The past three decades have witnessed an explosion of what is now referred to as high-dimensional `omics' data. Bioinformatics Methods: From Omics to Next Generation Sequencing describes the statistical methods and analytic frameworks that are best equipped to interpret these complex data and how they apply to health-related research. Covering the technologies that generate data, subtleties of various data types, and statistical underpinnings of methods, this book identifies a suite of potential analytic tools, and highlights commonalities among statistical methods that have been developed. An ideal reference for biostatisticians and data analysts that work in collaboration with scientists and clinical investigators looking to ensure rigorous application of available methodologies. Key Features: Survey of a variety of omics data types and their unique features Summary of statistical underpinnings for widely used omics data analysis methods Description of software resources for performing omics data analyses
The past three decades have witnessed an explosion of what is now referred to as high-dimensional `omics' data. Bioinformatics Methods: From Omics to Next Generation Sequencing describes the statistical methods and analytic frameworks that are best equipped to interpret these complex data and how they apply to health-related research. Covering the technologies that generate data, subtleties of various data types, and statistical underpinnings of methods, this book identifies a suite of potential analytic tools, and highlights commonalities among statistical methods that have been developed. An ideal reference for biostatisticians and data analysts that work in collaboration with scientists and clinical investigators looking to ensure rigorous application of available methodologies. Key Features: Survey of a variety of omics data types and their unique features Summary of statistical underpinnings for widely used omics data analysis methods Description of software resources for performing omics data analyses
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.
This book presents the fundamentals of iron and steel making, including the physical chemistry, thermodynamics and key concepts, while also discussing associated problems and solutions. It guides the reader through the production process from start to finish, covers the raw materials, and addresses the types of processes and reactions involved in both conventional and alternative methods. Though primarily intended as a textbook for students of metallurgical engineering, the book will also prove a useful reference for professionals and researchers working in this area.
This book has been prepared primarily for use by Students studying Ferrous Metallurgy (i.e., Iron and Steelmaking) at UG and PG level of Metallurgical and Materials Engineering, Research workers engaged in obtaining fundamental information in this field, and for Process Metallurgists to understand the processes in general and Sponge Iron Producers in particular. ; It also helps the practicing engineers who wish to apply the theoretical knowledge to the process they are operating. ;The book may very well be introduced as a Textbook for Elective subject in Third/Fourth year of UG programme in Metallurgical & Materials Engineering. ;The book consists of nine chapters in two parts; five chapters in Part-I: Direct Reduction Processes and four chapters in Part-II: Smelting Reduction Processes. In Part-I, the Chapter 1 deals with a brief introduction of the sponge iron and classification of the direct reduction processes with their advantages and limitations. Chapter 2 deals with the raw materials involved in direct reduced ironmaking and their characteristics. In Chapter 3, the physico-chemical principles and thermodynamics of reduction are highlighted. The details of different direct reduction (DR) processes are discussed in Chapter 4. The characteristics and uses of DRI as well as its effect on Electric Arc Furnace performance is discussed in Chapter 5.
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