ArticleDatabase : the journal of biological databases and curation2023
Assessing the use of supplementary materials to improve genomic variant discovery.
Article in Database : the journal of biological databases and curation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Enhancing the SIB Literature Services (SIBiLS) with annotations to support biocuration.Database : the journal of biological databases and curation · 2026Article
- Article
- Unlocking the potential of PubMed Central supplementary data files.Bioinformatics advances · 2025Article
- VarChat: the generative AI assistant for the interpretation of human genomic variations.Bioinformatics (Oxford, England) · 2024Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The curation of genomic variants requires collecting evidence not only in variant knowledge bases but also in the literature. However, some variants result in no match when searched in the scientific literature. Indeed, it has been reported that a significant subset of information related to genomic variants are not reported in the full text, but only in the supplementary materials associated with a publication. In the study, we present an evaluation of the use of supplementary data (SD) to improve the retrieval of relevant scientific publications for variant curation. Our experiments show that searching SD enables to significantly increase the volume of documents retrieved for a variant, thus reducing by ∼63% the number of variants for which no match is found in the scientific literature. SD thus represent a paramount source of information for curating variants of unknown significance and should receive more attention by global research infrastructures, which maintain literature search engines. Database URL https://www.expasy.org/resources/variomes.
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