Protein Structure Prediction and Gene Bi-clustering by Soft Computing Approach
Author: Dr Veera Talukdar
Publisher: Archers & Elevators Publishing House
Published:
Total Pages:
ISBN-13: 9386501783
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Soft Computing Techniques in Vision Science
Author: Srikanta Patnaik
Publisher: Springer Science & Business Media
Published: 2012-02-15
Total Pages: 222
ISBN-13: 364225506X
DOWNLOAD EBOOKThis Special Edited Volume is a unique approach towards Computational solution for the upcoming field of study called Vision Science. From a scientific firmament Optics, Ophthalmology, and Optical Science has surpassed an Odyssey of optimizing configurations of Optical systems, Surveillance Cameras and other Nano optical devices with the metaphor of Nano Science and Technology. Still these systems are falling short of its computational aspect to achieve the pinnacle of human vision system. In this edited volume much attention has been given to address the coupling issues Computational Science and Vision Studies. It is a comprehensive collection of research works addressing various related areas of Vision Science like Visual Perception and Visual system, Cognitive Psychology, Neuroscience, Psychophysics and Ophthalmology, linguistic relativity, color vision etc. This issue carries some latest developments in the form of research articles and presentations. The volume is rich of contents with technical tools for convenient experimentation in Vision Science. There are 18 research papers having significance in an array of application areas. The volume claims to be an effective compendium of computing developments like Frequent Pattern Mining, Genetic Algorithm, Gabor Filter, Support Vector Machine, Region Based Mask Filter, 4D stereo camera systems, Principal Component Analysis etc. The detailed analysis of the papers can immensely benefit to the researchers of this domain. It can be an Endeavour in the pursuit of adding value in the existing stock of knowledge in Vision Science.
Handbook of Research on Computational Intelligence Applications in Bioinformatics
Author: Dash, Sujata
Publisher: IGI Global
Published: 2016-06-20
Total Pages: 543
ISBN-13: 1522504281
DOWNLOAD EBOOKDevelopments in the areas of biology and bioinformatics are continuously evolving and creating a plethora of data that needs to be analyzed and decrypted. Since it can be difficult to decipher the multitudes of data within these areas, new computational techniques and tools are being employed to assist researchers in their findings. The Handbook of Research on Computational Intelligence Applications in Bioinformatics examines emergent research in handling real-world problems through the application of various computation technologies and techniques. Featuring theoretical concepts and best practices in the areas of computational intelligence, artificial intelligence, big data, and bio-inspired computing, this publication is a critical reference source for graduate students, professionals, academics, and researchers.
Rough Sets and Knowledge Technology
Author: JingTao Yao
Publisher: Springer
Published: 2007-06-26
Total Pages: 589
ISBN-13: 3540724583
DOWNLOAD EBOOKThis book constitutes the refereed proceedings of the Second International Conference on Rough Sets and Knowledge Technology, RSKT 2007, held in Toronto, Canada in May 2007 in conjunction with the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2007, both as part of the Joint Rough Set Symposium, JRS 2007.
Scalable Pattern Recognition Algorithms
Author: Pradipta Maji
Publisher: Springer Science & Business Media
Published: 2014-03-19
Total Pages: 316
ISBN-13: 3319056301
DOWNLOAD EBOOKThis book addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models. The text reviews both established and cutting-edge research, providing a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics. Features: integrates different soft computing and machine learning methodologies with pattern recognition tasks; discusses in detail the integration of different techniques for handling uncertainties in decision-making and efficiently mining large biological datasets; presents a particular emphasis on real-life applications, such as microarray expression datasets and magnetic resonance images; includes numerous examples and experimental results to support the theoretical concepts described; concludes each chapter with directions for future research and a comprehensive bibliography.
Artificial intelligence and soft computing
Author: M. H. Hamza
Publisher:
Published: 1999
Total Pages: 660
ISBN-13:
DOWNLOAD EBOOKEncyclopedia of Bioinformatics and Computational Biology
Author:
Publisher: Elsevier
Published: 2018-08-21
Total Pages: 3421
ISBN-13: 0128114320
DOWNLOAD EBOOKEncyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, Three Volume Set combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative –omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries. Brings together information from computer science, information technology, mathematics, statistics and biotechnology Written and reviewed by leading experts in the field, providing a unique and authoritative resource Focuses on the main theoretical and methodological concepts before expanding on specific topics and applications Includes interactive images, multimedia tools and crosslinking to further resources and databases
Similarity-Based Pattern Analysis and Recognition
Author: Marcello Pelillo
Publisher: Springer Science & Business Media
Published: 2013-11-26
Total Pages: 293
ISBN-13: 1447156285
DOWNLOAD EBOOKThis accessible text/reference presents a coherent overview of the emerging field of non-Euclidean similarity learning. The book presents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely theoretical challenges to practical, real-world applications. The coverage includes both supervised and unsupervised learning paradigms, as well as generative and discriminative models. Topics and features: explores the origination and causes of non-Euclidean (dis)similarity measures, and how they influence the performance of traditional classification algorithms; reviews similarity measures for non-vectorial data, considering both a “kernel tailoring” approach and a strategy for learning similarities directly from training data; describes various methods for “structure-preserving” embeddings of structured data; formulates classical pattern recognition problems from a purely game-theoretic perspective; examines two large-scale biomedical imaging applications.
Multiobjective Genetic Algorithms for Clustering
Author: Ujjwal Maulik
Publisher: Springer Science & Business Media
Published: 2011-09-01
Total Pages: 292
ISBN-13: 3642166156
DOWNLOAD EBOOKThis is the first book primarily dedicated to clustering using multiobjective genetic algorithms with extensive real-life applications in data mining and bioinformatics. The authors first offer detailed introductions to the relevant techniques – genetic algorithms, multiobjective optimization, soft computing, data mining and bioinformatics. They then demonstrate systematic applications of these techniques to real-world problems in the areas of data mining, bioinformatics and geoscience. The authors offer detailed theoretical and statistical notes, guides to future research, and chapter summaries. The book can be used as a textbook and as a reference book by graduate students and academic and industrial researchers in the areas of soft computing, data mining, bioinformatics and geoscience.
Computational Knowledge Discovery for Bioinformatics Research
Author: Li, Xiao-Li
Publisher: IGI Global
Published: 2012-06-30
Total Pages: 464
ISBN-13: 1466617861
DOWNLOAD EBOOK"This book discusses the most significant research and latest practices in computational knowledge discovery approaches to bioinformatics in a cross-disciplinary manner that is useful for researchers, practitioners, academicians, mathematicians, statisticians, and computer scientists involved in the many facets of bioinformatics"--
