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Cluster and Classification Techniques for the Biosciences

Cluster and Classification Techniques for the Biosciences PDF Author: Alan H. Fielding
Publisher: Cambridge University Press
ISBN: 1139460064
Category : Medical
Languages : en
Pages : 4

Book Description
Advances in experimental methods have resulted in the generation of enormous volumes of data across the life sciences. Hence clustering and classification techniques that were once predominantly the domain of ecologists are now being used more widely. This 2006 book provides an overview of these important data analysis methods, from long-established statistical methods to more recent machine learning techniques. It aims to provide a framework that will enable the reader to recognise the assumptions and constraints that are implicit in all such techniques. Important generic issues are discussed first and then the major families of algorithms are described. Throughout the focus is on explanation and understanding and readers are directed to other resources that provide additional mathematical rigour when it is required. Examples taken from across the whole of biology, including bioinformatics, are provided throughout the book to illustrate the key concepts and each technique's potential.

Cluster and Classification Techniques for the Biosciences

Cluster and Classification Techniques for the Biosciences PDF Author: Alan H. Fielding
Publisher: Cambridge University Press
ISBN: 1139460064
Category : Medical
Languages : en
Pages : 4

Book Description
Advances in experimental methods have resulted in the generation of enormous volumes of data across the life sciences. Hence clustering and classification techniques that were once predominantly the domain of ecologists are now being used more widely. This 2006 book provides an overview of these important data analysis methods, from long-established statistical methods to more recent machine learning techniques. It aims to provide a framework that will enable the reader to recognise the assumptions and constraints that are implicit in all such techniques. Important generic issues are discussed first and then the major families of algorithms are described. Throughout the focus is on explanation and understanding and readers are directed to other resources that provide additional mathematical rigour when it is required. Examples taken from across the whole of biology, including bioinformatics, are provided throughout the book to illustrate the key concepts and each technique's potential.

Cluster and Classification Techniques for the Biosciences

Cluster and Classification Techniques for the Biosciences PDF Author:
Publisher:
ISBN: 9780511260629
Category : Biology
Languages : en
Pages : 246

Book Description


Clustering and Classification

Clustering and Classification PDF Author: Phipps Arabie
Publisher: World Scientific
ISBN: 9789810212872
Category : Mathematics
Languages : en
Pages : 508

Book Description
At a moderately advanced level, this book seeks to cover the areas of clustering and related methods of data analysis where major advances are being made. Topics include: hierarchical clustering, variable selection and weighting, additive trees and other network models, relevance of neural network models to clustering, the role of computational complexity in cluster analysis, latent class approaches to cluster analysis, theory and method with applications of a hierarchical classes model in psychology and psychopathology, combinatorial data analysis, clusterwise aggregation of relations, review of the Japanese-language results on clustering, review of the Russian-language results on clustering and multidimensional scaling, practical advances, and significance tests.

Research Methods for the Biosciences

Research Methods for the Biosciences PDF Author: Debbie Holmes
Publisher: Oxford University Press, USA
ISBN: 0199545766
Category : Education
Languages : en
Pages : 483

Book Description
'Research Methods in the Biosciences' demystifies the process of research and describes all the factors that enable effective investigation. These include planning your experiment; data collection, analysis, interpretation, and reporting; and legal, ethical, and health & safety considerations.

Multicriteria and Clustering

Multicriteria and Clustering PDF Author: Zacharoula Andreopoulou
Publisher: Springer
ISBN: 3319555650
Category : Business & Economics
Languages : en
Pages : 91

Book Description
This book provides an introduction to operational research methods and their application in the agrifood and environmental sectors. It explains the need for multicriteria decision analysis and teaches users how to use recent advances in multicriteria and clustering classification techniques in practice. Further, it presents some of the most common methodologies for statistical analysis and mathematical modeling, and discusses in detail ten examples that explain and show “hands-on” how operational research can be used in key decision-making processes at enterprises in the agricultural food and environmental industries. As such, the book offers a valuable resource especially well suited as a textbook for postgraduate courses.

Integrative Cluster Analysis in Bioinformatics

Integrative Cluster Analysis in Bioinformatics PDF Author: Basel Abu-Jamous
Publisher: John Wiley & Sons
ISBN: 1118906535
Category : Technology & Engineering
Languages : en
Pages : 451

Book Description
Clustering techniques are increasingly being put to use in the analysis of high-throughput biological datasets. Novel computational techniques to analyse 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. This book details the complete pathway of cluster analysis, from the basics of molecular biology to the generation of biological knowledge. The book also presents the latest clustering methods and clustering validation, thereby offering the reader a comprehensive review of clustering analysis in bioinformatics from the fundamentals through to state-of-the-art techniques and applications. Key Features: Offers a contemporary review of clustering methods and applications in the field of bioinformatics, with particular emphasis on gene expression analysis Provides an excellent introduction to molecular biology with computer scientists and information engineering researchers in mind, laying out the basic biological knowledge behind the application of clustering analysis techniques in bioinformatics Explains the structure and properties of many types of high-throughput datasets commonly found in biological studies Discusses how clustering methods and their possible successors would be used to enhance the pace of biological discoveries in the future Includes a companion website hosting a selected collection of codes and links to publicly available datasets

Mathematical Classification and Clustering

Mathematical Classification and Clustering PDF Author: Boris Mirkin
Publisher: Springer Science & Business Media
ISBN: 1461304571
Category : Mathematics
Languages : en
Pages : 439

Book Description
I am very happy to have this opportunity to present the work of Boris Mirkin, a distinguished Russian scholar in the areas of data analysis and decision making methodologies. The monograph is devoted entirely to clustering, a discipline dispersed through many theoretical and application areas, from mathematical statistics and combina torial optimization to biology, sociology and organizational structures. It compiles an immense amount of research done to date, including many original Russian de velopments never presented to the international community before (for instance, cluster-by-cluster versions of the K-Means method in Chapter 4 or uniform par titioning in Chapter 5). The author's approach, approximation clustering, allows him both to systematize a great part of the discipline and to develop many in novative methods in the framework of optimization problems. The optimization methods considered are proved to be meaningful in the contexts of data analysis and clustering. The material presented in this book is quite interesting and stimulating in paradigms, clustering and optimization. On the other hand, it has a substantial application appeal. The book will be useful both to specialists and students in the fields of data analysis and clustering as well as in biology, psychology, economics, marketing research, artificial intelligence, and other scientific disciplines. Panos Pardalos, Series Editor.

Classification, Clustering, and Data Analysis

Classification, Clustering, and Data Analysis PDF Author: Krzystof Jajuga
Publisher: Springer Science & Business Media
ISBN: 3642561810
Category : Computers
Languages : en
Pages : 468

Book Description
The book presents a long list of useful methods for classification, clustering and data analysis. By combining theoretical aspects with practical problems, it is designed for researchers as well as for applied statisticians and will support the fast transfer of new methodological advances to a wide range of applications.

Data Science Concepts and Techniques with Applications

Data Science Concepts and Techniques with Applications PDF Author: Usman Qamar
Publisher: Springer Nature
ISBN: 9811561338
Category : Computers
Languages : en
Pages : 207

Book Description
This book comprehensively covers the topic of data science. Data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three sections: The first section is an introduction to data science. Starting from the basic concepts, the book will highlight the types of data, its use, its importance and issues that are normally faced in data analytics. Followed by discussion on wide range of applications of data science and widely used techniques in data science. The second section is devoted to the tools and techniques of data science. It consists of data pre-processing, feature selection, classification and clustering concepts as well as an introduction to text mining and opining mining. And finally, the third section of the book focuses on two programming languages commonly used for data science projects i.e. Python and R programming language. Although this book primarily serves as a textbook, it will also appeal to industrial practitioners and researchers due to its focus on applications and references. The book is suitable for both undergraduate and postgraduate students as well as those carrying out research in data science. It can be used as a textbook for undergraduate students in computer science, engineering and mathematics. It can also be accessible to undergraduate students from other areas with the adequate background. The more advanced chapters can be used by postgraduate researchers intending to gather a deeper theoretical understanding.

Multivariate Methods of Representing Relations in R for Prioritization Purposes

Multivariate Methods of Representing Relations in R for Prioritization Purposes PDF Author: Wayne L. Myers
Publisher: Springer Science & Business Media
ISBN: 1461431220
Category : Mathematics
Languages : en
Pages : 304

Book Description
This monograph is multivariate, multi-perspective and multipurpose. We intend to be innovatively integrative through statistical synthesis. Innovation requires capacity to operate in ways that are not ordinary, which means that conventional computations and generic graphics will not meet the needs of an adaptive approach. Flexible formulation and special schematics are essential elements that must be manageable and economical.