Neural Networks and Genome Informatics
Neural Networks and Genome Informatics

Author: C.H. Wu

Publisher: Elsevier

Published: 2012-12-02

Total Pages: 218

ISBN-13: 0080537375

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This book is a comprehensive reference in the field of neural networks and genome informatics. The tutorial of neural network foundations introduces basic neural network technology and terminology. This is followed by an in-depth discussion of special system designs for building neural networks for genome informatics, and broad reviews and evaluations of current state-of-the-art methods in the field. This book concludes with a description of open research problems and future research directions.

Neural Networks for Applied Sciences and Engineering
Neural Networks for Applied Sciences and Engineering

Author: Sandhya Samarasinghe

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 596

ISBN-13: 1420013068

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In response to the exponentially increasing need to analyze vast amounts of data, Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition provides scientists with a simple but systematic introduction to neural networks. Beginning with an introductory discussion on the role of neural networks in

Bioinformatics Technologies
Bioinformatics Technologies

Author: Yi-Ping Phoebe Chen

Publisher: Springer Science & Business Media

Published: 2005-12-12

Total Pages: 405

ISBN-13: 354026888X

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Solving modern biological problems requires advanced computational methods. Bioinformatics evolved from the active interaction of two fast-developing disciplines, biology and information technology. The central issue of this emerging field is the transformation of often distributed and unstructured biological data into meaningful information. This book describes the application of well-established concepts and techniques from areas like data mining, machine learning, database technologies, and visualization techniques to problems like protein data analysis, genome analysis and sequence databases. Chen has collected contributions from leading researchers in each area. The chapters can be read independently, as each offers a complete overview of its specific area, or, combined, this monograph is a comprehensive treatment that will appeal to students, researchers, and R&D professionals in industry who need a state-of-the-art introduction into this challenging and exciting young field.

Proceedings of the International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2013
Proceedings of the International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2013

Author: Suresh Chandra Satapathy

Publisher: Springer Science & Business Media

Published: 2013-10-05

Total Pages: 553

ISBN-13: 3319029312

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This volume contains the papers presented at the Second International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA-2013) held during 14-16 November 2013 organized by Bhubaneswar Engineering College (BEC), Bhubaneswar, Odisha, India. It contains 63 papers focusing on application of intelligent techniques which includes evolutionary computation techniques like genetic algorithm, particle swarm optimization techniques, teaching-learning based optimization etc for various engineering applications such as data mining, Fuzzy systems, Machine Intelligence and ANN, Web technologies and Multimedia applications and Intelligent computing and Networking etc.

Advances in Bioinformatics
Advances in Bioinformatics

Author: Vijai Singh

Publisher: Springer Nature

Published: 2021-07-31

Total Pages: 446

ISBN-13: 9813361913

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This book presents the latest developments in bioinformatics, highlighting the importance of bioinformatics in genomics, transcriptomics, metabolism and cheminformatics analysis, as well as in drug discovery and development. It covers tools, data mining and analysis, protein analysis, computational vaccine, and drug design. Covering cheminformatics, computational evolutionary biology and the role of next-generation sequencing and neural network analysis, it also discusses the use of bioinformatics tools in the development of precision medicine. This book offers a valuable source of information for not only beginners in bioinformatics, but also for students, researchers, scientists, clinicians, practitioners, policymakers, and stakeholders who are interested in harnessing the potential of bioinformatics in many areas.

Statistical Learning Using Neural Networks
Statistical Learning Using Neural Networks

Author: Basilio de Braganca Pereira

Publisher: CRC Press

Published: 2020-08-25

Total Pages: 286

ISBN-13: 0429775547

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Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks starting from the basics and increasingly demanding more effort from readers, who can learn the theory and its applications in statistical methods with concrete Python code examples. It presents a wide range of widely used statistical methodologies, applied in several research areas with Python code examples, which are available online. It is suitable for scientists and developers as well as graduate students. Key Features: Discusses applications in several research areas Covers a wide range of widely used statistical methodologies Includes Python code examples Gives numerous neural network models This book covers fundamental concepts on Neural Networks including Multivariate Statistics Neural Networks, Regression Neural Network Models, Survival Analysis Networks, Time Series Forecasting Networks, Control Chart Networks, and Statistical Inference Results. This book is suitable for both teaching and research. It introduces neural networks and is a guide for outsiders of academia working in data mining and artificial intelligence (AI). This book brings together data analysis from statistics to computer science using neural networks.

Handbook on Neural Information Processing
Handbook on Neural Information Processing

Author: Monica Bianchini

Publisher: Springer Science & Business Media

Published: 2013-04-12

Total Pages: 547

ISBN-13: 3642366570

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This handbook presents some of the most recent topics in neural information processing, covering both theoretical concepts and practical applications. The contributions include: Deep architectures Recurrent, recursive, and graph neural networks Cellular neural networks Bayesian networks Approximation capabilities of neural networks Semi-supervised learning Statistical relational learning Kernel methods for structured data Multiple classifier systems Self organisation and modal learning Applications to content-based image retrieval, text mining in large document collections, and bioinformatics This book is thought particularly for graduate students, researchers and practitioners, willing to deepen their knowledge on more advanced connectionist models and related learning paradigms.

Mobile Devices and Smart Gadgets in Medical Sciences
Mobile Devices and Smart Gadgets in Medical Sciences

Author: Umair, Sajid

Publisher: IGI Global

Published: 2020-02-21

Total Pages: 363

ISBN-13: 1799825221

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Each day, new applications and methods are developed for utilizing technology in the field of medical sciences, both as diagnostic tools and as methods for patients to access their medical information through their personal gadgets. However, the maximum potential for the application of new technologies within the medical field has not yet been realized. Mobile Devices and Smart Gadgets in Medical Sciences is a pivotal reference source that explores different mobile applications, tools, software, and smart gadgets and their applications within the field of healthcare. Covering a wide range of topics such as artificial intelligence, telemedicine, and oncology, this book is ideally designed for medical practitioners, mobile application developers, technology developers, software experts, computer engineers, programmers, ICT innovators, policymakers, researchers, academicians, and students.

Introduction to Machine Learning and Bioinformatics
Introduction to Machine Learning and Bioinformatics

Author: Sushmita Mitra

Publisher: CRC Press

Published: 2008-06-05

Total Pages: 386

ISBN-13: 1420011782

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Lucidly Integrates Current Activities Focusing on both fundamentals and recent advances, Introduction to Machine Learning and Bioinformatics presents an informative and accessible account of the ways in which these two increasingly intertwined areas relate to each other. Examines Connections between Machine Learning & Bioinformatics The book begins with a brief historical overview of the technological developments in biology. It then describes the main problems in bioinformatics and the fundamental concepts and algorithms of machine learning. After forming this foundation, the authors explore how machine learning techniques apply to bioinformatics problems, such as electron density map interpretation, biclustering, DNA sequence analysis, and tumor classification. They also include exercises at the end of some chapters and offer supplementary materials on their website. Explores How Machine Learning Techniques Can Help Solve Bioinformatics Problems Shedding light on aspects of both machine learning and bioinformatics, this text shows how the innovative tools and techniques of machine learning help extract knowledge from the deluge of information produced by today’s biological experiments.

Human Genome Informatics
Human Genome Informatics

Author: Christophe Lambert

Publisher: Academic Press

Published: 2018-08-02

Total Pages: 316

ISBN-13: 0128134313

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Human Genome Informatics: Translating Genes into Health examines the most commonly used electronic tools for translating genomic information into clinically meaningful formats. By analyzing and comparing interpretation methods of whole genome data, the book discusses the possibilities of their application in genomic and translational medicine. Topics such as electronic decision-making tools, translation algorithms, interpretation and translation of whole genome data for rare diseases are thoroughly explored. In addition, discussions of current human genome databases and the possibilities of big data in genomic medicine are presented. With an updated approach on recent techniques and current human genomic databases, the book is a valuable source for students and researchers in genome and medical informatics. It is also ideal for workers in the bioinformatics industry who are interested in recent developments in the field. - Provides an overview of the most commonly used electronic tools to translate genomic information - Brings an update on the existing human genomic databases that directly impact genome interpretation - Summarizes and comparatively analyzes interpretation methods of whole genome data and their application in genomic medicine