Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine and Healthcare
Grids are currently used in many sectors of life sciences, including basic sciences such as genomics, proteomics, and bioinformatics. ""The Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine, and Healthcare"" brings together state-of-the art methodologies and developments of grid technologies applied in different fields of life sciences. This ""Handbook of Research"" considers the use of grid technologies to support research and application of each information level where life science research takes place - a useful reference source for academicians, medical practitioners, and researchers involved in all areas of healthcare technologies. It includes: over 25 authoritative contributions by the world's leading experts in grid technologies for life sciences, biomedicine, and healthcare; comprehensive coverage of each specific topic, highlighting recent trends and describing the latest advances in the field; and, more than 1,000 references to existing literature and research on grid technologies for life sciences, biomedicine, and healthcare. A compendium of 230 key terms with detailed definitions, this book is organized by topic and indexed, making it a convenient method of reference for all IT/IS scholars and professionals. It features cross-referencing of key terms, figures, and information pertinent to grid technologies for life sciences, biomedicine, and healthcare.
- Hardback | 774 pages
- 223.52 x 292.1 x 76.2mm | 3,515.32g
- 15 Jun 2009
- IGI Global
- Medical Information Science Reference
- Hershey, United States
- Two Volumes
Table of contents
Biomedical application Data mining in proteomics Data provenance in scientific workflows Docking process in drug discovery Grid-based epidemic surveillance system Grid-based tool for comparative genomics Heart failure awareness management system Managing uncertain data Molecular structure determination Multiple repositories for digital content Polymorph prediction data for drug development Resource discovery in health grids
About Mario Cannataro
Mario Cannataro is an Associate Professor of computer engineering at University i?1/2Magna Gri?1/2ciai?1/2 of Catanzaro, Italy, since 2002. He received the Laurea Degree (cum laude) in computer engineering from the University of Calabria, Italy, in 1993. His current research interests include grid computing, bioinformatics, computational proteomics and genomics, grid-based problem solving environments, and adaptive hypermedia systems. He published a book and more than 100 papers on international journals and conference proceedings. Mario Cannataro is a co-founder of Exeura and is a member of ACM and IEEE Computer Society. Prof. Cannataro can be reached at email@example.com.