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Leveraging Biomedical and Healthcare Data : Semantics, Analytics and Knowledge /

Leveraging Biomedical and Healthcare Data: Semantics, Analytics and Knowledge provides an overview of the approaches used in semantic systems biology, introduces novel areas of its application, and describes step-wise protocols for transforming heterogeneous data into useful knowledge that can influ...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Kobeissy, Firas (Editor ), Wang, Kevin (Editor ), Zaraket, Fadi A. (Editor ), Alawieh, Ali (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Elsevier Ltd. : Academic Press, 2018.
Edición:First edition.
Temas:
Acceso en línea:Texto completo

MARC

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245 0 0 |a Leveraging Biomedical and Healthcare Data :  |b Semantics, Analytics and Knowledge /  |c edited by Firas Kobeissy [and 3 others]. 
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505 0 |a 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 
505 8 |a 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 
505 8 |a 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 
505 8 |a 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 
505 8 |a 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 
520 |a Leveraging Biomedical and Healthcare Data: Semantics, Analytics and Knowledge provides an overview of the approaches used in semantic systems biology, introduces novel areas of its application, and describes step-wise protocols for transforming heterogeneous data into useful knowledge that can influence healthcare and biomedical research. Given the astronomical increase in the number of published reports, papers, and datasets over the last few decades, the ability to curate this data has become a new field of biomedical and healthcare research. This book discusses big data text-based mining to better understand the molecular architecture of diseases and to guide health care decision. It will be a valuable resource for bioinformaticians and members of several areas of the biomedical field who are interested in understanding more about how to process and apply great amounts of data to improve their research. 
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700 1 |a Kobeissy, Firas,  |e editor. 
700 1 |a Wang, Kevin,  |e editor. 
700 1 |a Zaraket, Fadi A.,  |e editor. 
700 1 |a Alawieh, Ali,  |e editor. 
776 0 8 |i Print version:  |t Leveraging Biomedical and Healthcare Data.  |b First edition.  |d London : Elsevier Ltd. : Academic Press, 2018  |z 9780128095560  |z 0128095563  |w (OCoLC)986237293 
856 4 0 |u https://sciencedirect.uam.elogim.com/science/book/9780128095560  |z Texto completo