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Disease Markers
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Proteomics in Diagnostics

Authors: Timothy D. Veenstra; Sudhir Srivastava;

Proteomics in Diagnostics

Abstract

For many diseases, such as heart disease and cancer, early detection plays a pivotal role in the survival rate of the patient. When detected early, many such lethal diseases can be effectively treated with existing remedies. The difficulty remains, however, how to effectively detect such conditions at the earliest possible stage with a high enough positive predictive value so that they can be treated effectively without overwhelming the medical system with false positive diagnoses. What is required is the identification of more effective or additional biomarkers, as well as other types of technologies, that can aid in the diagnosis of early stage diseases. The challenge is how to identify more effective biomarkers or technologies that can provide an earlier indication of a disease with a higher positive predictive value than presently utilized methods. Proteomics, along with genomics and transcriptomics, has benefited greatly from the development of high-throughput methods to study thousands of proteins almost simultaneously. Based on the rate of interesting leads already being discovered using proteomics, it is likely that not only will biomarkers with better sensitivity and specificity be identified but individuals will be treated using customized therapies based on their specific protein profile. Since many of the proteomic technologies and data management tools are still in their infancy, the future of proteomics in disease diagnostics looks extremely promising.

Related Organizations
Keywords

Proteomics, Editorial, Humans, Biomarkers, Diagnostic Techniques and Procedures

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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