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A Metaheuristic Approach To Protein Structure Prediction
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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 A Meta-heuristic Optimization Tool for Simplified Protein Structure Prediction by : Gurpreet Singh Lakha
Download or read book A Meta-heuristic Optimization Tool for Simplified Protein Structure Prediction written by Gurpreet Singh Lakha and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Meta-heuristic algorithms give a satisfactory solution of complex optimization problems in a reasonable time. They are among the most promising and successful optimization techniques. However, some problems are highly complex and require improved techniques. A careful analysis of the existing meta-heuristic algorithms and hybridization among them may facilitate the research in this direction. To test this hypothesis, the author of the thesis developed a computational tool using a few meta-heuristic algorithms where these algorithms can be analyzed in detail and possible hybridization among them can be created. As a case study, the tool is developed for simplified protein structure prediction. The proper working of the software is demonstrated by optimizing the two sets of standard benchmark sequences. Along with testing and analyzing meta-heuristic algorithms, the tool can be used for simplified protein structure prediction.
Book Synopsis Machine-learning-based Meta Approaches to Protein Structure Prediction by : Hani Zakaria Girgis
Download or read book Machine-learning-based Meta Approaches to Protein Structure Prediction written by Hani Zakaria Girgis and published by . This book was released on 2008 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: The importance of knowing the three dimensional structure of proteins and the difficulty of determining it experimentally, have led scientists to develop several computational methods for protein structure prediction. Despite the abundance of protein structure prediction methods, these approaches have two major limitations in additions to others. First, the top ranked 3d-model reported by a prediction server is not necessarily the best predicted 3d-model. The correct predicted 3d-model may be ranked within the top 10 predictions after some false positives. Second, no single method can give correct predictions for all proteins. To attempt to remedy these limitations, protein structure prediction "meta" approaches have been developed. Some meta-servers apply a local model quality assessment program (MQAP) to select a set of candidate 3d-models by ranking 3d-models obtained from other servers. However, model quality assessment programs suffer from the same two limitations as the prediction servers. The data available for training machine-learning-based meta-approaches is constantly growing in size on a monthly or a weekly basis. Once new data become available which may contain new patterns, typically one will discard the models trained on the old training data and train new ones. Clearly such an approach is a waste of computation and needs manual human intervention to retrain the learning algorithm. My research has three goals, (i) to invent a novel machine-learning based meta-MQAP; (ii) to develop a new meta-selector based on the meta-MQAP; (iii) to devise new machine learning algorithms that can extend my meta-MQAP-meta-selector to make use of the newly available labeled data dynamically. To that end, (i) I have developed a new meta-MQAP-meta-selector based a on a three-levels-hierarchy of general linear models; (ii) I have proposed two algorithms to handle the problem of the constantly growing training date. The first algorithm trains a model dynamically on the related data to the unlabeled query (testing) data, in another words, it trains dynamically a custom-made expert. The second algorithm dynamically mixes local experts which are already trained and cached. My experimental results show that my meta-MQAP outperforms the best of the tested model quality assessment program by 7%-8% in the overall score. When selecting from the predictions made by humans in a standard benchmark CASP7, my meta-selectors achieve about 3% improvement above the best human predictor. I have participated in the world wide CASP8 competition with three meta-MQAP-meta-selectors. Based on the evaluation of 46 target proteins used in the recently completed, truly blind and independent CASP8 experiment, my meta-MQAP outperforms the best tested MQAP by 6%, 5%, 29%, and 10% in the easy, medium, hard categories and in the overall score respectively. These results show that my meta-MQAP outperforms any of its components proving that a hierarchy of weighted sums of the MQAP's scores has more information than a single MQAP. The three meta-selectors performances are very similar to the performance of the best performing CASP8 server, demonstrating that the "meta" approach used here, namely, meta-MQAPmeta-selection, is promising and further improvements are likely to result in a significant improvement in the performance over the best of the servers.
Book Synopsis Protein Structure Prediction by : Igor F. Tsigelny
Download or read book Protein Structure Prediction written by Igor F. Tsigelny and published by Internat'l University Line. This book was released on 2002 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Protein Structure Prediction Using Bee Colony Optimization Metaheuristic by : R. Fonseca
Download or read book Protein Structure Prediction Using Bee Colony Optimization Metaheuristic written by R. Fonseca and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis International Conference on Innovative Computing and Communications by : Ashish Khanna
Download or read book International Conference on Innovative Computing and Communications written by Ashish Khanna and published by Springer Nature. This book was released on 2021-08-31 with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes high-quality research papers presented at the Fourth International Conference on Innovative Computing and Communication (ICICC 2021), which is held at the Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India, on February 20–21, 2021. Introducing the innovative works of scientists, professors, research scholars, students and industrial experts in the field of computing and communication, the book promotes the transformation of fundamental research into institutional and industrialized research and the conversion of applied exploration into real-time applications.
Book Synopsis Applications of Artificial Intelligence in Engineering by : Xiao-Zhi Gao
Download or read book Applications of Artificial Intelligence in Engineering written by Xiao-Zhi Gao and published by Springer Nature. This book was released on 2021-05-10 with total page 922 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents best selected papers presented at the First Global Conference on Artificial Intelligence and Applications (GCAIA 2020), organized by the University of Engineering & Management, Jaipur, India, during 8–10 September 2020. The proceeding will be targeting the current research works in the domain of intelligent systems and artificial intelligence.
Book Synopsis High Performance Computing for Computational Science – VECPAR 2018 by : Hermes Senger
Download or read book High Performance Computing for Computational Science – VECPAR 2018 written by Hermes Senger and published by Springer. This book was released on 2019-03-25 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 13th International Conference on High Performance Computing in Computational Science, VECPAR 2018, held in São Pedro, Brazil, in September 2018. The 17 full papers and one short paper included in this book were carefully reviewed and selected from 32 submissions presented at the conference. The papers cover the following topics: heterogeneous systems, shared memory systems and GPUs, and techniques including domain decomposition, scheduling and load balancing, with a strong focus on computational science applications.
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 Applied Nature-Inspired Computing: Algorithms and Case Studies by : Nilanjan Dey
Download or read book Applied Nature-Inspired Computing: Algorithms and Case Studies written by Nilanjan Dey and published by Springer. This book was released on 2019-08-10 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications. It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems. In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each. Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management.
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 Controller Tuning Optimization Methods for Multi-Constraints and Nonlinear Systems by : Maude Josée Blondin
Download or read book Controller Tuning Optimization Methods for Multi-Constraints and Nonlinear Systems written by Maude Josée Blondin and published by Springer Nature. This book was released on 2021-01-06 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers controller tuning techniques from conventional to new optimization methods for diverse control engineering applications. Classical controller tuning approaches are presented with real-world challenges faced in control engineering. Current developments in applying optimization techniques to controller tuning are explained. Case studies of optimization algorithms applied to controller tuning dealing with nonlinearities and limitations like the inverted pendulum and the automatic voltage regulator are presented with performance comparisons. Students and researchers in engineering and optimization interested in optimization methods for controller tuning will utilize this book to apply optimization algorithms to controller tuning, to choose the most suitable optimization algorithm for a specific application, and to develop new optimization techniques for controller tuning.
Book Synopsis Mathematical Methods for Protein Structure Analysis and Design by : Concettina Guerra
Download or read book Mathematical Methods for Protein Structure Analysis and Design written by Concettina Guerra and published by Springer Science & Business Media. This book was released on 2003-06-25 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: The papers collected in this volume reproduce contributions by leading sch- arstoaninternationalschoolandworkshopwhichwasorganizedandheldwith thegoaloftakinga snapshotofadiscipline undertumultuous growth. Indeed, the area of protein folding, docking and alignment is developing in response to needs for a mix of heterogeneous expertise spanning biology, chemistry, mathematics, computer science, and statistics, among others. Some of the problems encountered in this area are not only important for the scienti?c challenges they pose, but also for the opportunities they disclose intermsofmedicalandindustrialexploitation. Atypicalexampleiso?eredby protein-drug interaction (docking), a problem posing daunting computational problems at the crossroads of geometry, physics and chemistry, and, at the same time, a problem with unimaginable implications for the pharmacopoeia of the future. The schoolfocused on problems posed by the study of the mechanisms - hind protein folding, and explored di?erent ways of attacking these problems under objective evaluations of the methods. Together with a relatively small core of consolidated knowledge and tools, important re?ections were brought to this e?ort by studies in a multitude of directions and approaches. It is obviously impossible to predict which, if any, among these techniques will prove completely successful, but it is precisely the implicit dialectic among them that best conveys the current ?avor of the ?eld. Such unique diversity and richness inspired the format of the meeting, and also explains the slight departure of the present volume from the typical format in this series: the exposition of the current sediment is complemented here by a selection of quali?ed specialized contributions.
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 Protein Structure by Distance Analysis by : Henrik Bohr
Download or read book Protein Structure by Distance Analysis written by Henrik Bohr and published by IOS Press. This book was released on 1994 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimizing Potentials for Protein Structure Prediction, Inverse Protein Folding and Protein Folding by : Ting-Lan Chiu
Download or read book Optimizing Potentials for Protein Structure Prediction, Inverse Protein Folding and Protein Folding written by Ting-Lan Chiu and published by . This book was released on 1999 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Parallel Combinatorial Optimization by : El-Ghazali Talbi
Download or read book Parallel Combinatorial Optimization written by El-Ghazali Talbi and published by John Wiley & Sons. This book was released on 2006-10-27 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text provides an excellent balance of theory and application that enables you to deploy powerful algorithms, frameworks, and methodologies to solve complex optimization problems in a diverse range of industries. Each chapter is written by leading experts in the fields of parallel and distributed optimization. Collectively, the contributions serve as a complete reference to the field of combinatorial optimization, including details and findings of recent and ongoing investigations.
