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Biomedical Data and Applications Softcover reprint of hardcover 1st ed. 2009 [Mīkstie vāki]

  • Formāts: Paperback / softback, 344 pages, height x width: 235x155 mm, weight: 545 g, X, 344 p., 1 Paperback / softback
  • Sērija : Studies in Computational Intelligence 224
  • Izdošanas datums: 28-Oct-2010
  • Izdevniecība: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3642101925
  • ISBN-13: 9783642101922
  • Mīkstie vāki
  • Cena: 136,16 €*
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  • Standarta cena: 160,19 €
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  • Formāts: Paperback / softback, 344 pages, height x width: 235x155 mm, weight: 545 g, X, 344 p., 1 Paperback / softback
  • Sērija : Studies in Computational Intelligence 224
  • Izdošanas datums: 28-Oct-2010
  • Izdevniecība: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3642101925
  • ISBN-13: 9783642101922
Compared with data from general application domains, modern biological data has many unique characteristics. Biological data are often characterized as having large volumes, complex structures, high dimensionality, evolving biological concepts, and insufficient data modelling practices. Over the past several years, bioinformatics has become an all-encompassing term for everything relating to both computer science and biology. The goal of this book is to cover data and applications identifying new issues and directions for future research in biomedical domain. The book will become a useful guide learning state-of-the-art development in biomedical data management, data-intensive bioinformatics systems, and other miscellaneous biological database applications. The book addresses various topics in bioinformatics with varying degrees of balance between biomedical data models and their real-world applications.
Current Trends in Biomedical Data and Applications.- Current Trends in
Biomedical Data and Applications.- I: Biomedical Data.- Towards
Bioinformatics Resourceomes.- A Summary of Genomic Databases: Overview and
Discussion.- Protein Data Integration Problem.- Multimedia Medical
Databases.- Bio-medical Ontologies Maintenance and Change Management.-
Extraction of Constraints from Biological Data.- Classifying Patterns in
Bioinformatics Databases by Using Alpha-Beta Associative Memories.- Mining
Clinical, Immunological, and Genetic Data of Solid Organ Transplantation.-
Substructure Analysis of Metabolic Pathways by Graph-Based Relational
Learning.- II: Biomedical Applications.- Design of an Online
Physician-Mediated Personal Health Record System.- Completing the Total
Wellbeing Puzzle Using a Multi-agent System.- The Minimal Model of Glucose
Disappearance in Type I Diabetes.- Genetic Algorithm inAb Initio Protein
Structure Prediction Using Low Resolution Model: A Review.