Leveraging Biomedical and Healthcare Data : Semantics, Analytics and Knowledge /: Semantics, Analytics and Knowledge. (2018)
- Record Type:
- Book
- Title:
- Leveraging Biomedical and Healthcare Data : Semantics, Analytics and Knowledge /: Semantics, Analytics and Knowledge. (2018)
- Main Title:
- Leveraging Biomedical and Healthcare Data : Semantics, Analytics and Knowledge
- Further Information:
- Note: Edited by Firas Kobeissy [and 3 others].
- Editors:
- Kobeissy, Firas
Wang, Kevin
Zaraket, Fadi A
Alawieh, Ali - Contents:
- Front Cover; Leveraging Biomedical and Healthcare Data: Semantics, Analytics and Knowledge; Copyright; Dedication; Contents; Contributors; Foreword I; Foreword II; Preface; Acknowledgments; Chapter 1: Comprehensive Workflow for Integrative Transcriptomics Meta-Analysis; 1. Introduction; 2. Data Preparation; 2.1. Data Download; 2.2. Quality Control; 2.2.1. Single-Array Metrics; 2.2.2. Multiarray Metrics; 2.3. Data Preprocessing; 2.3.1. Background Correction; 2.3.2. Normalization; 2.3.3. Summarization; 2.3.4. Comparison Between Different Procedures 2.4. Batch Effect: A Special Concern During Data Integration3. Crossplatform Integration; 4. Conclusion; References; Chapter 2: Proteomics and Protein Interaction in Molecular Cell Signaling Pathways; 1. Introduction; 2. Experimental Techniques; 3. Computational Methods; 3.1. Sequences Databases and Analysis; 3.2. Protein Feature Prediction Using Protein Sequence; 3.3. Structure Databases and Analysis; 3.4. Protein Families; 3.5. Interactions, Pathways, and System Biology; 3.6. Posttranslational Modifications; 4. Conclusion; References Chapter 3: Understanding Specialized Ribosomal Protein Functions and Associated Ribosomopathies by Navigating Across Sequ ...1. Introduction; 2. RPs and Diseases; 2.1. Ribosomopathies; 2.2. Cancer; 3. Specialized Functions of RPs; 3.1. RP-Mediated Translational Control of Distinct mRNAs, Through Interaction With IRES cis-Regulatory Elements; 3.2. Posttranslational Modifications (PTMs) of RPs; 3.3. RPFront Cover; Leveraging Biomedical and Healthcare Data: Semantics, Analytics and Knowledge; Copyright; Dedication; Contents; Contributors; Foreword I; Foreword II; Preface; Acknowledgments; Chapter 1: Comprehensive Workflow for Integrative Transcriptomics Meta-Analysis; 1. Introduction; 2. Data Preparation; 2.1. Data Download; 2.2. Quality Control; 2.2.1. Single-Array Metrics; 2.2.2. Multiarray Metrics; 2.3. Data Preprocessing; 2.3.1. Background Correction; 2.3.2. Normalization; 2.3.3. Summarization; 2.3.4. Comparison Between Different Procedures 2.4. Batch Effect: A Special Concern During Data Integration3. Crossplatform Integration; 4. Conclusion; References; Chapter 2: Proteomics and Protein Interaction in Molecular Cell Signaling Pathways; 1. Introduction; 2. Experimental Techniques; 3. Computational Methods; 3.1. Sequences Databases and Analysis; 3.2. Protein Feature Prediction Using Protein Sequence; 3.3. Structure Databases and Analysis; 3.4. Protein Families; 3.5. Interactions, Pathways, and System Biology; 3.6. Posttranslational Modifications; 4. Conclusion; References Chapter 3: Understanding Specialized Ribosomal Protein Functions and Associated Ribosomopathies by Navigating Across Sequ ...1. Introduction; 2. RPs and Diseases; 2.1. Ribosomopathies; 2.2. Cancer; 3. Specialized Functions of RPs; 3.1. RP-Mediated Translational Control of Distinct mRNAs, Through Interaction With IRES cis-Regulatory Elements; 3.2. Posttranslational Modifications (PTMs) of RPs; 3.3. RP Gene Expression; 3.4. RP Paralogs; 3.5. Differential Subcellular Stoichiometry of RPs; 4. Exploring RP Roles in Health and Disease by Navigating Bioinformatics Resources; 4.1. RP Nomenclature 4.2. Comparison of Human and Mouse RPs Reveals a Range of Conservation Levels5. Conclusions and Future Directions; References; Chapter 4: Big Data, Artificial Intelligence, and Machine Learning in Neurotrauma; 1. Introduction; 2. Big Data: Characteristics, Definitions, and Examples; 3. Traumatic Brain Injury (TBI); 4. Big Data in TBI; 5. Machine Learning; 6. Artificial Intelligence; 7. Text Mining; 8. Examples of Using BD Approaches in TBI Research; 9. Imaging; 10. Biochemical Markers; 11. Legacy Data; 12. Future of Big Data in TBI; References Chapter 5: Artificial Intelligence Integration for Neurodegenerative Disorders1. Introduction; 2. Wearables and ML-Based Therapeutics; 3. Neurodegenerative Therapeutics Through AI; 3.1. Parkinson's Disease; 3.2. Seizures and Epilepsy; 3.3. Alzheimer's Disease; 3.4. Amyotrophic Lateral Sclerosis; 3.5. Stroke and Spinal Cord Injury; 4. AI-Based Clinical Decision-Making; 5. Limitations and Future Perspectives; References; Chapter 6: Robust Detection of Epilepsy Using Weighted-Permutation Entropy: Methods and Analysis; 1. Introduction; 1.1. Background; 1.2. Approach; 2. Computational Details … (more)
- Publisher Details:
- London : Elsevier Ltd Academic Press
- Publication Date:
- 2018
- Extent:
- 1 online resource
- Subjects:
- 610.285
Medical care -- Data processing
Proteomics
Protein-protein interactions
Nervous system -- Degeneration
HEALTH & FITNESS / Holism
HEALTH & FITNESS / Reference
MEDICAL / Alternative Medicine
MEDICAL / Atlases
MEDICAL / Essays
MEDICAL / Family & General Practice
MEDICAL / Holistic Medicine
MEDICAL / Osteopathy
Electronic books - Languages:
- English
- ISBNs:
- 9780128095614
- Related ISBNs:
- 012809561X
9780128095560 - Notes:
- Note: Online resource; title from PDF title page (EBSCO, viewed November 28, 2018).
- Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.360860
- Ingest File:
- 01_324.xml