LEADER 00000cam 2200817Ii 4500 001 on1076269058 003 OCoLC 005 20200516093951.0 006 m o d 007 cr cnu|||unuuu 008 181126s2018 enk o 000 0 eng d 015 GBB8N1785|2bnb 016 7 019144402|2Uk 019 1076513020 020 9780128095614|q(electronic book) 020 012809561X|q(electronic book) 020 |z9780128095560 020 |z0128095563 035 (OCoLC)1076269058|z(OCoLC)1076513020 037 9780128095614|bIngram Content Group 040 N$T|beng|erda|epn|cN$T|dN$T|dEBLCP|dOPELS|dUKMGB|dYDX |dOCLCF|dMERER|dOCLCQ|dESU|dCQ$|dOCLCQ|dSTJ 049 STJJ 050 4 R858.A3 072 7 HEA|x012000|2bisacsh 072 7 HEA|x020000|2bisacsh 072 7 MED|x004000|2bisacsh 072 7 MED|x101000|2bisacsh 072 7 MED|x109000|2bisacsh 072 7 MED|x029000|2bisacsh 072 7 MED|x040000|2bisacsh 072 7 MED|x092000|2bisacsh 082 04 610.285|223 099 WORLD|aWIDE|aWEB|aE-BOOK|aSCIENCE 245 00 Leveraging Biomedical and Healthcare Data :|bSemantics, Analytics and Knowledge /|cedited by Firas Kobeissy [and 3 others]. 250 First edition. 264 1 London :|bElsevier Ltd. :|bAcademic Press,|c2018. 300 1 online resource 336 text|btxt|2rdacontent 337 computer|bc|2rdamedia 338 online resource|bcr|2rdacarrier 505 0 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 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 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 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 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 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. 588 0 Online resource; title from PDF title page (EBSCO, viewed November 28, 2018). 650 0 Medical care|xData processing. 650 0 Proteomics. 650 0 Protein-protein interactions. 650 0 Nervous system|xDegeneration. 650 7 HEALTH & FITNESS|xHolism.|2bisacsh 650 7 HEALTH & FITNESS|xReference.|2bisacsh 650 7 MEDICAL|xAlternative Medicine.|2bisacsh 650 7 MEDICAL|xAtlases.|2bisacsh 650 7 MEDICAL|xEssays.|2bisacsh 650 7 MEDICAL|xFamily & General Practice.|2bisacsh 650 7 MEDICAL|xHolistic Medicine.|2bisacsh 650 7 MEDICAL|xOsteopathy.|2bisacsh 650 7 Medical care|xData processing.|2fast|0(OCoLC)fst01013786 650 7 Nervous system|xDegeneration.|2fast|0(OCoLC)fst01036090 650 7 Protein-protein interactions.|2fast|0(OCoLC)fst01079705 650 7 Proteomics.|2fast|0(OCoLC)fst01079785 700 1 Kobeissy, Firas,|eeditor. 700 1 Wang, Kevin K. W.,|eeditor. 700 1 Zaraket, Fadi A.,|eeditor. 700 1 Alawieh, Ali,|eeditor. 776 08 |iPrint version:|tLeveraging Biomedical and Healthcare Data.|bFirst edition.|dLondon : Elsevier Ltd. : Academic Press, 2018|z9780128095560|z0128095563|w(OCoLC)986237293 994 C0|bSTJ
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