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Evolutionary Computation in Bioinformatics

Evolutionary Computation in Bioinformatics
Author: Gary Fogel
Publisher: Morgan Kaufmann
Total Pages: 432
Release: 2003
Genre: Computers
ISBN: 9781558607972

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This book offers a definitive resource that bridges biology and evolutionary computation. The authors have written an introduction to biology and bioinformatics for computer scientists, plus an introduction to evolutionary computation for biologists and for computer scientists unfamiliar with these techniques.


Evolutionary Computation for Modeling and Optimization

Evolutionary Computation for Modeling and Optimization
Author: Daniel Ashlock
Publisher: Springer Science & Business Media
Total Pages: 578
Release: 2006-04-04
Genre: Computers
ISBN: 0387319093

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Concentrates on developing intuition about evolutionary computation and problem solving skills and tool sets. Lots of applications and test problems, including a biotechnology chapter.


Evolutionary Computation in Gene Regulatory Network Research

Evolutionary Computation in Gene Regulatory Network Research
Author: Hitoshi Iba
Publisher: John Wiley & Sons
Total Pages: 464
Release: 2016-02-23
Genre: Computers
ISBN: 1118911512

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Introducing a handbook for gene regulatory network research using evolutionary computation, with applications for computer scientists, computational and system biologists This book is a step-by-step guideline for research in gene regulatory networks (GRN) using evolutionary computation (EC). The book is organized into four parts that deliver materials in a way equally attractive for a reader with training in computation or biology. Each of these sections, authored by well-known researchers and experienced practitioners, provides the relevant materials for the interested readers. The first part of this book contains an introductory background to the field. The second part presents the EC approaches for analysis and reconstruction of GRN from gene expression data. The third part of this book covers the contemporary advancements in the automatic construction of gene regulatory and reaction networks and gives direction and guidelines for future research. Finally, the last part of this book focuses on applications of GRNs with EC in other fields, such as design, engineering and robotics. • Provides a reference for current and future research in gene regulatory networks (GRN) using evolutionary computation (EC) • Covers sub-domains of GRN research using EC, such as expression profile analysis, reverse engineering, GRN evolution, applications • Contains useful contents for courses in gene regulatory networks, systems biology, computational biology, and synthetic biology • Delivers state-of-the-art research in genetic algorithms, genetic programming, and swarm intelligence Evolutionary Computation in Gene Regulatory Network Research is a reference for researchers and professionals in computer science, systems biology, and bioinformatics, as well as upper undergraduate, graduate, and postgraduate students. Hitoshi Iba is a Professor in the Department of Information and Communication Engineering, Graduate School of Information Science and Technology, at the University of Tokyo, Toyko, Japan. He is an Associate Editor of the IEEE Transactions on Evolutionary Computation and the journal of Genetic Programming and Evolvable Machines. Nasimul Noman is a lecturer in the School of Electrical Engineering and Computer Science at the University of Newcastle, NSW, Australia. From 2002 to 2012 he was a faculty member at the University of Dhaka, Bangladesh. Noman is an Editor of the BioMed Research International journal. His research interests include computational biology, synthetic biology, and bioinformatics.


Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Author: Elena Marchiori
Publisher: Springer Science & Business Media
Total Pages: 311
Release: 2007-04-02
Genre: Computers
ISBN: 354071782X

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This book constitutes the refereed proceedings of the 5th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2007, held in Valencia, Spain, April 2007. Coverage brings together experts in computer science with experts in bioinformatics and the biological sciences. It presents contributions on fundamental and theoretical issues along with papers dealing with different applications areas.


Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Author: Clara Pizzuti
Publisher: Springer
Total Pages: 259
Release: 2010-04-03
Genre: Computers
ISBN: 3642122116

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This book constitutes the refereed proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2010, held in Istanbul, Turkey, in April 2010 co-located with the Evo* 2010 events. This 15 revised full papers were carefully reviewed and selected from 40 submissions. EvoBIO is the premiere European event for those interested in the interface between evolutionary computation, machine learning, data mining, bioinformatics, and computational biology. Topics addressed by the papers include biomarker discovery, cell simulation and modeling, ecological modeling, fluxomics, gene networks, biotechnology, metabolomics, microarray analysis, phylogenetics, protein interactions, proteomics, sequence analysis and alignment, and systems biology.


Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Author: Leonardo Vanneschi
Publisher: Springer
Total Pages: 226
Release: 2013-02-26
Genre: Computers
ISBN: 3642371892

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This book constitutes the refereed proceedings of the 11th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2013, held in Vienna, Austria, in April 2013, colocated with the Evo* 2013 events EuroGP, EvoCOP, EvoMUSART and EvoApplications. The 10 revised full papers presented together with 9 poster papers were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics in the field of biological data analysis and computational biology. They address important problems in biology, from the molecular and genomic dimension to the individual and population level, often drawing inspiration from biological systems in oder to produce solutions to biological problems.


Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Author: Mario Giacobini
Publisher: Springer
Total Pages: 266
Release: 2012-03-23
Genre: Computers
ISBN: 3642290663

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This book constitutes the refereed proceedings of the 10th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2012, held in Málaga, Spain, in April 2012 co-located with the Evo* 2012 events. The 15 revised full papers presented together with 8 poster papers were carefully reviewed and selected from numerous submissions. Computational Biology is a wide and varied discipline, incorporating aspects of statistical analysis, data structure and algorithm design, machine learning, and mathematical modeling toward the processing and improved understanding of biological data. Experimentalists now routinely generate new information on such a massive scale that the techniques of computer science are needed to establish any meaningful result. As a consequence, biologists now face the challenges of algorithmic complexity and tractability, and combinatorial explosion when conducting even basic analyses.


Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Author: Clara Pizzuti
Publisher: Springer
Total Pages: 214
Release: 2009-04-10
Genre: Computers
ISBN: 3642011845

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This book constitutes the refereed proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2009, held in Tübingen, Germany, in April 2009 colocated with the Evo* 2009 events. The 17 revised full papers were carefully reviewed and selected from 44 submissions. EvoBio is the premiere European event for experts in computer science meeting with experts in bioinformatics and the biological sciences, all interested in the interface between evolutionary computation, machine learning, data mining, bioinformatics, and computational biology. Topics addressed by the papers include biomarker discovery, cell simulation and modeling, ecological modeling, uxomics, gene networks, biotechnology, metabolomics, microarray analysis, phylogenetics, protein interactions, proteomics, sequence analysis and alignment, as well as systems biology.


Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Author: Elena Marchiori
Publisher: Springer
Total Pages: 302
Release: 2007-06-21
Genre: Computers
ISBN: 3540717838

Download Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics Book in PDF, ePub and Kindle

This book constitutes the refereed proceedings of the 5th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2007, held in Valencia, Spain, April 2007. Coverage brings together experts in computer science with experts in bioinformatics and the biological sciences. It presents contributions on fundamental and theoretical issues along with papers dealing with different applications areas.


Frontiers of Evolutionary Computation

Frontiers of Evolutionary Computation
Author: Anil Menon
Publisher: Springer Science & Business Media
Total Pages: 288
Release: 2006-04-11
Genre: Computers
ISBN: 1402077823

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Frontiers of Evolutionary Computation brings together eleven contributions by international leading researchers discussing what significant issues still remain unresolved in the field of Evolutionary Computation (Ee. They explore such topics as the role of building blocks, the balancing of exploration with exploitation, the modeling of EC algorithms, the connection with optimization theory and the role of EC as a meta-heuristic method, to name a few. The articles feature a mixture of informal discussion interspersed with formal statements, thus providing the reader an opportunity to observe a wide range of EC problems from the investigative perspective of world-renowned researchers. These prominent researchers include: Heinz M]hlenbein, Kenneth De Jong, Carlos Cotta and Pablo Moscato, Lee Altenberg, Gary A. Kochenberger, Fred Glover, Bahram Alidaee and Cesar Rego, William G. Macready, Christopher R. Stephens and Riccardo Poli, Lothar M. Schmitt, John R. Koza, Matthew J. Street and Martin A. Keane, Vivek Balaraman, Wolfgang Banzhaf and Julian Miller.