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Applied Computational Genomics
"Applied Computational Genomics" focuses on an in-depth review of statistical development and application in the area of human genomics including candidate gene mapping, linkage analysis, population-based, genome-wide association, exon sequencing and whole genome sequencing analysis. The authors are extremely experienced in the area of statistical genomics and will give a detailed introduction of the evolution in the field and critical evaluations of the advantages and disadvantages of the statistical models proposed. They will also share their views on a future shift toward translational biology. The book will be of value to human geneticists, medical doctors, health educators, policy makers, and graduate students majoring in biology, biostatistics, and bioinformatics. Dr. Yin Yao Shugart is investigator in the Intramural Research Program at the National Institute of Mental Health, Bethesda, Maryland USA.
Familial Cancer and Prevention
A New Strategy Toward Cancer Control. Still in its infancy, the familial/hereditary approach to cancer control is proving to be one of the most potent strategies in the war on cancer. Over the past few years the human genome project has generated an abundance of valuable information on the genetic origins of a range of cancers. Tests now exist for several hereditary, tumor-promoting genetic mutations-including those found in BRCA genes associated with breast cancer as well as mutations of HNPCC genes which have been linked to colon cancers-and many more are anticipated in the near future. Armed with the information yielded by these tests, physicians have already saved countless lives through...
Developmental Neuroscience
A concise introductory textbook on the development of the nervous system This textbook offers a concise introduction to the exciting field of developmental neuroscience, a discipline concerned with the mechanisms by which complex nervous systems emerge during embryonic growth. Bridging the divide between basic and clinical research, it captures the extraordinary progress that has been achieved in the field. It provides an opportunity for students to apply and extend what they have learned in their introductory biology courses while also directing them to the primary literature. This accessible textbook is unique in that it takes an in-depth look at a small number of key model systems and sig...
Single Cell Sequencing and Systems Immunology
The volume focuses on the genomics, proteomics, metabolomics, and bioinformatics of a single cell, especially lymphocytes and on understanding the molecular mechanisms of systems immunology. Based on the author’s personal experience, it provides revealing insights into the potential applications, significance, workflow, comparison, future perspectives and challenges of single-cell sequencing for identifying and developing disease-specific biomarkers in order to understand the biological function, activation and dysfunction of single cells and lymphocytes and to explore their functional roles and responses to therapies. It also provides detailed information on individual subgroups of lympho...
Linkage Disequilibrium and Association Mapping
As researchers continue to make enormous progress in mapping disease genes, exciting, novel, and complex analyses have emerged. In this book, scientists from around the world, who are leaders in this field, contribute their vast experience and expertise to produce a comprehensive and fascinating text for researchers and clinicians alike. They provide cutting-edge analysis of the most up-to-date and preeminent information available.
Novel Approaches to the Analysis of Family Data in Genetic Epidemiology
Genome-wide association studies (GWAS) for complex disorders with large case-control populations have been performed on hundreds of traits in more than 1200 published studies (http://www.genome.gov/gwastudies/) but the variants detected by GWAS account for little of the heritability of these traits, leading to an increasing interest in using family based designs. While GWAS studies are designed to find common variants with low to moderate attributable risks, family based studies are expected to find rare variants with high attributable risk. Because family-based designs can better control both genetic and environmental background, this study design is robust to heterogeneity and population s...
Cause Effect Pairs in Machine Learning
This book presents ground-breaking advances in the domain of causal structure learning. The problem of distinguishing cause from effect (“Does altitude cause a change in atmospheric pressure, or vice versa?”) is here cast as a binary classification problem, to be tackled by machine learning algorithms. Based on the results of the ChaLearn Cause-Effect Pairs Challenge, this book reveals that the joint distribution of two variables can be scrutinized by machine learning algorithms to reveal the possible existence of a “causal mechanism”, in the sense that the values of one variable may have been generated from the values of the other. This book provides both tutorial material on the st...
Biocomputing 2006 - Proceedings Of The Pacific Symposium
The Pacific Symposium on Biocomputing (PSB) 2006 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2006 will be held January 3-7, 2006 at the Grand Wailea, Maui. Tutorials will be offered prior to the start of the conference.PSB 2006 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the pr...
