Introduction to Bioinformatics : A Theoretical and Practical Approach

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The genomic revolution that has spawned microarrays and high throughput technologies has produced vast amounts of complex biological data that require integration and multidimensional analysis. In Introduction to Bioinformatics: A Theoretical and Practical Approach, leading researchers and experts introduce the key biological, mathematical, statistical, and computer concepts and tools necessary for physical and life scientists to understand and analyze these data. For physical and computer scientists, the book provides a sound biological framework for understanding the questions a life scientist would ask in the context of currently available computational tools. Here, the basic cellular structure and the biological decoding of the genome, the long-range regulation of the genome, the in silico detection of the elements that impact long-range control, and the molecular genetic basis of disease as a consequence of replication are explained. Reviews of clinical human genetics, the various clinical databases, and pertinent issues in population genetics complete this tutorial.
For life scientists, a complete discussion of the UNIX operating system, which is commonly used to support advanced computational tools, offers biologists graphical-user-interface comfort in a command-line environment, plus an understanding of the installation and management of UNIX-based software tools.
It is in the applications sections that the book provides a common meeting ground for life and physical scientists. Here they will find examples of the management and analysis of DNA sequencing projects, the modeling of DNA as a statistical series of patterns, various methods of pattern discovery, protein visualization, and the use of multiple sequence alignment to infer both functional and structural biological relationships.
Cross-disciplinary and highly instructive, Introduction to Bioinformatics: A Theoretical and Practical Approach offers life, mathematical, computer, and statistical scientists an integrated foundation for using today's many new computational advances to elucidate the nuances of both genetic code and integrated biological systems.