Theory and Technical Concept -- Computational Biology -- Statistical Theory in QTL Mapping -- Haplotype-Based Computational Genetic Analysis In Mice -- Haplotype Structure of the Mouse Genome -- SNP Discovery and Genotyping -- Selected Examples: Murine Models of Human Disease -- Genetic and Genomic Approaches to Complex Lung Diseases Using Mouse Models -- Murine Models of Osteoporosis -- Murine Models of Substance and Alcohol Dependence -- Murine Models of Alcoholism -- Selected Examples: The Genetic Basis for Human Disease -- HLA Polymorphism and Disease Susceptibility -- Asthma Genetics. Despite ever-increasing investments in genetic research, the translation of genetic discoveries into new therapies has been a slow process. In Computational Genetics and Genomics: Tools for Understanding Disease, well-recognized computational geneticists review and assess both currently available and developing tools for the rapid identification of the genetic basis for susceptibility to disease. The authors introduce a new computational approach that makes it possible to identify the genetic basis for differences in physiological or pathological responses among inbred mouse strains, thus facilitating more rapid genetic discovery. The focus is on the haplotype-based computational genetic analysis method and its application to inbred mouse strains. Reviewing murine models of asthma, lung disease, osteoporosis, and substance abuse, the contributors provide an overview of available mouse models, what has been learned from them, and which new models must be developed to advance our understanding of these diseases. They also describe how genetic analysis of human populations has yielded information on the genetic basis for susceptibility to asthma and other inflammatory diseases. Authoritative and path-breaking, Computational Genetics and Genomics: Tools for Understanding Disease surveys and assesses both currently available and powerful new computational genetic mapping methods that can be used to quickly analyze genetic models of biomedically important traits. This information provides a basis for uncovering the genetic factors regulating human disease-related traits.