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| computational molecular biology an algorithmic approach: Computational Molecular Biology Pavel Pevzner, 2014-05-14 In one of the first major texts in the emerging field of computational molecular biology, Pavel Pevzner covers a broad range of algorithmic and combinatorial topics and shows how they are connected to molecular biology and to biotechnology. The book has a substantial computational biology without formulas component that presents the biological and computational ideas in a relatively simple manner. This makes the material accessible to computer scientists without biological training, as well as to biologists with limited background in computer science. Computational Molecular Biology series Computer science and mathematics are transforming molecular biology from an informational to a computational science. Drawing on computational, statistical, experimental, and technological methods, the new discipline of computational molecular biology is dramatically increasing the discovery of new technologies and tools for molecular biology. The new MIT Press Computational Molecular Biology series provides a unique venue for the rapid publication of monographs, textbooks, edited collections, reference works, and lecture notes of the highest quality. |
| computational molecular biology an algorithmic approach: Computational Molecular Biology S. Istrail, P. Pevzner, R. Shamir, 2003-04-02 This volume contains papers demonstrating the variety and richness of computational problems motivated by molecular biology. The application areas within biology that give rise to the problems studied in these papers include solid molecular modeling, sequence comparison, phylogeny, evolution, mapping, DNA chips, protein folding and 2D gel technology. The mathematical techniques used are algorithmics, combinatorics, optimization, probability, graph theory, complexity and applied mathematics. This is the fourth volume in the Discrete Applied Mathematics series on computational molecular biology, which is devoted to combinatorial and algorithmic techniques in computational molecular biology. This series publishes novel research results on the mathematical and algorithmic foundations of the inherently discrete aspects of computational biology. Key features: . protein folding . phylogenetic inference . 2-dimensional gel analysis . graphical models for sequencing by hybridisation . dynamic visualization of molecular surfaces . problems and algorithms in sequence alignment This book is a reprint of Discrete Applied Mathematics Volume 127, Number 1. |
| computational molecular biology an algorithmic approach: Computational Molecular Biology Pavel A. Pevzner, 2000-08-17 In one of the first major texts in the emerging field of computational molecular biology, Pavel Pevzner covers a broad range of algorithmic and combinatorial topics and shows how they are connected to molecular biology and to biotechnology. The book has a substantial computational biology without formulas component that presents the biological and computational ideas in a relatively simple manner. This makes the material accessible to computer scientists without biological training, as well as to biologists with limited background in computer science. Computational Molecular Biology seriesComputer science and mathematics are transforming molecular biology from an informational to a computational science. Drawing on computational, statistical, experimental, and technological methods, the new discipline of computational molecular biology is dramatically increasing the discovery of new technologies and tools for molecular biology. The new MIT Press Computational Molecular Biology series provides a unique venue for the rapid publication of monographs, textbooks, edited collections, reference works, and lecture notes of the highest quality. |
| computational molecular biology an algorithmic approach: Algorithms in Structural Molecular Biology Bruce R. Donald, 2023-08-15 An overview of algorithms important to computational structural biology that addresses such topics as NMR and design and analysis of proteins.Using the tools of information technology to understand the molecular machinery of the cell offers both challenges and opportunities to computational scientists. Over the past decade, novel algorithms have been developed both for analyzing biological data and for synthetic biology problems such as protein engineering. This book explains the algorithmic foundations and computational approaches underlying areas of structural biology including NMR (nuclear magnetic resonance); X-ray crystallography; and the design and analysis of proteins, peptides, and small molecules. Each chapter offers a concise overview of important concepts, focusing on a key topic in the field. Four chapters offer a short course in algorithmic and computational issues related to NMR structural biology, giving the reader a useful toolkit with which to approach the fascinating yet thorny computational problems in this area. A recurrent theme is understanding the interplay between biophysical experiments and computational algorithms. The text emphasizes the mathematical foundations of structural biology while maintaining a balance between algorithms and a nuanced understanding of experimental data. Three emerging areas, particularly fertile ground for research students, are highlighted: NMR methodology, design of proteins and other molecules, and the modeling of protein flexibility. The next generation of computational structural biologists will need training in geometric algorithms, provably good approximation algorithms, scientific computation, and an array of techniques for handling noise and uncertainty in combinatorial geometry and computational biophysics. This book is an essential guide for young scientists on their way to research success in this exciting field. |
| computational molecular biology an algorithmic approach: An Introduction to Bioinformatics Algorithms Neil C. Jones, Pavel A. Pevzner, 2004-08-06 An introductory text that emphasizes the underlying algorithmic ideas that are driving advances in bioinformatics. This introductory text offers a clear exposition of the algorithmic principles driving advances in bioinformatics. Accessible to students in both biology and computer science, it strikes a unique balance between rigorous mathematics and practical techniques, emphasizing the ideas underlying algorithms rather than offering a collection of apparently unrelated problems. The book introduces biological and algorithmic ideas together, linking issues in computer science to biology and thus capturing the interest of students in both subjects. It demonstrates that relatively few design techniques can be used to solve a large number of practical problems in biology, and presents this material intuitively. An Introduction to Bioinformatics Algorithms is one of the first books on bioinformatics that can be used by students at an undergraduate level. It includes a dual table of contents, organized by algorithmic idea and biological idea; discussions of biologically relevant problems, including a detailed problem formulation and one or more solutions for each; and brief biographical sketches of leading figures in the field. These interesting vignettes offer students a glimpse of the inspirations and motivations for real work in bioinformatics, making the concepts presented in the text more concrete and the techniques more approachable.PowerPoint presentations, practical bioinformatics problems, sample code, diagrams, demonstrations, and other materials can be found at the Author's website. |
| computational molecular biology an algorithmic approach: Introduction to Bioinformatics Stephen A. Krawetz, David D. Womble, 2003-01-31 CD-ROM contains: chapter illustrations -- full and trial versions of programs. |
| computational molecular biology an algorithmic approach: Algorithms in Computational Molecular Biology Mourad Elloumi, Albert Y. Zomaya, 2011-04-04 This book represents the most comprehensive and up-to-date collection of information on the topic of computational molecular biology. Bringing the most recent research into the forefront of discussion, Algorithms in Computational Molecular Biology studies the most important and useful algorithms currently being used in the field, and provides related problems. It also succeeds where other titles have failed, in offering a wide range of information from the introductory fundamentals right up to the latest, most advanced levels of study. |
| computational molecular biology an algorithmic approach: Bioinformatics Algorithms Phillip Compeau, Pavel Pevzner, 1986-06 Bioinformatics Algorithms: an Active Learning Approach is one of the first textbooks to emerge from the recent Massive Online Open Course (MOOC) revolution. A light-hearted and analogy-filled companion to the authors' acclaimed online course (http://coursera.org/course/bioinformatics), this book presents students with a dynamic approach to learning bioinformatics. It strikes a unique balance between practical challenges in modern biology and fundamental algorithmic ideas, thus capturing the interest of students of biology and computer science students alike.Each chapter begins with a central biological question, such as Are There Fragile Regions in the Human Genome? or Which DNA Patterns Play the Role of Molecular Clocks? and then steadily develops the algorithmic sophistication required to answer this question. Hundreds of exercises are incorporated directly into the text as soon as they are needed; readers can test their knowledge through automated coding challenges on Rosalind (http://rosalind.info), an online platform for learning bioinformatics.The textbook website (http://bioinformaticsalgorithms.org) directs readers toward additional educational materials, including video lectures and PowerPoint slides. |
| computational molecular biology an algorithmic approach: Introduction to Computational Molecular Biology João Carlos Setubal, João Meidanis, 1997 Basic concepts of molecular biology. Strings, graphs, and algorithms. Sequence comparasion and database search. Fragment assembly of DNA. Physical mapping of DNA. Phylogenetic trees. Genome rearrangements. Molecular structure prediction. epilogue: computing with DNA. Answers to selected exercises. References. index. |
| computational molecular biology an algorithmic approach: Statistical Modeling and Machine Learning for Molecular Biology Alan Moses, 2017-01-06 • Assumes no background in statistics or computers • Covers most major types of molecular biological data • Covers the statistical and machine learning concepts of most practical utility (P-values, clustering, regression, regularization and classification) • Intended for graduate students beginning careers in molecular biology, systems biology, bioengineering and genetics |
| computational molecular biology an algorithmic approach: Algorithms on Strings, Trees, and Sequences Dan Gusfield, 1997-05-28 String algorithms are a traditional area of study in computer science. In recent years their importance has grown dramatically with the huge increase of electronically stored text and of molecular sequence data (DNA or protein sequences) produced by various genome projects. This book is a general text on computer algorithms for string processing. In addition to pure computer science, the book contains extensive discussions on biological problems that are cast as string problems, and on methods developed to solve them. It emphasises the fundamental ideas and techniques central to today's applications. New approaches to this complex material simplify methods that up to now have been for the specialist alone. With over 400 exercises to reinforce the material and develop additional topics, the book is suitable as a text for graduate or advanced undergraduate students in computer science, computational biology, or bio-informatics. Its discussion of current algorithms and techniques also makes it a reference for professionals. |
| computational molecular biology an algorithmic approach: Bioinformatics Algorithms Phillip Compeau, Pavel Pevzner, 2015-08-01 Bioinformatics Algorithms: An Active Learning Approach is one of the first textbooks to emerge from the recent Massive Open Online Course (MOOC) revolution. A light-hearted and analogy-filled companion to the authors' series of courses on Coursera, this book presents students with a dynamic approach to learning bioinformatics. It strikes a unique balance between practical challenges in modern biology and fundamental algorithmic ideas, thus capturing the interest of biology and computer science students alike. Each chapter begins with a central biological question, such as Are There Fragile Regions in the Human Genome? or Which DNA Patterns Play the Role of Molecular Clocks? and then steadily develops the algorithmic sophistication required to answer this question. Hundreds of exercises are incorporated directly into the text as soon as they are needed; readers can test their knowledge through automated coding challenges on Rosalind (http://rosalind.info), an online platform for learning bioinformatics. The textbook website (http://bioinformaticsalgorithms.com) directs readers toward additional educational materials, including video lectures and PowerPoint slides. |
| computational molecular biology an algorithmic approach: Computational Biology And Genome Informatics Paul P Wang, Jason T L Wang, Cathy H Wu, 2003-02-19 This book contains articles written by experts on a wide range of topics that are associated with the analysis and management of biological information at the molecular level. It contains chapters on RNA and protein structure analysis, DNA computing, sequence mapping, genome comparison, gene expression data mining, metabolic network modeling, and phyloinformatics.The important work of some representative researchers in bioinformatics is brought together for the first time in one volume. The topic is treated in depth and is related to, where applicable, other emerging technologies such as data mining and visualization. The goal of the book is to introduce readers to the principle techniques of bioinformatics in the hope that they will build on them to make new discoveries of their own. |
| computational molecular biology an algorithmic approach: An Introduction to Computational Systems Biology Karthik Raman, 2023-05-29 Emphasises a hands-on approach to modelling Strong emphasis on coding and software tools for systems biology Covers the entire spectrum of modelling, from static networks, to dynamic models Thoughtful exercises to test and enable student understanding of concepts Current chapters on exciting new developments like whole-cell modelling and community modelling |
| computational molecular biology an algorithmic approach: Using The Biological Literature Diane Schmidt, Elisabeth B. Davis, 2001-12-06 Provides an in-depth review of current print and electronic tools for research in numerous disciplines of biology, including dictionaries and encyclopedias, method guides, handbooks, on-line directories, and periodicals. Directs readers to an associated Web page that maintains the URLs and annotations of all major Inernet resources discussed in th |
| computational molecular biology an algorithmic approach: Algorithms for Computational Biology Adrian-Horia Dediu, Carlos Martín-Vide, Bianca Truthe, 2014-06-07 This book constitutes the refereed proceedings of the First International Conference, AlCoB 2014, held in July 2014 in Tarragona, Spain. The 20 revised full papers were carefully reviewed and selected from 39 submissions. The scope of AlCoB includes topics of either theoretical or applied interest, namely: exact sequence analysis, approximate sequence analysis, pairwise sequence alignment, multiple sequence alignment, sequence assembly, genome rearrangement, regulatory motif finding, phylogeny reconstruction, phylogeny comparison, structure prediction, proteomics: molecular pathways, interaction networks, transcriptomics: splicing variants, isoform inference and quantification, differential analysis, next-generation sequencing: population genomics, metagenomics, metatranscriptomics, microbiome analysis, systems biology. |
| computational molecular biology an algorithmic approach: Algorithms and Computation Toshihide Ibaraki, Naoki Katoh, Hirotaka Ono, 2003-11-24 This volume contains the proceedings of the 14th Annual International S- posium on Algorithms and Computation (ISAAC 2003), held in Kyoto, Japan, 15–17 December 2003. In the past, it was held in Tokyo (1990), Taipei (1991), Nagoya (1992), Hong Kong (1993), Beijing (1994), Cairns (1995), Osaka (1996), Singapore (1997), Taejon (1998), Chennai (1999), Taipei (2000), Christchurch (2001), and Vancouver (2002). ISAACisanannualinternationalsymposiumthatcoverstheverywiderange of topics in algorithms and computation. The main purpose of the symposium is to provide a forum for researchers working in algorithms and the theory of computation where they can exchange ideas in this active research community. In response to our call for papers, we received unexpectedly many subm- sions, 207 papers. The task of selecting the papers in this volume was done by our program committee and referees. After a thorough review process, the committee selected 73 papers. The selection was done on the basis of originality and relevance to the ?eld of algorithms and computation. We hope all accepted papers will eventally appear in scienti?c journals in more polished forms. The best paper award was given for “On the Geometric Dilation of Finite Point Sets” to Annette Ebbers-Baumann, Ansgar Grune ̈ and Rolf Klein. Two eminent invited speakers, Prof. Andrew Chi-Chih Yao of Princeton University and Prof. Takao Nishizeki of Tohoku University, contributed to this proceedings. |
| computational molecular biology an algorithmic approach: Algorithms in Bioinformatics Olivier Gascuel, 2001-08-15 This book constitutes the refereed proceedings of the First International Workshop on Algorithms in Bioinformatics, WABI 2001, held in Aarhus, Denmark, in August 2001. The 23 revised full papers presented were carefully reviewed and selected from more than 50 submissions. Among the issues addressed are exact and approximate algorithms for genomics, sequence analysis, gene and signal recognition, alignment, molecular evolution, structure determination or prediction, gene expression and gene networks, proteomics, functional genomics, and drug design; methodological topics from algorithmics; high-performance approaches to hard computational problems in bioinformatics. |
| computational molecular biology an algorithmic approach: Health & Drugs Nicolae Sfetcu, 2014-05-02 Information about drugs, side effects and abuse. Drug prescription, medication and therapy. online stores to buy drugs. Testing, interaction, administration and treatments for the health care. Medicine is the branch of health science and the sector of public life concerned with maintaining or restoring human health through the study, diagnosis, treatment and possible prevention of disease and injury. It is both an area of knowledge – a science of body systems, their diseases and treatment – and the applied practice of that knowledge. A drug is any biological substance, synthetic or non-synthetic, that is taken for non-dietary needs. It is usually synthesized outside of an organism, but introduced into an organism to produce its action. That is, when taken into the organisms body, it will produce some effects or alter some bodily functions (such as relieving symptoms, curing diseases or used as preventive medicine or any other purposes). |
| computational molecular biology an algorithmic approach: Encyclopedia of Data Warehousing and Mining, Second Edition Wang, John, 2008-08-31 There are more than one billion documents on the Web, with the count continually rising at a pace of over one million new documents per day. As information increases, the motivation and interest in data warehousing and mining research and practice remains high in organizational interest. The Encyclopedia of Data Warehousing and Mining, Second Edition, offers thorough exposure to the issues of importance in the rapidly changing field of data warehousing and mining. This essential reference source informs decision makers, problem solvers, and data mining specialists in business, academia, government, and other settings with over 300 entries on theories, methodologies, functionalities, and applications. |
| computational molecular biology an algorithmic approach: Comprehensive Metaheuristics Ali Mirjalili, Amir Hossein Gandomi, 2023-01-31 Comprehensive Metaheuristics: Algorithms and Applications presents the foundational underpinnings of metaheuristics and a broad scope of algorithms and real-world applications across a variety of research fields. The book starts with fundamentals, mathematical prerequisites, and conceptual approaches to provide readers with a solid foundation. After presenting multi-objective optimization, constrained optimization, and problem formation for metaheuristics, world-renowned authors give readers in-depth understanding of the full spectrum of algorithms and techniques. Scientists, researchers, academicians, and practitioners who are interested in optimizing a process or procedure to achieve a goal will benefit from the case studies of real-world applications from different domains. The book takes a much-needed holistic approach, putting the most widely used metaheuristic algorithms together with an in-depth treatise on multi-disciplinary applications of metaheuristics. Each algorithm is thoroughly analyzed to observe its behavior, providing a detailed tutorial on how to solve problems using metaheuristics. New case studies and research problem statements are also discussed, which will help researchers in their application of the concepts. - Presented by world-renowned researchers and practitioners in metaheuristics - Includes techniques, algorithms, and applications based on real-world case studies - Presents the methodology for formulating optimization problems for metaheuristics - Provides readers with methods for analyzing and tuning the performance of a metaheuristic, as well as for integrating metaheuristics in other AI techniques - Features online complementary source code from the applications and algorithms |
| computational molecular biology an algorithmic approach: Evolutionary Machine Design Nadia Nedjah, Luiza de Macedo Mourelle, 2005 In recent years, genetic programming has attracted many researcher's attention and so became a consolidated methodology to automatically create new competitive computer programs. Concise and efficient synthesis of a variety of systems has been generated by evolutionary computations. Evolvable hardware is a growing discipline. It allows one to evolve creative and novel hardware architectures given the expected input/output behaviour. There are two kinds of evolvable hardware: extrinsic and intrinsic. The former relies on a simulated evolutionary process to evaluate the characteristics of the evolved designs while the latter uses hardware itself to do so. Usually, reconfigurable hardware such FPGA and FPAA are exploited. One of the main problems that still faces researchers in the field of evolutionary machine design is the scalability. This book is devoted to reporting innovative and significant progress in automatic machine design. Theoretical as well as practical chapters are contemplated. The scalability problem in evolutionary machine designs is addresses. The content of this book is divided into two main parts: evolvable hardware and genetic programming; and evolutionary designs. In the following, we give a brief description of the main contribution of each of the included chapters. |
| computational molecular biology an algorithmic approach: High Performance Computing for Computational Science - VECPAR 2006 Michel Daydé, 2007-04-02 This book constitutes the thoroughly refereed post-proceedings of the 7th International Conference on High Performance Computing for Computational Science, VECPAR 2006, held in Rio de Janeiro, Brazil, in June 2006. The 44 revised full papers presented together with one invited paper and 12 revised workshop papers cover Grid computing, cluster computing, numerical methods, large-scale simulations in Physics, and computing in Biosciences. |
| computational molecular biology an algorithmic approach: Developments in Language Theory Hsu-Chun Yen, Oscar H. Ibarra, 2012-07-16 This book constitutes the refereed proceedings of the 16th International Conference on Developments in Language Theory, DLT 2012, held in Taipei, Taiwan, in August 2012. The 34 regular papers presented were carefully reviewed and selected from numerous submissions. The volume also contains the papers or extended abstracts of 4 invited lectures, as well as a special memorial presentation in honor of Sheng Yu. The topics covered include grammars, acceptors and transducers for words, trees and graphs; algebraic theories of automata; algorithmic, combinatorial and algebraic properties of words and languages; variable length codes; symbolic dynamics; cellular automata; polyominoes and multidimensional patterns; decidability questions; image manipulation and compression; efficient text algorithms; relationships to cryptography, concurrency, complexity theory and logic; bio-inspired computing; quantum computing. |
| computational molecular biology an algorithmic approach: Introduction to Algorithms, third edition Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, 2009-07-31 The latest edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-based flow. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called “Divide-and-Conquer”), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many exercises and problems have been added for this edition. The international paperback edition is no longer available; the hardcover is available worldwide. |
| computational molecular biology an algorithmic approach: Combinatorial Pattern Matching Amihood Amir, Gad M. Landau, 2003-06-29 This book constitutes the refereed proceedings of the 12th Annual Symposium on Combinatorial Pattern Matching, CPM 2001, held in Jerusalem, Israel, in July 2001. The 21 revised papers presented together with one invited paper were carefully reviewed and selected from 35 submissions. The papers are devoted to current theoretical and algorithmic issues of searching and matching strings and more complicated patterns such as trees, regular expressions, graphs, point sets, and arrays as well as to advanced applications of CPM in areas such as the Internet, computational biology, multimedia systems, information retrieval, data compression, coding, computer vision, and pattern recognition. |
| computational molecular biology an algorithmic approach: Handbook of Graph Theory Jonathan L. Gross, Jay Yellen, Ping Zhang, 2013-12-17 In the ten years since the publication of the best-selling first edition, more than 1,000 graph theory papers have been published each year. Reflecting these advances, Handbook of Graph Theory, Second Edition provides comprehensive coverage of the main topics in pure and applied graph theory. This second edition-over 400 pages longer than its prede |
| computational molecular biology an algorithmic approach: Encyclopedia of Algorithms Ming-Yang Kao, 2008-08-06 One of Springer’s renowned Major Reference Works, this awesome achievement provides a comprehensive set of solutions to important algorithmic problems for students and researchers interested in quickly locating useful information. This first edition of the reference focuses on high-impact solutions from the most recent decade, while later editions will widen the scope of the work. All entries have been written by experts, while links to Internet sites that outline their research work are provided. The entries have all been peer-reviewed. This defining reference is published both in print and on line. |
| computational molecular biology an algorithmic approach: Genetic and Evolutionary Computation — GECCO 2004 Kalyanmoy Deb, Riccardo Poli, Wolfgang Banzhaf, Hans-Georg Beyer, Edmund Burke, Paul Darwen, Dipankar Dasgupta, Dario Floreano, James A. Foster, Mark Harman, Owen Holland, Pier Luca Lanzi, Lee Spector, Andrea Tettamanzi, Dirk Thierens, Andy Tyrrell, 2004-06-01 The two volume set LNCS 3102/3103 constitutes the refereed proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2004, held in Seattle, WA, USA, in June 2004. The 230 revised full papers and 104 poster papers presented were carefully reviewed and selected from 460 submissions. The papers are organized in topical sections on artificial life, adaptive behavior, agents, and ant colony optimization; artificial immune systems, biological applications; coevolution; evolutionary robotics; evolution strategies and evolutionary programming; evolvable hardware; genetic algorithms; genetic programming; learning classifier systems; real world applications; and search-based software engineering. |
| computational molecular biology an algorithmic approach: BioMath in the Schools Margaret B. Cozzens, Fred S. Roberts, 2011 Even though contemporary biology and mathematics are inextricably linked, high school biology and mathematics courses have traditionally been taught in isolation. But this is beginning to change. This volume presents papers related to the integration of biology and mathematics in high school classes. The first part of the book provides the rationale for integrating mathematics and biology in high school courses as well as opportunities for doing so. The second part explores the development and integration of curricular materials and includes responses from teachers. Papers in the third part of the book explore the interconnections between biology and mathematics in light of new technologies in biology. The last paper in the book discusses what works and what doesn't and presents positive responses from students to the integration of mathematics and biology in their classes. |
| computational molecular biology an algorithmic approach: Computer Science , |
| computational molecular biology an algorithmic approach: Metaheuristics for String Problems in Bio-informatics Christian Blum, Paola Festa, 2016-08-16 So-called string problems are abundant in bioinformatics and computational biology. New optimization problems dealing with DNA or protein sequences are constantly arising and researchers are highly in need of efficient optimization techniques for solving them. One obstacle for optimization practitioners is the atypical nature of these problems which require an interdisciplinary approach in order to solve them efficiently and accurately. |
| computational molecular biology an algorithmic approach: Applied Combinatorics on Words M. Lothaire, 2005-07-11 Publisher Description |
| computational molecular biology an algorithmic approach: Introduction To Algorithms Thomas H Cormen, Charles E Leiserson, Ronald L Rivest, Clifford Stein, 2001 An extensively revised edition of a mathematically rigorous yet accessible introduction to algorithms. |
| computational molecular biology an algorithmic approach: Limit Theorems in Probability, Statistics and Number Theory Peter Eichelsbacher, Guido Elsner, Holger Kösters, Matthias Löwe, Franz Merkl, Silke Rolles, 2013-04-23 Limit theorems and asymptotic results form a central topic in probability theory and mathematical statistics. New and non-classical limit theorems have been discovered for processes in random environments, especially in connection with random matrix theory and free probability. These questions and the techniques for answering them combine asymptotic enumerative combinatorics, particle systems and approximation theory, and are important for new approaches in geometric and metric number theory as well. Thus, the contributions in this book include a wide range of applications with surprising connections ranging from longest common subsequences for words, permutation groups, random matrices and free probability to entropy problems and metric number theory. The book is the product of a conference that took place in August 2011 in Bielefeld, Germany to celebrate the 60th birthday of Friedrich Götze, a noted expert in this field. |
| computational molecular biology an algorithmic approach: Developments in Language Theory Tero Harju, Juhani Karhumäki, Arto Lepistö, 2007-09-13 This book constitutes the refereed proceedings of the 11th International Conference on Developments in Language Theory, DLT 2007, held in Turku, Finland in July 2007. It addresses all important issues in language theory including grammars, acceptors and transducers for words, trees and graphs; algebraic theories of automata; relationships to cryptography, concurrency, complexity theory and logic; bioinspired computing, and quantum computing. |
| computational molecular biology an algorithmic approach: Active Mining Shusaku Tsumoto, Takahira Yamaguchi, Masayuki Numao, Hiroshi Motoda, 2005-06-03 This book constitutes the thoroughly refereed postproceedings of the Second International Workshop on Active Mining, AM 2003, held in Maebashi, Japan, in October 2003 as a satellite workshop of ISMIS 2003. The 16 revised full papers presented together with 2 tutorial papers and an overview of the Japanese Active Mining Project went through 2 rounds of reviewing and improvement and were selected from initialy 38 submissions. The papers are organized in topical sections on active information collection, active data mining, and active user reaction. Many current aspects of active mining are addressed, ranging from theoretical and methodological topics to algorithms and their applications in fields such as bioinformatics, medicine, and life science more generally. |
| computational molecular biology an algorithmic approach: Experimental and Efficient Algorithms Sotiris Nikoletseas, 2005-04-28 This book constitutes the refereed proceedings of the 4th International Workshop on Experimental and Efficient Algorithms, WEA 2005, held in Santorini Island, Greece in May 2005. The 47 revised full papers and 7 revised short papers presented together with extended abstracts of 3 invited talks were carefully reviewed and selected from 176 submissions. The book is devoted to the design, analysis, implementation, experimental evaluation, and engineering of efficient algorithms. Among the application areas addressed are most fields applying advanced algorithmic techniques, such as combinatorial optimization, approximation, graph theory, discrete mathematics, scheduling, searching, sorting, string matching, coding, networking, data mining, data analysis, etc. |
| computational molecular biology an algorithmic approach: Computational Neurogenetic Modeling Lubica Benuskova, Nikola K. Kasabov, 2010-05-05 Computational Neurogenetic Modeling is a student text, introducing the scope and problems of a new scientific discipline - Computational Neurogenetic Modeling (CNGM). CNGM is concerned with the study and development of dynamic neuronal models for modeling brain functions with respect to genes and dynamic interactions between genes. These include neural network models and their integration with gene network models. This new area brings together knowledge from various scientific disciplines, such as computer and information science, neuroscience and cognitive science, genetics and molecular biology, as well as engineering. |
| computational molecular biology an algorithmic approach: Comparative Genomics Glenn Tesler, Dannie Durand, 2007-08-31 This book constitutes the refereed proceedings of the 5th RECOMB Comparative Genomics Satellite Workshop, RECOMB-CG 2007, held in San Diego, CA, USA, in September 2007. The 14 revised full papers presented address a broad variety of aspects and components of the field of comparative genomics, ranging from quantitative discoveries about genome structure to algorithms for comparative inference to theorems on the complexity of computational problems required for genome comparison. |
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COMPUTATIONAL | English meaning - Cambridge Dictionary
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Computational science - Wikipedia
Computational science, also known as scientific computing, technical computing or scientific computation (SC), is a division of …
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The meaning of COMPUTATION is the act or action of computing : calculation. How to use computation in a sentence.
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Computational is an adjective referring to a system of calculating or "computing," or, more commonly today, work involving …
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