Clinical Applications of Proteomics
Proteome Analysis, Page: 225-241
2004
- 14Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures14
- Readers14
- 14
Book Chapter Description
Despite tremendous advances in the understanding of the molecular genetics of diseases, such as cancer, the development of novel diagnostics and therapeutics has lagged behind. Promising areas in disease-related proteomics include the identification of distinctive disease proteomic profiles that correlate with clinical features; the development of novel biomarkers for diagnosis and early detection; the identification of novel targets for therapeutics on the one hand, given that the vast majority of drugs target proteins; and on the other hand, to utilize proteomics to accelerate drug development and evaluation of efficacy and toxicity. The proteome of a cell or a tissue is highly dynamic and changes much more readily in response to external factors than the genome or transcriptome. To capture all the proteomes that a cell or a tissue may manifest in health and disease, represents a substantial challenge for which the current available technologies have a limited reach. There is a need to employ and integrate multiple technologies, as it is unlikely that one technology will address all facets of proteomics. There is also a need to begin an organized international effort in proteomics that brings together investigators in the public as well as private sectors, given the enormity of the task of identifying and characterizing all the proteins in the human proteome. Beyond technological innovations that are required to increase throughput and sensitivity, there is a substantial need to develop informatics tools that allow the mining of proteomic data that will be generated at an unprecedented scale.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/B9780444510242500266; http://dx.doi.org/10.1016/b978-044451024-2/50026-6; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84904079991&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/B9780444510242500266; http://linkinghub.elsevier.com/retrieve/pii/B9780444510242500266; https://dx.doi.org/10.1016/b978-044451024-2/50026-6
Elsevier BV
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