Ebook: Biomedical Data and Applications

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.

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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.

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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.

Content:
Front Matter....Pages -
Current Trends in Biomedical Data and Applications....Pages 1-9
Front Matter....Pages 11-11
Towards Bioinformatics Resourceomes....Pages 13-36
A Summary of Genomic Databases: Overview and Discussion....Pages 37-54
Protein Data Integration Problem....Pages 55-69
Multimedia Medical Databases....Pages 71-141
Bio-medical Ontologies Maintenance and Change Management....Pages 143-168
Extraction of Constraints from Biological Data....Pages 169-186
Classifying Patterns in Bioinformatics Databases by Using Alpha-Beta Associative Memories....Pages 187-210
Mining Clinical, Immunological, and Genetic Data of Solid Organ Transplantation....Pages 211-236
Substructure Analysis of Metabolic Pathways by Graph-Based Relational Learning....Pages 237-261
Front Matter....Pages 263-263
Design of an Online Physician-Mediated Personal Health Record System....Pages 265-279
Completing the Total Wellbeing Puzzle Using a Multi-agent System....Pages 281-293
The Minimal Model of Glucose Disappearance in Type I Diabetes....Pages 295-315
Genetic Algorithm inAb Initio Protein Structure Prediction Using Low Resolution Model: A Review....Pages 317-342
Back Matter....Pages -

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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.

Content:
Front Matter....Pages -
Current Trends in Biomedical Data and Applications....Pages 1-9
Front Matter....Pages 11-11
Towards Bioinformatics Resourceomes....Pages 13-36
A Summary of Genomic Databases: Overview and Discussion....Pages 37-54
Protein Data Integration Problem....Pages 55-69
Multimedia Medical Databases....Pages 71-141
Bio-medical Ontologies Maintenance and Change Management....Pages 143-168
Extraction of Constraints from Biological Data....Pages 169-186
Classifying Patterns in Bioinformatics Databases by Using Alpha-Beta Associative Memories....Pages 187-210
Mining Clinical, Immunological, and Genetic Data of Solid Organ Transplantation....Pages 211-236
Substructure Analysis of Metabolic Pathways by Graph-Based Relational Learning....Pages 237-261
Front Matter....Pages 263-263
Design of an Online Physician-Mediated Personal Health Record System....Pages 265-279
Completing the Total Wellbeing Puzzle Using a Multi-agent System....Pages 281-293
The Minimal Model of Glucose Disappearance in Type I Diabetes....Pages 295-315
Genetic Algorithm inAb Initio Protein Structure Prediction Using Low Resolution Model: A Review....Pages 317-342
Back Matter....Pages -
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