eRAM: encyclopedia of rare disease annotations for precision medicine
Open accessAbstract
Rare diseases affect over a hundred million people worldwide, most of these patients are not accurately diagnosed and effectively treated. The limited knowledge of rare diseases forms the biggest obstacle for improving their treatment. Detailed clinical phenotyping is considered as a keystone of deciphering genes and realizing the precision medicine for rare diseases. Here, we preset a standardized system for various types of rare diseases, called encyclopedia of Rare disease Annotations for Precision Medicine (eRAM). eRAM was built by text-mining nearly 10 million scientific publications and electronic medical records, and integrating various data in existing recognized databases (such as Unified Medical Language System (UMLS), Human Phenotype Ontology, Orphanet, OMIM, GWAS). eRAM systematically incorporates currently available data on clinical manifestations and molecular mechanisms of rare diseases and uncovers many novel associations among diseases. eRAM provides enriched annotations for 15 942 rare diseases, yielding 6147 human disease related phenotype terms, 31 661 mammalians phenotype terms, 10,202 symptoms from UMLS, 18 815 genes and 92 580 genotypes. eRAM can not only provide information about rare disease mechanism but also facilitate clinicians to make accurate diagnostic and therapeutic decisions towards rare diseases. eRAM can be freely accessed at http://www.unimd.org/eram/.
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The disease associations panel has been greatly expanded, incorporating DisGeNet and eRAM, as well as in size and placement.
“The disease associations panel has been greatly expanded, both in the amount of featured resources, now incorporating DisGeNet (31) and eRAM (32), as well as in size and placement.”
From TCRD and pharos 2021: mining the human proteome for disease biology (2021) · cites this paper as [32]
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- Authors
- Jia, J., An, Z., Ming, Y., Guo, Y., Li, W., Liang, Y., Guo, D., Li, X., Tai, J., Chen, G., Jin, Y., Liu, Z., Ni, X., & Shi, T.
- Affiliations
- East China Normal University (CN)
- Capital Medical University (CN)
- Corresponding author
- Ni, Xin
- Shi, Tieliu
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2017-11-02
- Volume
- 46
- Issue
- D1
- Pages
- D937-D943
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC5753383
- OpenAlex
- W2765673425
- Cited by
- 35
- References
- 58
- Citations by year
- 2024: 2 · 2023: 5 · 2022: 4 · 2021: 4 · 2020: 5 · 2019: 10 · 2018: 4 · 2017: 1
- FWCI
- 2.23
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (31671377)
- Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support
- Beijing Municipal Administration of Hospitals
- Beijing Children's Hospital, Capital Medical University
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- rare diseases, clinical phenotyping, disease annotation, precision medicine, text mining, electronic health records, gene-disease association
- MeSH terms
- Animals, Disease Models, Animal, Genotype, Humans, Terminology as Topic, Phenotype, Species Specificity, Databases, Factual, Rare Diseases, Mice, Precision Medicine, Data Curation
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