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Home > Mathematics and Science Textbooks > Mathematics > Probability and statistics > Gene-Environment Interaction Analysis: Methods in Bioinformatics and Computational Biology
Gene-Environment Interaction Analysis: Methods in Bioinformatics and Computational Biology

Gene-Environment Interaction Analysis: Methods in Bioinformatics and Computational Biology


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About the Book

Gene-environment (GE) interaction analysis is a statistical method for clarifying GE interactions applicable to a phenotype or a disease that is the result of interactions between genes and the environment. This is the first book dealing with the theme of gene-environment (G ) interaction analysis. The book compiles and details cutting-edge research in bioinformatics and computational biology. Edited by Sumiko Anno.

Table of Contents:
Understanding Skin Color Variations as an Adaptation by Detecting Gene-Environment Interactions. Information Theoretic Methods for Gene-Environment Interaction Analysis. Approaches for Gene-Environment Interaction Analysis: Practice of Regional Epidemiological Study. Use of Bioinformatics in Revealing the Identity of Nature's Products with Minimum Genetic Variation: The Sibling Species. Integrated Bioinformatics, Biostatistics, and Molecular Epidemiologic Approaches to Studying How the Environment and Genes Work Together to Affect the Development of Complex Chronic Diseases.

About the Author :
Sumiko Anno is currently an associate professor at the Shibaura Institute of Technology. She investigates public health issues using genetic engineering, remote sensing, and geographic information systems technologies. Dr. Anno established gene-environment (GE) interaction analysis, which is used in a variety of scientific applications. In recent decades, there has been a great deal of scientific interest in her work on combining micro- and macro-information obtained from molecular, biological, and ecological studies. Her achievements have been rated highly, and she has received several awards from institutes in Japan and abroad.

Review :
"Human genomes are being intensively studied worldwide not only because of their importance in the fields of medicine and healthcare but also because a large number of personal genomes, which cover wide varieties of human races, have become available from international DNA databanks because of revolutionary advances in DNA sequencing technologies. By combining worldwide spatiotemporal studies on ultraviolet radiation with those on racial sequence diversity of a gene related with melanin production, researchers have clarified the geographically localized adaptive evolution among human races. This finding provides not only the fundamental knowledge of the adaptive evolution of human skin pigmentation but also valuable information for research in medicine and healthcare. The massive amount of sequence data can be utilized in any scientific field of research and is especially helpful for those involved in collaborative work on genomes and in developing new, promising, and interdisciplinary studies. This book introduces a pioneering study on this intendment." —Prof. Emeritus Toshimichi Ikemura, Nagahama Institute of Bio-Science and Technology, Japan "This book by Dr. Anno is a compilation of cutting-edge research in bioinformatics and computational biology and is authored by leading scientists and researchers in the field. It contains numerous worked examples, discussion problems, and a wide range of exercises for education. Since current systems for reporting electrochemical nanofabrication studies make it hard to assess whether the observed interactions are reproducible, the book also gives suggestions for improvements in this area." —Prof. Ming-An Lee, National Taiwan Ocean University, Taiwan


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Product Details
  • ISBN-13: 9789814669641
  • Publisher: Pan Stanford Publishing Pte Ltd
  • Publisher Imprint: Pan Stanford Publishing Pte Ltd
  • Language: English
  • ISBN-10: 9814669644
  • Publisher Date: 30 Mar 2016
  • Binding: Digital (delivered electronically)
  • Sub Title: Methods in Bioinformatics and Computational Biology


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