Bioinformatics and Computational Biology (BCB) combine elements of computer science, information technology, mathematics, statistics, and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. In the era of molecular diagnostics, targeted drug design and Big Data for personalized medicine, computational methods for data analysis are essential for biochemistry, biology, biotechnology, pharmacology, biomedical science and computer science as well mathematics and statistics.
Navigating the maze of confusing and often contradictory jargon combined with a plethora of software tools is often confusing for students and researchers alike. This comprehensive and unique resource provides up-to-date theory and application content to address molecular data analysis requirements, with precise definition of terminology, and lucid explanations by experts.
This Encyclopedia comprises three sections, covering Theory, Topics and Applications, with a special focus on Integrative -omics and Systems Biology. The theoretical methodology underpinning BCB are described in the Theory section, with Topics covering traditional areas such as phylogeny, as well as more recent areas such as translational bioinformatics, cheminformatics and environmental informatics. Finally, Applications provides guidance for commonly asked how to questions.
Bioinformatics and Computational Biology are essential for making sense of the molecular data from many modern high-throughput studies of mice and men, as well as key model organisms and pathogens. This MRW spans basics to cutting-edge methodologies, authored by leaders in the field, providing an invaluable resource to students as well as scientists, in academia and research institutes as well as biotechnology, biomedical and pharmaceutical industries.
Interdisciplinary and comprehenisve: this work unifies the myriad of computer science, information technology, mathematics, statistics and biotechnology terms and concepts used by scientists working in bioinformatics and computational biology. Written and reviewed by leading experts in the field, it is a unique and authoritative resource.
Educational: this work focuses on the main theoretical and methodological concepts before expanding on specific topics and applications. As such, it is accessible to scientists with different backgrounds and provides an invaluable teaching resource.
Enhanced content: interactive images, multimedia tools and cross-linking to further resources and databases allow the interested reader to deepen his understanding of specific topics, and find relevant codes and open resources.