ArticleGigaScience2024
Hiding in plain sight: a research parasite's perspective on new lessons in old data.
Article in GigaScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- A standards perspective on genomic data reusability and reproducibility.Frontiers in bioinformatics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-throughput techniques that measure thousands of analytes at once have become ubiquitous features of biological research. The increasing expectation that the raw data generated by these techniques be deposited to public repositories creates rich opportunities for secondary analysis of these datasets. Such opportunities can take multiple forms. As the recipient of the 2023 Junior Research Parasite Award, I was asked to comment on the role of so-called research parasites within the ecosystem of secondary data analysis. Drawing on my own experiences, I discuss mechanisms by which reanalysis of published datasets can catalyze biological discoveries, produce resources that would be impossible to generate within a single laboratory, and drive the refinement of computational methods.
Indexed as
Identifiers
What Socratic 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 Socratic graph.