Statistical Methods in Bioinformatics: An Introduction (Statistics for Biology and Health)

Statistical Methods in Bioinformatics: An Introduction (Statistics for Biology and Health)

Advances in computers and biotechnology have had an immense impact on the biomedical fields, with broad consequences for humanity. Correspondingly, new areas of probability and statistics are being developed specifically to meet the needs of this area. There is now a necessity for a text that introduces probability and statistics in the bioinformatics context. This book also describes some of the main statistical applications in the field, including BLAST, gene finding, and evolutionary inference, much of which has not yet been summarized in an introductory textbook format. This book grew out of a need to teach bioinformatics to graduate students at the University of Pennsylvania. At the same time however, it is organized to appeal to a wider audience. In particular it should appeal to any biologist or computer scientist who wants to know more about the statistical methods of the field, as well as to a trained statistician who wishes to become involved in bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, and will be accessible to students who have only had introductory calculus and linear algebra. Later chapters are immediately accessible to the trained statistician. Only a basic understanding of biological concepts is assumed, and all concepts are explained when used or can be understood from the context. Several chapters contain material independent of that in other chapters, so that the reader interested in certain areas can proceed directly to those areas. Warren Ewens is Professor of Biology at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics, and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceeding of the Royal Society B and SIAM Journal in Mathematical Biology. He was recently awarded the Gold Medal of the Australian Statistical Society and elected as Fellow of the Royal Society. His research interests are in evolutionary population genetics, linkage analysis for human diseases, and bioinformatics. Gregory Grant is a bioinformatics researcher at the University of Pennsylvania in the Computational Biology and Informatics Laboratory (CBIL), where he has been since 1998. In 1995 he received a Ph.D. in Mathematics from the University of Maryland and in 1999 a Masters in Computer Science from the University of Pennsylvania. His research interests are in bioinformatics in general and in particular in the statistical analysis of gene expression data and significance testing methods for IBD-mapping.

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Statistical Analysis of Network Data: Methods and Models (Springer Series in Statistics)

In the past decade, the study of networks has increased dramatically. Researchers from across the sciences—including biology and bioinformatics, computer science, economics, engineering, mathematics, physics, sociology, and statistics—are more and more involved with the collection and statistical analysis of network-indexed data. As a result, statistical methods and models are being developed in this area at a furious pace, with contributions coming from a wide spectrum of disciplines.

This book provides an up-to-date treatment of the foundations common to the statistical analysis of network data across the disciplines. The material is organized according to a statistical taxonomy, although the presentation entails a conscious balance of concepts versus mathematics. In addition, the examples—including extended cases studies—are drawn widely from the literature. This book should be of substantial interest both to statisticians and to anyone else working in the area of ‘network science.’

The coverage of topics in this book is broad, but unfolds in a systematic manner, moving from descriptive (or exploratory) methods, to sampling, to modeling and inference. Specific topics include network mapping, characterization of network structure, network sampling, and the modeling, inference, and prediction of networks, network processes, and network flows. This book is the first such resource to present material on all of these core topics in one place.

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Principles of Health Interoperability HL7 and SNOMED (Health Informatics)

Principles of Health Interoperability HL7 and SNOMED (Health Informatics)

Joined-up healthcare makes information available when and where it is needed to improve safety, efficiency and effectiveness. Politicians may take interoperability between healthcare computer systems for granted, but it is non-trivial. Healthcare integration projects are notoriously under-estimated and come in over-budget and over-time.

Joined-up healthcare depends on standards. The two leading standards are the SNOMED CT, which is a clinical terminology (semantics) and HL7 Version 3, which is a specialised healthcare interoperability language (syntax). Both are new, complex and fit for purpose.

Tim Benson believes there is an unmet need for a book on Healthcare Integration. Some health informatics textbooks include chapters on HL7 and/or SNOMED, but these are usually quite short and cannot provide even an adequate introduction. There is little of much value on the Internet, or in journals or conference proceedings.

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Biomedical Informatics: Computer Applications in Health Care and Biomedicine (Health Informatics)

Biomedical Informatics: Computer Applications in Health Care and Biomedicine (Health Informatics)

The practice of modern medicine requires sophisticated information technologies with which to manage patient information, plan diagnostic procedures, interpret laboratory results, and conduct research. This book, inspired by a Stanford University training program developed to introduce health professionals to computer applications in modern medical care, fills the need for a high quality text in computers and medicine, and meets the growing demand by practitioners, researchers, and students for a comprehensive introduction to key topics in the field. The work is designed for a broad audience interested in the intersection of computer science and medicine.

Completely revised and expanded, the Third Edition (previously titled “Medical Informatics”) includes several new chapters filled with brand new material.  This book will provide both a conceptual framework and a practical approach for the implementation and management of IT used to improve the delivery of health care. Designed for use by professors and students of medical informatics and for practicing professionals, this book will focus on the role of computers in the provision of medical services. Biomedial Informatics, Third Edition, provides the conceptual base needed to comprehend and utilize medical informatics through easy to understand examples that demonstrate how computers assist in the delivery of health care.  This text also includes pointers to additional literature, chapter summaries, and concise definition of recurring terms for self-study or classroom use.

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Postdoc Position in Bioinformatics – University of Tennessee Health Science Center – Memphis, TN

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