Описание: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.
Описание: Peer reviewed articles from the Natural Language Processing and Cognitive Science (NLPCS) 2014 meeting in October 2014 workshop. The meeting fosters interactions among researchers and practitioners in NLP by taking a Cognitive Science perspective. Articles cover topics such as artificial intelligence, computational linguistics, psycholinguistics, cognitive psychology and language learning.
Автор: Tsai Jeffrey J P & Ng Ka-Lok Название: Computational Methods With Applications In Bioinformatics Analysis ISBN: 9813207973 ISBN-13(EAN): 9789813207974 Издательство: World Scientific Publishing Рейтинг: Цена: 13622.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This compendium contains 10 chapters written by world renowned researchers with expertise in semantic computing, genome sequence analysis, biomolecular interaction, time-series microarray analysis, and machine learning algorithms.
The salient feature of this book is that it highlights eight types of computational techniques to tackle different biomedical applications. These techniques include unsupervised learning algorithms, principal component analysis, fuzzy integral, graph-based ensemble clustering method, semantic analysis, interolog approach, molecular simulations and enzyme kinetics.
The unique volume will be a useful reference material and an inspirational read for advanced undergraduate and graduate students, computer scientists, computational biologists, bioinformatics and biomedical professionals.
Автор: Tomasz G. Smolinski; Mariofanna G. Milanova; Aboul Название: Computational Intelligence in Biomedicine and Bioinformatics ISBN: 3642089690 ISBN-13(EAN): 9783642089695 Издательство: Springer Рейтинг: Цена: 30606.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The purpose of this book is to provide an overview of state-of-the-art methodologies currently utilized for biomedicine and/or bioinformatics-oriented applications. Researchers working in these fields will learn new methods to help tackle their problems.
Автор: James K. Peterson Название: BioInformation Processing ISBN: 9812878696 ISBN-13(EAN): 9789812878694 Издательство: Springer Рейтинг: Цена: 25155.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book shows how mathematics, computer science and science can be usefully and seamlessly intertwined. It introduces specialized data for emotional content, which allows a brain model to be built using MatLab tools, and also highlights a simple model of cognitive dysfunction.
Описание: This book proposes applications of tensor decomposition to unsupervised feature extraction and feature selection. The author posits that although supervised methods including deep learning have become popular, unsupervised methods have their own advantages. He argues that this is the case because unsupervised methods are easy to learn since tensor decomposition is a conventional linear methodology. This book starts from very basic linear algebra and reaches the cutting edge methodologies applied to difficult situations when there are many features (variables) while only small number of samples are available. The author includes advanced descriptions about tensor decomposition including Tucker decomposition using high order singular value decomposition as well as higher order orthogonal iteration, and train tenor decomposition. The author concludes by showing unsupervised methods and their application to a wide range of topics.
Allows readers to analyze data sets with small samples and many features;Provides a fast algorithm, based upon linear algebra, to analyze big data;Includes several applications to multi-view data analyses, with a focus on bioinformatics.
Описание: This book discusses topics related to bioinformatics, statistics, and machine learning, presenting the latest research in various areas of bioinformatics.
Название: Bayesian Modeling in Bioinformatics ISBN: 0367383659 ISBN-13(EAN): 9780367383657 Издательство: Taylor&Francis Рейтинг: Цена: 9798.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Bayesian Modeling in Bioinformatics discusses the development and application of Bayesian statistical methods for the analysis of high-throughput bioinformatics data arising from problems in molecular and structural biology and disease-related medical research, such as cancer. It presents a broad overview of statistical inference, clustering, and classification problems in two main high-throughput platforms: microarray gene expression and phylogenic analysis.
The book explores Bayesian techniques and models for detecting differentially expressed genes, classifying differential gene expression, and identifying biomarkers. It develops novel Bayesian nonparametric approaches for bioinformatics problems, measurement error and survival models for cDNA microarrays, a Bayesian hidden Markov modeling approach for CGH array data, Bayesian approaches for phylogenic analysis, sparsity priors for protein-protein interaction predictions, and Bayesian networks for gene expression data. The text also describes applications of mode-oriented stochastic search algorithms, in vitro to in vivo factor profiling, proportional hazards regression using Bayesian kernel machines, and QTL mapping.
Focusing on design, statistical inference, and data analysis from a Bayesian perspective, this volume explores statistical challenges in bioinformatics data analysis and modeling and offers solutions to these problems. It encourages readers to draw on the evolving technologies and promote statistical development in this area of bioinformatics.
Автор: Ismail, Hamid D. (nc A&t State University, North Carolina, Usa) Название: Bioinformatics ISBN: 1032123699 ISBN-13(EAN): 9781032123691 Издательство: Taylor&Francis Рейтинг: Цена: 13473.00 р. Наличие на складе: Поставка под заказ.
Описание: Bioinformatics: A Practical Guide to NCBI Databases and Sequence Alignments provides the basics of bioinformatics and in-depth coverage of NCBI databases, sequence alignment, and NCBI Sequence Local Alignment Search Tool (BLAST).
Автор: Singh Vijai, Kumar Ajay Название: Advances in Bioinformatics ISBN: 9813361905 ISBN-13(EAN): 9789813361904 Издательство: Springer Цена: 25155.00 р. Наличие на складе: Поставка под заказ.
Описание: 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.
Описание: In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance in boosting the research efforts in the field and contributing to the education of a new generation of Bioinformatics scientists.
Автор: Bao Le Nguyen, Deepak Gupta, Siddhartha Bhattacharyya, Utku Kose Название: Artificial Intelligence for Data-Driven Medical Diagnosis ISBN: 3110667819 ISBN-13(EAN): 9783110667813 Издательство: Walter de Gruyter Рейтинг: Цена: 21190.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.
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