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Leveraging Biomedical and Healthcare Data
Semantics, Analytics and Knowledge
An overview of the approaches used in semantic systems biology that included step-wise protocols for transforming heterogeneous data into useful knowledge
Firas Kobeissy (Edited by), Kevin Wang (Edited by), Fadi A. Zaraket (Edited by), Ali Alawieh (Edited by)
9780128095560
Paperback, published 29 November 2018
225 pages
23.4 x 19 x 1.5 cm, 0.48 kg
Approx.201 pages
Part I Understanding Molecular Architecture of Disease Using Big Data1. Curation of molecular data pertaining to human cancer and the Cancer Genome Atlas Initiative 2. Merging data from published literature to understand the sequence of disease pathology 3. Predicting potential therapeutic targets using drug-gene and gene-disease associations 4. Combination of graph theory and big data analysis in genomics and proteomics 5. Challenges in sharing, standardization and dissemination of molecular big data Part II Guiding Health Care Decisions Using Big Data6. Towards a unified version of EMR corpora and data systems7. Natural language processing and computational linguistics in EMR analysis8. Orienting infectious disease management using Big Data9. Modeling disease burden using big data10. Automated diagnosis and risk factor prediction based on natural language processing Part III Online Repositories and In-Silico Research in the Era of Big Data11. Curating a brain connectome using Big Data12. Genotype and phenotype associations using online clinical repositories – a step-wise approach13. In-silico pharmacology and cost- and time- effective approaches in drug discovery14. Guided and semi-automatic approaches for clinical meta-analyses15. Towards a unified language in molecular big data
Subject Areas: Cardiovascular medicine [MJD]
