Monogenetic Rare Diseases in Biomedical Databases and Text Mining
Nesterova, A. P.; Klimov, E.; Sozin, S.; Sobolev, V.; Linsley, P.; Golovatenko-Abramov, P. K.
Show abstract
1AO_SCPLOWBSTRACTC_SCPLOWThe testing of pharmacological hypotheses becomes faster and more accurate, but at the same time more difficult than even two decades ago. It takes more time to collect and analyse disease mechanisms and experimental facts in various specialized resources. We discuss a new approach to aggregating individual pieces of information about a single disease using Elseviers automated text mining technology. Developed algorithm allows for the collection of published facts in a unified format starting only with the name of the disease. The special template, which combines research and clinical descriptions of diseases was developed. The approach was tested, and information was collected for 55 rare monogenic diseases. Clinical, molecular, and pharmacological characteristics of diseases with supporting references from the literature are available in the form of tables and files. Manually curated templates for 10 rare diseases, including top ranked Cystic Fibrosis and Huntingtons disease, were published to demonstrate the results of the described approach.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Monoallelic CRMP1 gene variants cause neurodevelopmental disorder 92%
- Systematic analysis of electronic health records identifies drugs reducing risk of COVID-19 hospitalization and severity 91%
- Discovery of runs-of-homozygosity diplotype clusters and their associations with diseases in UK Biobank 90%
Similar papers in this journal
- DDIEM: Drug Database for Inborn Errors of Metabolism 94%
- Genetic Insight into Birt-Hogg-Dubé syndrome in Indian patients reveals novel mutations in FLCN 93%
- The COVID-19 pandemic impact on continuity of care provision on rare brain diseases and on Ataxia, Dystonia and PKU. A scoping review protocol 90%
Similar papers in this journal
- Matching whole genomes to rare genetic disorders: Identification of potential causative variants using phenotype-weighted knowledge in the CAGI SickKids5 clinical genomes challenge 92%
- Cancer SIGVAR: A semi-automated interpretation tool for germline variants of hereditary cancer-related genes 92%
- REVEL is better at predicting pathogenicity of loss-of-function than gain-of-function variants 92%
Similar papers in this journal
- MicroRNA childhood Cancer Catalog (M3Cs): A Resource for Translational Bioinformatics Toward Health Informatics in Pediatric Cancer. 93%
- Creation and evaluation of full-text literature-derived, feature-weighted disease models of genetically determined developmental disorders 92%
- Integrated ACMG approved genes and ICD codes for the translational research and precision medicine 92%
Similar papers in this journal
- Targeting Lyn Kinase in Chorea-Acanthocytosis: A Translational Treatment Approach in an Ultra-Rare Disease 91%
- Comprehensive profiling of genomic and transcriptomic differences between risk groups of lung adenocarcinoma and lung squamous cell carcinoma 90%
- Precision Autism: Genomic Stratification of Disorders Making Up the Broad Spectrum May Demystify its "Epidemic Rates" 89%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.