ArticleDatabase : the journal of biological databases and curation2024
AHP DB: a reference database of proteins in the human aqueous humor.
Article in Database : the journal of biological databases and curation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- Deep Proteomic Analysis With Machine Learning Identifies Aqueous Humor Biomarkers of ADAMTSL4-associated Congenital Ectopia Lentis.Investigative ophthalmology & visual science · 2026Article
- Comparative analysis of human tear fluid and aqueous humor proteomes.The ocular surface · 2024Article
- Advances in aqueous humor proteomics for biomarker discovery and disease mechanisms exploration: a spotlight on primary open angle glaucoma.Frontiers in molecular neuroscience · 2024Review
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Authors and funding
14 authors at 1 institution in 1 country.
Funding
Abstract
The aqueous humor (AH) is a low-viscosity biofluid that continuously circulates from the posterior chamber to the anterior chamber of the eye. Recent advances in high-resolution mass-spectrometry workflows have facilitated the study of proteomic content in small-volume biofluids like AH, highlighting the potential clinical implications of the AH proteome. Nevertheless, in-depth investigations into the role of AH proteins in ocular diseases have encountered challenges due to limited accessibility to these workflows, difficulties in large-scale AH sample collection and the absence of a reference AH proteomic database. In response to these obstacles, and to promote further research on the involvement of AH proteins in ocular physiology and pathology, we have developed the web-based Aqueous Humor Proteomics Database (AHP DB). The current version of AHP DB contains proteomic data from 307 human AH samples, which were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The database offers comprehensive information on 1683 proteins identified in the AH samples. Furthermore, relevant clinical data are provided for each analyzed sample. Researchers also have the option to download these datasets individually for offline use, rendering it a valuable resource for the scientific community. Database URL: https://ahp.augusta.edu/.
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Registered trials
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