioinformatics and produces better results. Each of the chapters is authored by an established expert in the field and carefully edited to ensure a consistent approach and high standard throughout the publication. The work is organized into five parts: * Algorithms and models * Sequence analysis and microarrays * Phylogenetics * Protein folding * Platforms and enabling technologies Researchers, educators, and students in the field of bioinformatics will discover how high-performance computing can enable them to handle more complex data sets, gain deeper insights, and make new discoveries.
Book Synopsis 2002 International Conference on Computational Nanoscience and Nanotechnology by : Matthew Laudon
Download or read book 2002 International Conference on Computational Nanoscience and Nanotechnology written by Matthew Laudon and published by . This book was released on 2002 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: The worlds most comprehensive and up-to-date collection of Nanotechnology and Nanoscience technical papers. Technical Proceedings of the Nanotech 2002 and the International Conference on Computational Nanoscience and Nanotechnology. Nanotech Vol. 1: Sequence and Biological Structure, Computer Aided Drug Design, Biological Conduction Processes, Biotechnology, Micro and Nano Fluidic Systems, Soft Condensed Matter, Extedned-Scale Atomistics, Quantum Effects, Quantum Devices, Spintronics, Mechanical Properties at the Nanoscale, Molecular and Nano Electronics, Condensed Matter Phenomena, Process Modeling, Nanotechnology, Materials and Nanostructures Studies, Nano Particles and Molecules. Papers taken from the 2002 Nanotechnology Conference and Trade Show, San Juan, Puerto Rico, April. 2002.
Book Synopsis Introduction to Protein Structure Prediction by : Huzefa Rangwala
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.
Book Synopsis A Multiobjective Approach Applied to the Protein Structure Prediction Problem by : Richard O. Day
Download or read book A Multiobjective Approach Applied to the Protein Structure Prediction Problem written by Richard O. Day and published by . This book was released on 2002-03-01 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in discovering a methodology for solving the Protein Structure Prediction problem extends into many fields of study including biochemistry, medicine, biology, and numerous engineering and science disciplines. Experimental approaches, such as, x-ray crystallographic studies or solution Nuclear Magnetic Resonance Spectroscopy, to mathematical modeling, such as minimum energy models are used to solve this problem. Recently, Evolutionary Algorithm studies at the Air Force Institute of Technology include the following: Simple Genetic Algorithm (GA), messy GA , fast messy GA, and Linkage Learning GA, as approaches for potential protein energy minimization. Prepackaged software like GENOCOP, GENESIS, and mGA are in use to facilitate experimentation of these techniques. In addition to this software, a parallelized version of the fmGA, the so-called parallel fast messy GA, is found to be good at finding semi-optimal answers in reasonable wall clock time. The aim of this work is to apply a Multiobjective approach to solving this problem using a modified fast messy GA. By dividing the CHARMm energy model into separate objectives, it should be possible to find structural configurations of a protein that yield lower energy values and ultimately more correct conformations.
Book Synopsis Protein Structure Prediction : A Practical Approach by : Michael J. E. Sternberg
Download or read book Protein Structure Prediction : A Practical Approach written by Michael J. E. Sternberg and published by Oxford University Press, USA. This book was released on 1996-11-28 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-dimensional structure of proteins is a key factor in their biological activity. There is an increasing need to be able to predict the structure of a protein once its amino-acid sequence is known; this book presents practical methods of achieving that ambitious aim, using the latest computer modelling algorithms. - ;The prediction of the three-dimensional structure of a protein from its sequence is a problem faced by an ever-increasing number of biological scientists as they strive to utilize genetic information. The increasing sizes of the sequence and structural databases, the improvements in computing power, and the deeper understanding of the principles of protein structure have led to major developments in the field in the last few years. This book presents practical computer-based methods using the latest computer modelling algorithms. -
Book Synopsis Computational Methods for Protein Structure Prediction and Modeling by : Ying Xu
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 2007-08-24 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume One of this two-volume sequence focuses on the basic characterization of known protein structures, and structure prediction from protein sequence information. Eleven chapters survey of the field, covering key topics in modeling, force fields, classification, computational methods, and structure prediction. Each chapter is a self contained review covering definition of the problem and historical perspective; mathematical formulation; computational methods and algorithms; performance results; existing software; strengths, pitfalls, challenges, and future research.
Book Synopsis Protein Structure Prediction by : Mohammed Zaki
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.
Book Synopsis Computational Methods for Protein Structure Prediction and Modeling by : Ying Xu
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.
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 Refined Genetic Algorithms for Polypeptide Structure Prediction by : Charles Edward Kaiser
Download or read book Refined Genetic Algorithms for Polypeptide Structure Prediction written by Charles Edward Kaiser and published by . This book was released on 1996-12-01 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate and reliable prediction of macromolecular structures has eluded researchers for nearly 40 years. Prediction via energy minimization assumes the native conformation has the globally minimal energy potential. An exhaustive search is impossible since for molecules of normal size, the size of the search space exceeds the size of the universe. Domain knowledge sources, such as the Brookhaven PDB can be mined for constraints to limit the search space. Genetic algorithms (GAs) are stochastic, population based, search algorithms of polynomial (P) time complexity that can produce semi-optimal solutions for problems of nondeterministic polynomial (NP) time complexity such as PSP. Three three refined GAs are presented: A farming model parallel hybrid GA (PHGA) preserves the effectiveness of the serial algorithm with substantial speed up. Portability across distributed and MPP platforms is accomplished with the Message Passing Interface (MPI) communications standard. A Real-valved GA system, real-valued Genetic Algorithm, Limited by constraints (REGAL), exploiting domain knowledge. Experiments with the pentapeptide Met-enkephalin have identified conformers with lower energies (CHARMM) than the accepted optimal conformer (Scheraga, et al), -31.98 vs -28.96 kcals/mol. Analysis of exogenous parameters yields additional insight into performance. A parallel version (Para-REGAL), an island model modified to allow different active constraints in the distributed subpopulations and novel concepts of Probability of Migration and Probability of Complete Migration.
Book Synopsis La Reqveste présentée av conseil privé par les bourgeois de la ville de Paris : avec levr lettre av cardinal Mazarin by :
Download or read book La Reqveste présentée av conseil privé par les bourgeois de la ville de Paris : avec levr lettre av cardinal Mazarin written by and published by . This book was released on 1649 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Protein Structure Prediction Using Parallel Linkage Investigating Genetic Algorithms by : Karl Deerman
Download or read book Protein Structure Prediction Using Parallel Linkage Investigating Genetic Algorithms written by Karl Deerman and published by . This book was released on 1999-03-01 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: AFIT has had a long-standing interest in solving the protein structure prediction (PSP) problem. The PSP problem is an intractable problem that if "solved" can lead to revolutionary new techniques for everything from the development of new medicines to optical computer switches. The challenge is to find a reliable and consistent method of predicting the 3-dimensional structure of a protein given its defining sequence of amino acids. PSP is primarily concerned with predicting the tertiary protein structure without regards to how the protein came to this folded state. The tertiary structure determines the protein's functionality.
Book Synopsis The Protein Folding Problem and Tertiary Structure Prediction by : Kenneth M. Merz
Download or read book The Protein Folding Problem and Tertiary Structure Prediction written by Kenneth M. Merz and published by . This book was released on 1994-01-01 with total page 581 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Protein Structure Prediction by : David Webster
Download or read book Protein Structure Prediction written by David Webster and published by Humana Press. This book was released on 2000-08-15 with total page 430 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.
