Clinical Metabolomics Applications in Genetic Diseases (eBook)

This model has been successfully applied in various conditions, including inborn errors of metabolism, primary immunodeficiency, and endocrine disorders. However, integrating metabolomics with other omics datasets and clinical phenotypes requires careful study design, analytical tools, and data analysis and interpretation. 

This groundbreaking new book provides essential guidance for researchers, students, and professionals looking to leverage metabolomics in their own work, including biochemical and clinical geneticists, pharmacogenomics and pharmacometabolomics experts, pharmaceutics and diagnostic researchers, medical scientists, clinical dietitians, metabolic engineers, clinical chemists, and personalized medicine specialists. 

With over a decade of experience in metabolomics research, Dr. Abdel Rahman's research has been focused on the next generation of metabolic screening. He has been actively involved in studying rare genetic diseases using advanced omics techniques, including metabolomics. His research group has successfully established metabolomics platforms for biomarker discovery and disease prediction models. 

Dr. Abdel Rahman's research has led to numerous publications in high-impact scientific journals, and his contributions to the field of clinical metabolomics have been widely recognized. He is a respected mentor, inspiring the next generation of researchers and scientists and advancing the field of personalized medicine. 

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This book helps readers discover the forefront of personalized medicine on clinical metabolomics and its applications in genetic diseases. This comprehensive guide offers a functional relationship map between cell components and genetic variations in various diseases, providing insights that can be applied to personalized medicine.  The book covers the latest developments in metabolomics for health, with practical guidance for clinical experts looking to advance their laboratory techniques and career. The metabolomics profile is a powerful tool that has revolutionized our understanding of the relationship between genetics, clinical readouts, and disease outcomes. By integrating metabolomics with genomics and clinical phenotypes, the authors have developed diagnostic and prediction models that have vastly improved patient outcomes and deepened the understanding of disease mechanisms. This model has been successfully applied in various conditions, including inborn errors of metabolism, primary immunodeficiency, and endocrine disorders. However, integrating metabolomics with other omics datasets and clinical phenotypes requires careful study design, analytical tools, and data analysis and interpretation. This groundbreaking new book provides essential guidance for researchers, students, and professionals looking to leverage metabolomics in their own work, including biochemical and clinical geneticists, pharmacogenomics and pharmacometabolomics experts, pharmaceutics and diagnostic researchers, medical scientists, clinical dietitians, metabolic engineers, clinical chemists, and personalized medicine specialists.