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Computational Intelligence And Its Applications: Evolutionary Computation, Fuzzy Logic, Neural Network And Support Vector Machine Techniques

Computational Intelligence And Its Applications: Evolutionary Computation, Fuzzy Logic, Neural Network And Support Vector Machine Techniques
Author: Hung Tan Nguyen
Publisher: World Scientific
Total Pages: 318
Release: 2012-07-17
Genre: Computers
ISBN: 1908977078

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This book focuses on computational intelligence techniques and their applications — fast-growing and promising research topics that have drawn a great deal of attention from researchers over the years. It brings together many different aspects of the current research on intelligence technologies such as neural networks, support vector machines, fuzzy logic and evolutionary computation, and covers a wide range of applications from pattern recognition and system modeling, to intelligent control problems and biomedical applications. Fundamental concepts and essential analysis of various computational techniques are presented to offer a systematic and effective tool for better treatment of different applications, and simulation and experimental results are included to illustrate the design procedure and the effectiveness of the approaches./a


Computational Intelligence and Pattern Analysis in Biology Informatics

Computational Intelligence and Pattern Analysis in Biology Informatics
Author: Ujjwal Maulik
Publisher: John Wiley & Sons
Total Pages: 552
Release: 2011-03-21
Genre: Medical
ISBN: 1118097807

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An invaluable tool in Bioinformatics, this unique volume provides both theoretical and experimental results, and describes basic principles of computational intelligence and pattern analysis while deepening the reader's understanding of the ways in which these principles can be used for analyzing biological data in an efficient manner. This book synthesizes current research in the integration of computational intelligence and pattern analysis techniques, either individually or in a hybridized manner. The purpose is to analyze biological data and enable extraction of more meaningful information and insight from it. Biological data for analysis include sequence data, secondary and tertiary structure data, and microarray data. These data types are complex and advanced methods are required, including the use of domain-specific knowledge for reducing search space, dealing with uncertainty, partial truth and imprecision, efficient linear and/or sub-linear scalability, incremental approaches to knowledge discovery, and increased level and intelligence of interactivity with human experts and decision makers Chapters authored by leading researchers in CI in biology informatics. Covers highly relevant topics: rational drug design; analysis of microRNAs and their involvement in human diseases. Supplementary material included: program code and relevant data sets correspond to chapters.


Application of Computational Intelligence to Biology

Application of Computational Intelligence to Biology
Author: Ravi Bhramaramba
Publisher: Springer
Total Pages: 107
Release: 2016-05-06
Genre: Technology & Engineering
ISBN: 9811003912

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This book is a contribution of translational and allied research to the proceedings of the International Conference on Computational Intelligence and Soft Computing. It explains how various computational intelligence techniques can be applied to investigate various biological problems. It is a good read for Research Scholars, Engineers, Medical Doctors and Bioinformatics researchers.


Applications of Computational Intelligence in Biology

Applications of Computational Intelligence in Biology
Author: Tomasz G. Smolinski
Publisher: Springer Science & Business Media
Total Pages: 439
Release: 2008-06-10
Genre: Mathematics
ISBN: 3540785337

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Computational Intelligence (CI) has been a tremendously active area of - search for the past decade or so. There are many successful applications of CI in many sub elds of biology, including bioinformatics, computational - nomics, protein structure prediction, or neuronal systems modeling and an- ysis. However, there still are many open problems in biology that are in d- perate need of advanced and e cient computational methodologies to deal with tremendous amounts of data that those problems are plagued by. - fortunately, biology researchers are very often unaware of the abundance of computational techniques that they could put to use to help them analyze and understand the data underlying their research inquiries. On the other hand, computational intelligence practitioners are often unfamiliar with the part- ular problems that their new, state-of-the-art algorithms could be successfully applied for. The separation between the two worlds is partially caused by the use of di erent languages in these two spheres of science, but also by the relatively small number of publications devoted solely to the purpose of fac- itating the exchange of new computational algorithms and methodologies on one hand, and the needs of the biology realm on the other. The purpose of this book is to provide a medium for such an exchange of expertise and concerns. In order to achieve the goal, we have solicited cont- butions from both computational intelligence as well as biology researchers.


Applications of Computational Intelligence in Biology

Applications of Computational Intelligence in Biology
Author: Tomasz G. Smolinski
Publisher: Springer
Total Pages: 428
Release: 2009-08-29
Genre: Mathematics
ISBN: 9783540849261

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Computational Intelligence (CI) has been a tremendously active area of - search for the past decade or so. There are many successful applications of CI in many sub elds of biology, including bioinformatics, computational - nomics, protein structure prediction, or neuronal systems modeling and an- ysis. However, there still are many open problems in biology that are in d- perate need of advanced and e cient computational methodologies to deal with tremendous amounts of data that those problems are plagued by. - fortunately, biology researchers are very often unaware of the abundance of computational techniques that they could put to use to help them analyze and understand the data underlying their research inquiries. On the other hand, computational intelligence practitioners are often unfamiliar with the part- ular problems that their new, state-of-the-art algorithms could be successfully applied for. The separation between the two worlds is partially caused by the use of di erent languages in these two spheres of science, but also by the relatively small number of publications devoted solely to the purpose of fac- itating the exchange of new computational algorithms and methodologies on one hand, and the needs of the biology realm on the other. The purpose of this book is to provide a medium for such an exchange of expertise and concerns. In order to achieve the goal, we have solicited cont- butions from both computational intelligence as well as biology researchers.


Practical Applications of Computational Biology and Bioinformatics, 14th International Conference (PACBB 2020)

Practical Applications of Computational Biology and Bioinformatics, 14th International Conference (PACBB 2020)
Author:
Publisher:
Total Pages: 231
Release: 2021
Genre: Bioinformatics
ISBN: 9783030545697

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This book highlights the latest research on practical applications of computational biology and bioinformatics, and addresses emerging experimental and sequencing techniques that are posing new challenges for bioinformatics and computational biology. Successfully applying these techniques calls for new algorithms and approaches from fields such as statistics, data mining, machine learning, optimization, computer science, and artificial intelligence. In response to these challenges, we have seen the rise of a new generation of interdisciplinary scientists with a strong background in the biological and computational sciences.These proceedings include 21 papers covering many different subfields of bioinformatics and computational biology. Focusing on interdisciplinary applications that combine e.g. bioinformatics, chemoinformatics, and system biology, they are intended to promote the collaboration of scientists from different research groups and with different backgrounds (computer scientists, mathematicians, biologists) to reach breakthrough solutions and overcome the challenges outlined above.


Practical Applications of Computational Biology & Bioinformatics, 15th International Conference (PACBB 2021)

Practical Applications of Computational Biology & Bioinformatics, 15th International Conference (PACBB 2021)
Author: Miguel Rocha
Publisher: Springer Nature
Total Pages: 188
Release: 2021-08-27
Genre: Technology & Engineering
ISBN: 3030862585

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This book features novel research papers spanning many different subfields in bioinformatics and computational biology, presenting the latest research on the practical applications to promote fruitful interactions between young researchers in different areas related to the field. Clearly, biology is increasingly becoming a science of information, requiring tools from the computational sciences. To address these challenges, we have seen the emergence of a new generation of interdisciplinary scientists with a strong background in the biological and computational sciences. PACBB'21 expects to contribute to this effort by encouraging a successful collaboration of researchers in different areas related to bioinformatics. The PACBB'21 technical program included 17 papers covering many different subfields in bioinformatics and computational biology. Therefore, this conference, held in Salamanca (Spain), definitely promotes the collaboration of scientists from different research groups and with different backgrounds (computer scientists, mathematicians, biologists) to reach breakthrough solutions for these challenges.


Computational Intelligence and Data Sciences

Computational Intelligence and Data Sciences
Author: Ayodeji Olalekan Salau
Publisher: CRC Press
Total Pages: 287
Release: 2022-03-10
Genre: Computers
ISBN: 1000541754

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This book presents futuristic trends in computational intelligence including algorithms as applicable to different application domains in health informatics covering bio-medical, bioinformatics, and biological sciences. Latest evolutionary approaches to solve optimization problems under biomedical engineering field are discussed. It provides conceptual framework with a focus on application of computational intelligence techniques in the domain of biomedical engineering and health informatics including real-time issues.


Computational Intelligence in Bioinformatics

Computational Intelligence in Bioinformatics
Author: Gary B. Fogel
Publisher: John Wiley & Sons
Total Pages: 377
Release: 2007-12-10
Genre: Computers
ISBN: 0470199083

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Combining biology, computer science, mathematics, and statistics, the field of bioinformatics has become a hot new discipline with profound impacts on all aspects of biology and industrial application. Now, Computational Intelligence in Bioinformatics offers an introduction to the topic, covering the most relevant and popular CI methods, while also encouraging the implementation of these methods to readers' research.


Artificial Intelligence and Molecular Biology

Artificial Intelligence and Molecular Biology
Author: Lawrence Hunter
Publisher:
Total Pages: 484
Release: 1993
Genre: Computers
ISBN:

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These original contributions provide a current sampling of AI approaches to problems of biological significance; they are the first to treat the computational needs of the biology community hand-in-hand with appropriate advances in artificial intelligence. The enormous amount of data generated by the Human Genome Project and other large-scale biological research has created a rich and challenging domain for research in artificial intelligence. These original contributions provide a current sampling of AI approaches to problems of biological significance; they are the first to treat the computational needs of the biology community hand-in-hand with appropriate advances in artificial intelligence. Focusing on novel technologies and approaches, rather than on proven applications, they cover genetic sequence analysis, protein structure representation and prediction, automated data analysis aids, and simulation of biological systems. A brief introductory primer on molecular biology and Al gives computer scientists sufficient background to understand much of the biology discussed in the book. Lawrence Hunter is Director of the Machine Learning Project at the National Library of Medicine, National Institutes of Health.