| URL: | http://bioinfo.wilmer.jhu.edu/AAgMarker/ |
| Full name: | Human Serum Autoantigen Biomarker Resource |
| Description: | Human Serum Autoantigen Biomarker Resource (AAgMarker 1.0) is a free database that provides information of non-invasive serum autoantigen biomarker candidates identified from high-throughput autoantibody profiling projects. For basic search, autoantigen biomarkers are those desregulated autoantigens which could distinguish patients with diseases from healthy controls (AUC≥0.6, P value≤0.05) and be easily detected with high signaling rate (≥10%) in either group; Sensitivity, specificity and discriminative ability are also introduced to quantitatively evaluate the performance of biomarkers. |
| Year founded: | 2018 |
| Last update: | |
| Version: | 1.0 |
| Accessibility: |
Accessible
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| Country/Region: | United States |
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| University/Institution: | Johns Hopkins University |
| Address: | The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA Tel: +1 443 287 3882; Fax: +1 410 502 5382 |
| City: | Baltimore |
| Province/State: | |
| Country/Region: | United States |
| Contact name (PI/Team): | Jiang Qian |
| Contact email (PI/Helpdesk): | jiang.qian@jhmi.edu |
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AAgMarker 1.0: a resource of serological autoantigen biomarkers for clinical diagnosis and prognosis of various human diseases. [PMID: 28977551]
Autoantibodies are produced to target an individual's own antigens (e.g. proteins). They can trigger autoimmune responses and inflammation, and thus, cause many types of diseases. Many high-throughput autoantibody profiling projects have been reported for unbiased identification of serological autoantigen-based biomarkers. However, a lack of centralized data portal for these published assays has been a major obstacle to further data mining and cross-evaluate the quality of these datasets generated from different diseases. Here, we introduce a user-friendly database, AAgMarker 1.0, which collects many published raw datasets obtained from serum profiling assays on the proteome microarrays, and provides a toolbox for mining these data. The current version of AAgMarker 1.0 contains 854 serum samples, involving 136 092 proteins. A total of 7803 (4470 non-redundant) candidate autoantigen biomarkers were identified and collected for 12 diseases, such as Alzheimer's disease, Bechet's disease and Parkinson's disease. Seven statistical parameters are introduced to quantitatively assess these biomarkers. Users can retrieve, analyse and compare the datasets through basic search, advanced search and browse. These biomarkers are also downloadable by disease terms. The AAgMarker 1.0 is now freely accessible at http://bioinfo.wilmer.jhu.edu/AAgMarker/. We believe this database will be a valuable resource for the community of both biomedical and clinical research. |