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Proteomics in Diagnostics
Author(s) -
Timothy D. Veenstra,
Sudhir Srivastava
Publication year - 2004
Publication title -
disease markers
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.912
H-Index - 66
eISSN - 1875-8630
pISSN - 0278-0240
DOI - 10.1155/2004/509356
Subject(s) - proteomics , disease , identification (biology) , genomics , medical diagnosis , predictive value , medicine , computational biology , bioinformatics , computer science , biology , pathology , genome , genetics , gene , botany
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.

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