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Generation of Two-color Antigen Microarrays for the Simultaneous Detection of IgG and IgM Autoantibodies

Generation of Two-color Antigen Microarrays for the Simultaneous Detection of IgG and IgM Autoantibodies

Published on: September 15, 2016

AAgAtlas 1.0: a human autoantigen database.

Dan Wang¹, Liuhui Yang¹, Ping Zhang¹

¹State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Radiation Medicine, Beijing 102206, China.

Nucleic Acids Research

|December 8, 2016

Summary

This summary is machine-generated.

This study introduces the AAgAtlas database, a centralized resource for human autoantigens and associated diseases. It consolidates scattered information, aiding research into autoantibodies and autoimmune conditions.

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Area of Science:

Immunology
Bioinformatics
Computational Biology

Background:

Autoantibodies target self-antigens and are implicated in homeostasis, cancer detection, and autoimmune diseases.
Existing knowledge on autoantigens and their associated diseases is fragmented across scientific literature.
Elucidating autoantibody generation, evolution, and function is crucial for understanding health and disease.

Purpose of the Study:

To construct a comprehensive and accessible database of human autoantigens and their related diseases.
To centralize dispersed autoantigen information for easier research access.
To provide a valuable resource for basic and translational research on autoantigens.

Main Methods:

Utilized text-mining and manual curation of PubMed abstracts related to autoantigens and autoantibodies.
Employed a bio-entity recognizer based on the Protein Ontology for refining candidate autoantigens.
Developed the AAgAtlas database (version 1.0) to store and present identified human autoantigens and diseases.

Main Results:

Identified 1126 human genes as autoantigens.
Linked these autoantigens to 1071 human diseases.
Created the AAgAtlas database 1.0, containing 43,253 refined sentences and 3984 candidate autoantigens.
The database includes 45,830 autoantigen-related abstracts and 94,313 sentences from PubMed.

Conclusions:

The AAgAtlas database 1.0 offers a user-friendly platform for browsing, retrieving, and downloading human autoantigen data.
This database serves as a significant resource for tracking and understanding human autoantigens.
Facilitates investigation into the roles of autoantigens in both fundamental biological processes and clinical applications.