Leveraging Biomedical and Healthcare Data - by Firas Kobeissy & Kevin Wang & Fadi A Zaraket & Ali Alawieh (Paperback)
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<p/><br></br><p><b> Book Synopsis </b></p></br></br><p><i>Leveraging Biomedical and Healthcare Data: Semantics, Analytics and Knowledge</i> 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. </p> <p>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.</p><p/><br></br><p><b> About the Author </b></p></br></br>Dr. Firas Kobeissy obtained his PhD from the University of Florida in the area of Neuroscience. His post doc at the Department of Psychiatry focused on neuroproteomics studies of brain injury as well as drug abuse neurotoxicity. His current research is in the area of biochemistry and neuroscience focusing on identifying biomarkers of traumatic brain injury neuroproteomics.<p>Dr. Kobeissy is the author of more than 75 articles, reviews and book chapters along with two patents. He is a member of the Center of Neuroproteomics and Biomarker Research (CNBR) at the McKnight Brain Institute at the University of Florida. He is the editor of three books (Humana Press and Taylor and Francis); the books deal with biomarker identification and proteomics research. Dr. Kobeissy has published extensively in the areas of systems biology pertaining to the areas of deciphering biomarker and pathways of pathogenesis in brain studies obtained from high throughput proteomics data.
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