Disease Pathways: An Atlas of Human Disease Signaling Pathways

Disease Pathways: An Atlas of Human Disease Signaling Pathways is designed to fill a void of illustrated reviews about the cellular mechanisms of human diseases. It covers 42 of the most common non-oncologic diseases and illustrates the connections between the molecular causes of the disease and its symptoms. This resource provides readers with detailed information about the disease molecular pathways, while keeping the presentation simple.

Pathway models that aggregate the knowledge about protein–protein interactions have become indispensable tools in many areas of molecular biology, pharmacology, and medicine. In addition to disease pathways, the book includes a comprehensive overview of molecular signaling biology and application of pathway models in the analysis of big data for drug discovery and personalized medicine.

This is a must-have reference for general biologists, biochemists, students, medical workers, and everyone interested in the cellular and molecular mechanisms of human disease.

Over 145 full-color illustrations of the molecular and cellular cascades underlying the disease pathology.Disease pathways are based on computational models from Elsevier’s Disease Pathway Collection, published for the first time outside of Pathway Studio® commercial software.Each relationship on the pathway models is supported by references to scientific articles and can be examined at freely available online resources.

1. Part One 1. Introduction to the cell signaling biochemistry and proteomics 2. System biology and signaling pathways 3. Complexity of molecular mechanisms of human diseases

2. Part Two 1. Cardiovascular Diseases 2. Dermatological Diseases 3. Endocrine and Metabolic Diseases 4. Intestinal Diseases 5. Musculoskeletal System Diseases 6. Neurological Diseases 7. Obstetrics and Gynecology Diseases 8. Ophthalmology/Eye Diseases 9. Otolaryngological Diseases 10. Respirator and Pulmonology Diseases 11. Nephrology Diseases

3. Part Three 1. Methods of using intracellular maps for diagnosis of diseases in personalized medicine 2. Conclusion