Bio-kernel Machines And Applications

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Publisher : World Scientific
ISBN 13 : 981128735X
Total Pages : 267 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Bio-kernel Machines And Applications by : Zheng Rong Yang

Download or read book Bio-kernel Machines And Applications written by Zheng Rong Yang and published by World Scientific. This book was released on 2024-03-06 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to its capability of handling very complex problems and its high flexibility in adapting to different algorithms, the kernel machine plays a crucial role in machine learning.Bio-Kernel Machines and Applications will introduce a new type of kernel machine for the exploration and modeling between the genotypic inherent structures of short protein sequences or nucleic sequences and the phenotypic biological properties or functions of proteins or nucleotides.The book seeks to establish the fundamentals of the bio-kernel machines by presenting the basic principle and theory of the kernel machine and the various formats of kernel machines, such as string kernel machines adapted for biological applications. The book will also introduce several biological applications of the mutation matrices, demonstrating how mutation matrices can enhance the efficiency and biological relevance of machine learning models applied in specific biological problems.Through analyzing current applications of bio-kernel machines, readers will delve into the advantages of the bio-kernel machines and explore how bio-kernel machines can be further enhanced to tackle a wide spectrum of biological challenges and pave the way for future advancements.

Kernel Methods in Computational Biology

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Publisher : MIT Press
ISBN 13 : 9780262195096
Total Pages : 428 pages
Book Rating : 4.1/5 (95 download)

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Book Synopsis Kernel Methods in Computational Biology by : Bernhard Schölkopf

Download or read book Kernel Methods in Computational Biology written by Bernhard Schölkopf and published by MIT Press. This book was released on 2004 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: A detailed overview of current research in kernel methods and their application to computational biology.

Kernel Methods in Computational Biology

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Publisher :
ISBN 13 : 9780262292689
Total Pages : pages
Book Rating : 4.2/5 (926 download)

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Book Synopsis Kernel Methods in Computational Biology by : Bernhard Sch?lkopf

Download or read book Kernel Methods in Computational Biology written by Bernhard Sch?lkopf and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Kernel Methods in Bioengineering, Signal and Image Processing

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Publisher : IGI Global
ISBN 13 : 1599040425
Total Pages : 431 pages
Book Rating : 4.5/5 (99 download)

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Book Synopsis Kernel Methods in Bioengineering, Signal and Image Processing by : Gustavo Camps-Valls

Download or read book Kernel Methods in Bioengineering, Signal and Image Processing written by Gustavo Camps-Valls and published by IGI Global. This book was released on 2007-01-01 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book presents an extensive introduction to the field of kernel methods and real world applications. The book is organized in four parts: the first is an introductory chapter providing a framework of kernel methods; the others address Bioegineering, Signal Processing and Communications and Image Processing"--Provided by publisher.

Medical Informatics: Concepts, Methodologies, Tools, and Applications

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Publisher : IGI Global
ISBN 13 : 1605660515
Total Pages : 2772 pages
Book Rating : 4.6/5 (56 download)

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Book Synopsis Medical Informatics: Concepts, Methodologies, Tools, and Applications by : Tan, Joseph

Download or read book Medical Informatics: Concepts, Methodologies, Tools, and Applications written by Tan, Joseph and published by IGI Global. This book was released on 2008-09-30 with total page 2772 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a collection of medical IT research in topics such as clinical knowledge management, medical informatics, mobile health and service delivery, and gene expression.

Encyclopedia of Bioinformatics and Computational Biology

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Publisher : Elsevier
ISBN 13 : 0128114320
Total Pages : 3421 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Encyclopedia of Bioinformatics and Computational Biology by :

Download or read book Encyclopedia of Bioinformatics and Computational Biology written by and published by Elsevier. This book was released on 2018-08-21 with total page 3421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Encyclopedia 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

Computational Science and Its Applications - ICCSA 2005

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Publisher : Springer
ISBN 13 : 3540320458
Total Pages : 1403 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Computational Science and Its Applications - ICCSA 2005 by : Osvaldo Gervasi

Download or read book Computational Science and Its Applications - ICCSA 2005 written by Osvaldo Gervasi and published by Springer. This book was released on 2005-05-02 with total page 1403 pages. Available in PDF, EPUB and Kindle. Book excerpt: The four volume set assembled following The 2005 International Conference on Computational Science and its Applications, ICCSA 2005, held in Suntec International Convention and Exhibition Centre, Singapore, from 9 May 2005 till 12 May 2005, represents the ?ne collection of 540 refereed papers selected from nearly 2,700 submissions. Computational Science has ?rmly established itself as a vital part of many scienti?c investigations, a?ecting researchers and practitioners in areas ranging from applications such as aerospace and automotive, to emerging technologies such as bioinformatics and nanotechnologies, to core disciplines such as ma- ematics, physics, and chemistry. Due to the shear size of many challenges in computational science, the use of supercomputing, parallel processing, and - phisticated algorithms is inevitable and becomes a part of fundamental t- oretical research as well as endeavors in emerging ?elds. Together, these far reaching scienti?c areas contribute to shape this Conference in the realms of state-of-the-art computational science research and applications, encompassing the facilitating theoretical foundations and the innovative applications of such results in other areas.

Springer Handbook of Bio-/Neuro-Informatics

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Publisher : Springer Science & Business Media
ISBN 13 : 3642305741
Total Pages : 1239 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Springer Handbook of Bio-/Neuro-Informatics by : Nikola Kasabov

Download or read book Springer Handbook of Bio-/Neuro-Informatics written by Nikola Kasabov and published by Springer Science & Business Media. This book was released on 2013-11-30 with total page 1239 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Springer Handbook of Bio-/Neuro-Informatics is the first published book in one volume that explains together the basics and the state-of-the-art of two major science disciplines in their interaction and mutual relationship, namely: information sciences, bioinformatics and neuroinformatics. Bioinformatics is the area of science which is concerned with the information processes in biology and the development and applications of methods, tools and systems for storing and processing of biological information thus facilitating new knowledge discovery. Neuroinformatics is the area of science which is concerned with the information processes in biology and the development and applications of methods, tools and systems for storing and processing of biological information thus facilitating new knowledge discovery. The text contains 62 chapters organized in 12 parts, 6 of them covering topics from information science and bioinformatics, and 6 cover topics from information science and neuroinformatics. Each chapter consists of three main sections: introduction to the subject area, presentation of methods and advanced and future developments. The Springer Handbook of Bio-/Neuroinformatics can be used as both a textbook and as a reference for postgraduate study and advanced research in these areas. The target audience includes students, scientists, and practitioners from the areas of information, biological and neurosciences. With Forewords by Shun-ichi Amari of the Brain Science Institute, RIKEN, Saitama and Karlheinz Meier of the University of Heidelberg, Kirchhoff-Institute of Physics and Co-Director of the Human Brain Project.

Artificial Neural Networks

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Publisher : Springer
ISBN 13 : 3319099035
Total Pages : 487 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Artificial Neural Networks by : Petia Koprinkova-Hristova

Download or read book Artificial Neural Networks written by Petia Koprinkova-Hristova and published by Springer. This book was released on 2014-09-02 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book reports on the latest theories on artificial neural networks, with a special emphasis on bio-neuroinformatics methods. It includes twenty-three papers selected from among the best contributions on bio-neuroinformatics-related issues, which were presented at the International Conference on Artificial Neural Networks, held in Sofia, Bulgaria, on September 10-13, 2013 (ICANN 2013). The book covers a broad range of topics concerning the theory and applications of artificial neural networks, including recurrent neural networks, super-Turing computation and reservoir computing, double-layer vector perceptrons, nonnegative matrix factorization, bio-inspired models of cell communities, Gestalt laws, embodied theory of language understanding, saccadic gaze shifts and memory formation, and new training algorithms for Deep Boltzmann Machines, as well as dynamic neural networks and kernel machines. It also reports on new approaches to reinforcement learning, optimal control of discrete time-delay systems, new algorithms for prototype selection, and group structure discovering. Moreover, the book discusses one-class support vector machines for pattern recognition, handwritten digit recognition, time series forecasting and classification, and anomaly identification in data analytics and automated data analysis. By presenting the state-of-the-art and discussing the current challenges in the fields of artificial neural networks, bioinformatics and neuroinformatics, the book is intended to promote the implementation of new methods and improvement of existing ones, and to support advanced students, researchers and professionals in their daily efforts to identify, understand and solve a number of open questions in these fields.

Bio-Inspired Models of Network, Information, and Computing Systems

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Publisher : Springer
ISBN 13 : 3642326153
Total Pages : 712 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Bio-Inspired Models of Network, Information, and Computing Systems by : Junichi Suzuki

Download or read book Bio-Inspired Models of Network, Information, and Computing Systems written by Junichi Suzuki and published by Springer. This book was released on 2012-07-25 with total page 712 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 5th International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems (BIONETICS 2010) which was held in Boston, USA, in December 2010. The 78 revised full papers were carefully reviewed and selected from numerous submissions for inclusion in the proceedings. BIONETICS 2010 aimed to provide the understanding of the fundamental principles and design strategies in biological systems and leverage those understandings to build bio-inspired systems.

Application of Computational Intelligence to Biology

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Publisher : Springer
ISBN 13 : 9811003912
Total Pages : 107 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Application of Computational Intelligence to Biology by : Ravi Bhramaramba

Download or read book Application of Computational Intelligence to Biology written by Ravi Bhramaramba and published by Springer. This book was released on 2016-05-06 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Data Mining and Mathematical Programming

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Publisher : American Mathematical Soc.
ISBN 13 : 9780821870402
Total Pages : 252 pages
Book Rating : 4.8/5 (74 download)

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Book Synopsis Data Mining and Mathematical Programming by : Panos M. Pardalos

Download or read book Data Mining and Mathematical Programming written by Panos M. Pardalos and published by American Mathematical Soc.. This book was released on 2008-04-09 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining aims at finding interesting, useful or profitable information in very large databases. The enormous increase in the size of available scientific and commercial databases (data avalanche) as well as the continuing and exponential growth in performance of present day computers make data mining a very active field. In many cases, the burgeoning volume of data sets has grown so large that it threatens to overwhelm rather than enlighten scientists. Therefore, traditional methods are revised and streamlined, complemented by many new methods to address challenging new problems. Mathematical Programming plays a key role in this endeavor. It helps us to formulate precise objectives (e.g., a clustering criterion or a measure of discrimination) as well as the constraints imposed on the solution (e.g., find a partition, a covering or a hierarchy in clustering). It also provides powerful mathematical tools to build highly performing exact or approximate algorithms. This book is based on lectures presented at the workshop on "Data Mining and Mathematical Programming" (October 10-13, 2006, Montreal) and will be a valuable scientific source of information to faculty, students, and researchers in optimization, data analysis and data mining, as well as people working in computer science, engineering and applied mathematics.

Pacific Symposium On Biocomputing 2014

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Publisher : World Scientific
ISBN 13 : 9814583235
Total Pages : 436 pages
Book Rating : 4.8/5 (145 download)

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Book Synopsis Pacific Symposium On Biocomputing 2014 by : Russ B Altman

Download or read book Pacific Symposium On Biocomputing 2014 written by Russ B Altman and published by World Scientific. This book was released on 2013-11-19 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Pacific Symposium on Biocomputing (PSB) 2014 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2014 will be held from January 3 - 7, 2014 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2014 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's “hot topics.” In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field.

Encyclopedia of Data Warehousing and Mining, Second Edition

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Publisher : IGI Global
ISBN 13 : 1605660116
Total Pages : 2542 pages
Book Rating : 4.6/5 (56 download)

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Book Synopsis Encyclopedia of Data Warehousing and Mining, Second Edition by : Wang, John

Download or read book Encyclopedia of Data Warehousing and Mining, Second Edition written by Wang, John and published by IGI Global. This book was released on 2008-08-31 with total page 2542 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Machine Learning Algorithms for Data Scientists: An Overview

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Publisher : Vinaitheerthan Renganathan
ISBN 13 : 9354737692
Total Pages : 102 pages
Book Rating : 4.3/5 (547 download)

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Book Synopsis Machine Learning Algorithms for Data Scientists: An Overview by : Vinaitheerthan Renganathan

Download or read book Machine Learning Algorithms for Data Scientists: An Overview written by Vinaitheerthan Renganathan and published by Vinaitheerthan Renganathan. This book was released on 2021-06-02 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning models are widely used in different fields such as Artificial Intelligence, Business, Clinical and Biological Sciences which includes self-driving cars, predictive models, disease prediction, genome sequencing, spam filtering, product recommendation, fraud detection and image recognition . It has gained importance due to its capabilities of handling large volume of data, prediction and classification accuracy and validation procedures. Machine Learning models are built on the basis of statistical and mathematical algorithms. One important aspect of machine learning is it does not stick to standard algorithm throughout modeling process instead it learns from the data over a period of time and improves the accuracy of the model. Classification and prediction tasks are carried out based on the characteristics, patterns and relationship of the features present in the data set. Machine learning model also forms the basis of Deep Learning models. Machine Learning models involve supervised learning, unsupervised learning, semi supervised learning and reinforcement learning algorithms. Data Scientists analyze, model and visualize data and provide actionable insights to the decision makers. Machine learning algorithms and tools help the data scientist to carry out these tasks with the help of software such R and Python. This book provides an overview of Machine Learning models, algorithms and its application in different fields through the use of R Software. It also provides short introduction to R software for the benefit of users. Author assumes the users have basic descriptive and inferential statistical knowledge which is essential for building Machine Learning models. Data sets used in the books can be downloaded from the author’s website.

Learning with Kernels

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Publisher : MIT Press
ISBN 13 : 0262536579
Total Pages : 645 pages
Book Rating : 4.2/5 (625 download)

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Book Synopsis Learning with Kernels by : Bernhard Scholkopf

Download or read book Learning with Kernels written by Bernhard Scholkopf and published by MIT Press. This book was released on 2018-06-05 with total page 645 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to Support Vector Machines and related kernel methods. In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs—-kernels—for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics. Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.

Introduction to Machine Learning, fourth edition

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Publisher : MIT Press
ISBN 13 : 0262358069
Total Pages : 709 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Introduction to Machine Learning, fourth edition by : Ethem Alpaydin

Download or read book Introduction to Machine Learning, fourth edition written by Ethem Alpaydin and published by MIT Press. This book was released on 2020-03-24 with total page 709 pages. Available in PDF, EPUB and Kindle. Book excerpt: A substantially revised fourth edition of a comprehensive textbook, including new coverage of recent advances in deep learning and neural networks. The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Machine learning underlies such exciting new technologies as self-driving cars, speech recognition, and translation applications. This substantially revised fourth edition of a comprehensive, widely used machine learning textbook offers new coverage of recent advances in the field in both theory and practice, including developments in deep learning and neural networks. The book covers a broad array of topics not usually included in introductory machine learning texts, including supervised learning, Bayesian decision theory, parametric methods, semiparametric methods, nonparametric methods, multivariate analysis, hidden Markov models, reinforcement learning, kernel machines, graphical models, Bayesian estimation, and statistical testing. The fourth edition offers a new chapter on deep learning that discusses training, regularizing, and structuring deep neural networks such as convolutional and generative adversarial networks; new material in the chapter on reinforcement learning that covers the use of deep networks, the policy gradient methods, and deep reinforcement learning; new material in the chapter on multilayer perceptrons on autoencoders and the word2vec network; and discussion of a popular method of dimensionality reduction, t-SNE. New appendixes offer background material on linear algebra and optimization. End-of-chapter exercises help readers to apply concepts learned. Introduction to Machine Learning can be used in courses for advanced undergraduate and graduate students and as a reference for professionals.