OsteoporosAtlas

OsteoporosAtlas catalogs genes and microRNAs associated with osteoporosis to support genetic and functional analysis of the disease.


Key Features:

  • Centralized Database: Consolidates literature-derived information on osteoporosis-related genes and miRNAs into a single curated resource.
  • Data Extraction and Curation: Data were obtained by text-mining PubMed abstracts followed by manual curation and stored in a local MySQL database hosted on a Windows server.
  • Extensive Gene and miRNA Repository: Includes 617 human encoding genes, 131 non-coding miRNAs, and 128 annotated functional roles linked to osteoporosis.
  • Integrated Functional Analyses: Provides gene ontology and pathway analyses for annotated genes and miRNAs.

Scientific Applications:

  • Facilitating Genetic Research: Supports identification and exploration of genes, loci, and miRNA associations implicated in osteoporosis pathogenesis.
  • Supporting Drug Development: Enables analysis of genetic interactions and pathways relevant to therapeutic target identification.
  • Enhancing Diagnostic and Preventive Strategies: Informs development of genetic biomarkers and risk assessment approaches for osteoporosis.

Methodology:

Text-mining of PubMed abstracts combined with manual curation, data storage in a local MySQL database on a Windows server, and inclusion of gene ontology and pathway analyses.

Topics

Details

License:
Unlicense
Maturity:
Mature
Cost:
Free of charge
Tool Type:
web application
Operating Systems:
Linux, Windows, Mac
Programming Languages:
PHP, SQL
Added:
8/9/2019
Last Updated:
6/16/2020

Operations

Publications

Wang X, Diao L, Sun D, Wang D, Zhu J, He Y, Liu Y, Xu H, Zhang Y, Liu J, Wang Y, He F, Li Y, Li D. OsteoporosAtlas: a human osteoporosis-related gene database. PeerJ. 2019;7:e6778. doi:10.7717/peerj.6778. PMID:31086734. PMCID:PMC6487800.

PMID: 31086734
PMCID: PMC6487800
Funding: - National Natural Science Foundation of China: 31601064, 31871341 - State Key Laboratory of Proteomics: SKLP-K201702 - Innovation Project: 16CXZ027 - Beijing Nova Program: Z171100001117117 - Program of Precision Medicine: 2016YFC0901905

Documentation