ArticleGigaScience2021
Quantitative monitoring of nucleotide sequence data from genetic resources in context of their citation in the scientific literature.
Article in GigaScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 6 citations in OpenAlex.
- How can biological databases support the new UN mechanism for benefit-sharing from digital sequence information?Scientific data · 2026Article
- VirJenDB: a FAIR (meta)data and bioinformatics platform for all viruses.Nucleic acids research · 2026Article
- A new indicator for the Kunming-Montreal Global Biodiversity Framework: Capturing non-monetary benefit data from access and benefit-sharing agreements.Bioscience · 2025Article
- Identifying genomic data use with the Data Citation Explorer.Scientific data · 2024Article
- Article
- Article
- Quantitative monitoring of nucleotide sequence data from genetic resources in context of their citation in the scientific literature.GigaScience · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLinking nucleotide sequence data (NSD) to scientific publication citations can enhance understanding of NSD provenance, scientific use, and reuse in the community. By connecting publications with NSD records, NSD geographical provenance information, and author geographical information, it becomes possible to assess the contribution of NSD to infer trends in scientific knowledge gain at the global level.
findingsWe extracted and linked records from the European Nucleotide Archive to citations in open-access publications aggregated at Europe PubMed Central. A total of 8,464,292 ENA accessions with geographical provenance information were associated with publications. We conducted a data quality review to uncover potential issues in publication citation information extraction and author affiliation tagging and developed and implemented best-practice recommendations for citation extraction. We constructed flat data tables and a data warehouse with an interactive web application to enable ad hoc exploration of NSD use and summary statistics.
conclusionsThe extraction and linking of NSD with associated publication citations enables transparency. The quality review contributes to enhanced text mining methods for identifier extraction and use. Furthermore, the global provision and use of NSD enable scientists worldwide to join literature and sequence databases in a multidimensional fashion. As a concrete use case, we visualized statistics of country clusters concerning NSD access in the context of discussions around digital sequence information under the United Nations Convention on Biological Diversity.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.