Download or read book Molecular Pathway Analysis Using High-Throughput OMICS Molecular Data written by Anton Buzdin and published by Elsevier. This book was released on 2024-10-26 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field molecular pathway analysis evolves rapidly, and many progressive methods have recently been discovered. Molecular Pathway Analysis Using High-Throughput OMICS Data contains the largest collections of molecular pathways. For the first time, guidelines on how to do genomic, epigenetic, transcriptomic, proteomic, and metabolomic data analysis in real-world research practice are given. Molecular Pathway Analysis Using High-Throughput OMICS Molecular Data also focuses on the pathway analysis applications for solving tasks in biotechnology, pharmaceutics, and molecular diagnostics ​​It demonstrates how pathway analysis can be applied for the research and treatment of chronic and acute diseases, for next-generation molecular diagnostics, for drug design and preclinical testing; relevant real-world examples, molecular tests, and web resources will be reviewed in-depth.​ ​​The book shows a tendency of erasing the borders between chemistry, physics, informatics, mathematics, biology, and medicine by means of novel research approaches and instruments, providing a truly multidisciplinary approach. - Provides theoretical insights, links to available resources and their descriptions, and protocols related to multiple possibilities and options of the molecular pathway analysis - Elucidates unique instruments (i) for the quantitative pathway analysis using metabolomic data, and (ii) for algorithmic hypothesis-free reconstruction and functional annotation of the molecular pathways that have a strong potential to revolutionize the field - Includes intuitive practical guidelines on the analysis of genomic, epigenetic, transcriptomic, proteomic, and metabolomic data at the molecular pathway level for non-bioinformaticians - Provides state-of-the art in the field of Big molecular data analysis for research, medicine, biotechnology, pharmaceutics, and next-generation molecular diagnostics