Download or read online books in PDF, EPUB and Mobi Format. Click Download or Read Online button to get book now. This site is like a library, Use search box in the widget to get ebook that you want.

Bioinformatics

Bioinformatics Author Pierre Baldi
ISBN-10 026202506X
Release 2001
Pages 452
Download Link Click Here

A guide to machine learning approaches and their application to the analysis of biological data.



Introduction to Machine Learning

Introduction to Machine Learning Author Ethem Alpaydin
ISBN-10 9780262028189
Release 2014-08-29
Pages 640
Download Link Click Here

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. Subjects include supervised learning; Bayesian decision theory; parametric, semi-parametric, and nonparametric methods; multivariate analysis; hidden Markov models; reinforcement learning; kernel machines; graphical models; Bayesian estimation; and statistical testing.Machine learning is rapidly becoming a skill that computer science students must master before graduation. The third edition of Introduction to Machine Learning reflects this shift, with added support for beginners, including selected solutions for exercises and additional example data sets (with code available online). Other substantial changes include discussions of outlier detection; ranking algorithms for perceptrons and support vector machines; matrix decomposition and spectral methods; distance estimation; new kernel algorithms; deep learning in multilayered perceptrons; and the nonparametric approach to Bayesian methods. All learning algorithms are explained so that students can easily move from the equations in the book to a computer program. The book can be used by both advanced undergraduates and graduate students. It will also be of interest to professionals who are concerned with the application of machine learning methods.



Deep Learning

Deep Learning Author Ian Goodfellow
ISBN-10 9780262035613
Release 2016-11-18
Pages 800
Download Link Click Here

An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.



Convergence and Hybrid Information Technology

Convergence and Hybrid Information Technology Author Geuk Lee
ISBN-10 9783642326455
Release 2012-08-21
Pages 763
Download Link Click Here

This book constitutes the refereed proceedings of the 6th International Conference on Convergence and Hybrid Information Technology, ICHIT 2012, held in Daejeon, Korea, in August 2012. The 94 revised full papers presented were carefully reviewed and selected from 196 submissions. The papers are organized in topical sections on communications and networking; HCI and virtual reality; image processing and pattern recognition; hardware design and applications; computational biology and medical information; data mining and information retrieval; security and safety system; software engineering; workshop on advanced smart convergence (IWASC).



Software Tools and Algorithms for Biological Systems

Software Tools and Algorithms for Biological Systems Author Hamid Arabnia
ISBN-10 9781441970466
Release 2011-03-23
Pages 776
Download Link Click Here

“Software Tools and Algorithms for Biological Systems" is composed of a collection of papers received in response to an announcement that was widely distributed to academicians and practitioners in the broad area of computational biology and software tools. Also, selected authors of accepted papers of BIOCOMP’09 proceedings (International Conference on Bioinformatics and Computational Biology: July 13-16, 2009; Las Vegas, Nevada, USA) were invited to submit the extended versions of their papers for evaluation.



BIOINFORMATICS METHODS AND APPLICATIONS

BIOINFORMATICS  METHODS AND APPLICATIONS Author S. C. RASTOGI
ISBN-10 9788120347854
Release 2013-05-22
Pages 648
Download Link Click Here

Designed as a text for students and professionals pursuing careers in the fields of molecular biology, pharmacy and bioinformatics, the fourth edition continues to offer a fascinating and authoritative treatment of the entire spectrum of bioinformatics, covering a wide range of high-throughput technologies. In this edition, four new chapters are included and two chapters are updated. As a student-friendly text, it embodies several pedagogic features such as detailed examples, chapter-end problems, numerous tables, a large number of diagrams, flow charts, a comprehensive glossary and an up-to-date bibliography. This book should prove an invaluable asset to students and researchers in the fields of bioinformatics, biotechnology, computer-aided drug design, information technology, medical diagnostics, molecular biology and pharmaceutical industry. NEW TO THE FOURTH EDITION: • Includes four new chapters—Introduction to Biological Databases, Introduction to Phylogenetic, Methods of Phylogenic analysis and RNA Predict. • Updates chapters on Information Search and Data Retrieval and Alignment of Multiple Sequences. • Incorporates Problem Sets containing more than 250 problems and Multiple Choice Questions so that students can test their knowledge and understanding. Key Features • State-of-the-art technologies for gene identification, molecular modeling and monitoring of cellular processes • Data mining, analysis, classification, interpretation and efficient structure determination of genomes and proteomes • Importance of cell cycle for discovering new drug targets and their ligands • Computer-aided drug design and ADME-Tox property prediction Companion website www.phindia.com/rastogi provides useful resources for the teachers as well as for the students.



Bioinformatics Methods And Applications Genomics Proteomics And Drug Discovery 3Rd Ed

Bioinformatics Methods And Applications  Genomics Proteomics And Drug Discovery 3Rd Ed Author S. C. Rastogi
ISBN-10 9788120335950
Release 2008
Pages 524
Download Link Click Here

Bioinformatics Methods And Applications Genomics Proteomics And Drug Discovery 3Rd Ed has been writing in one form or another for most of life. You can find so many inspiration from Bioinformatics Methods And Applications Genomics Proteomics And Drug Discovery 3Rd Ed also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Bioinformatics Methods And Applications Genomics Proteomics And Drug Discovery 3Rd Ed book for free.



Machine Learning in Bioinformatics

Machine Learning in Bioinformatics Author Yanqing Zhang
ISBN-10 0470397411
Release 2009-02-23
Pages 400
Download Link Click Here

An introduction to machine learning methods and their applications to problems in bioinformatics Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. From an internationally recognized panel of prominent researchers in the field, Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics. Coverage includes: feature selection for genomic and proteomic data mining; comparing variable selection methods in gene selection and classification of microarray data; fuzzy gene mining; sequence-based prediction of residue-level properties in proteins; probabilistic methods for long-range features in biosequences; and much more. Machine Learning in Bioinformatics is an indispensable resource for computer scientists, engineers, biologists, mathematicians, researchers, clinicians, physicians, and medical informaticists. It is also a valuable reference text for computer science, engineering, and biology courses at the upper undergraduate and graduate levels.



Machine Learning Approaches to Bioinformatics

Machine Learning Approaches to Bioinformatics Author Zheng Rong Yang
ISBN-10 9789814287319
Release 2010
Pages 322
Download Link Click Here

This book covers a wide range of subjects in applying machine learning approaches for bioinformatics projects. The book succeeds on two key unique features. First, it introduces the most widely used machine learning approaches in bioinformatics and discusses, with evaluations from real case studies, how they are used in individual bioinformatics projects. Second, it introduces state-of-the-art bioinformatics research methods. The theoretical parts and the practical parts are well integrated for readers to follow the existing procedures in individual research. Unlike most of the bioinformatics books on the market, the content coverage is not limited to just one subject. A broad spectrum of relevant topics in bioinformatics including systematic data mining and computational systems biology researches are brought together in this book, thereby offering an efficient and convenient platform for teaching purposes. An essential reference for both final year undergraduates and graduate students in universities, as well as a comprehensive handbook for new researchers, this book will also serve as a practical guide for software development in relevant bioinformatics projects.



International Journal of Bioinformatics Research and Applicatons

International Journal of Bioinformatics Research and Applicatons Author
ISBN-10 17445485
Release 2006
Pages
Download Link Click Here

International Journal of Bioinformatics Research and Applicatons has been writing in one form or another for most of life. You can find so many inspiration from International Journal of Bioinformatics Research and Applicatons also informative, and entertaining. Click DOWNLOAD or Read Online button to get full International Journal of Bioinformatics Research and Applicatons book for free.



Bioinformatics

Bioinformatics Author Thomas Lengauer
ISBN-10 UCLA:L0083551440
Release 2002
Pages 700
Download Link Click Here

Bioinformatics - the use of computers to retrieve, process, analyze and simulate biological information - promises to revolutionize the process of drug discovery and development. This book provides a broad, application-oriented overview of this technology. Contributions by internationally renowned specialists in the field afford a detailed insight into single bioinformatics components and algorithmic methods. In addition, the state-of-the-art in bioinformatics is evaluated equally from a global view by introducing real application scenarios such as genome projects that require the use of a whole set of bioinformatics tools. The profound knowledge on bioinformatics presented here not only enables readers to go beyond a mere push-button approach to using bioinformatics software and interpreting the data generated appropriately. It is also essential to assess the potential and limitations of today's bioinformatics software and future challenges. Directed to all those involved in the use or development of new bioinformatics tools - scientists and managers from the fields of molecular biotechnology, pharmaceutics, and medicinal chemistry - this book will lead one step further on the way to rational drug design



Biomolecular interactions using machine learning

Biomolecular interactions using machine learning Author Joel Robert Bock
ISBN-10 UCSD:31822009432030
Release 2003
Pages 294
Download Link Click Here

Biomolecular interactions using machine learning has been writing in one form or another for most of life. You can find so many inspiration from Biomolecular interactions using machine learning also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Biomolecular interactions using machine learning book for free.



Introduction to Bioinformatics

Introduction to Bioinformatics Author Teresa K. Attwood
ISBN-10 STANFORD:36105110143414
Release 1999
Pages 218
Download Link Click Here

Bioinformatics, the application of computers in biological sciences and especially analysis of biological sequence data, is becoming an essential tool in molecular biology as genome projects generate vast quantities of data. This text provides an introduction to the subject for undergraduates (final year), focussing on two key areas, genojmics and protein sequence analysis. It provides an overview of primary, composite and secondary databases, and gives a brief introduction to the Internet and the World Wide Web.



Self Adaptive Systems for Machine Intelligence

Self Adaptive Systems for Machine Intelligence Author Haibo He
ISBN-10 1118025598
Release 2011-09-15
Pages 250
Download Link Click Here

This book will advance the understanding and application of self-adaptive intelligent systems; therefore it will potentially benefit the long-term goal of replicating certain levels of brain-like intelligence in complex and networked engineering systems. It will provide new approaches for adaptive systems within uncertain environments. This will provide an opportunity to evaluate the strengths and weaknesses of the current state-of-the-art of knowledge, give rise to new research directions, and educate future professionals in this domain. Self-adaptive intelligent systems have wide applications from military security systems to civilian daily life. In this book, different application problems, including pattern recognition, classification, image recovery, and sequence learning, will be presented to show the capability of the proposed systems in learning, memory, and prediction. Therefore, this book will also provide potential new solutions to many real-world applications.



Data Mining

Data Mining Author Sushmita Mitra
ISBN-10 0471460540
Release 2003-09-25
Pages 424
Download Link Click Here

First title to ever present soft computing approaches and their application in data mining, along with the traditional hard-computing approaches Addresses the principles of multimedia data compression techniques (for image, video, text) and their role in data mining Discusses principles and classical algorithms on string matching and their role in data mining



Machine Learning in Non stationary Environments

Machine Learning in Non stationary Environments Author Masashi Sugiyama
ISBN-10 9780262017091
Release 2012
Pages 261
Download Link Click Here

As the power of computing has grown over the past few decades, the field of machine learning has advanced rapidly in both theory and practice. Machine learning methods are usually based on the assumption that the data generation mechanism does not change over time. Yet real-world applications of machine learning, including image recognition, natural language processing, speech recognition, robot control, and bioinformatics, often violate this common assumption. Dealing with non-stationarity is one of modern machine learning's greatest challenges. This book focuses on a specific non-stationary environment known as covariate shift, in which the distributions of inputs (queries) change but the conditional distribution of outputs (answers) is unchanged, and presents machine learning theory, algorithms, and applications to overcome this variety of non-stationarity. After reviewing the state-of-the-art research in the field, the authors discuss topics that include learning under covariate shift, model selection, importance estimation, and active learning. They describe such real world applications of covariate shift adaption as brain-computer interface, speaker identification, and age prediction from facial images. With this book, they aim to encourage future research in machine learning, statistics, and engineering that strives to create truly autonomous learning machines able to learn under non-stationarity.



Bioinformatics Technologies

Bioinformatics Technologies Author Yi-Ping Phoebe Chen
ISBN-10 3540208739
Release 2005-01-18
Pages 396
Download Link Click Here

Introductio to bioinformatics. Overview of structural bioinformatics. Database warehousing in bioinformatics. Modeling for bioinformatics. Pattern matching for motifs. Visualization and fractal analysis of biological sequences. Microarray data analysis.