ArticleGigaScience2020
Unifying package managers, workflow engines, and containers: Computational reproducibility with BioNix.
Article in GigaScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Packaging and containerization of computational methods.Nature protocols · 2024Pooled it
- Olaparib, durvalumab, and cyclophosphamide, and a prognostic blood signature in platinum-sensitive ovarian cancer: the randomized phase 2 SOLACE2 trial.Nature communications · 2025Trial
- hpci improves reproducibility of computational biology research by integrating Continuous Integration with High Performance Computing clusters.Bioinformatics (Oxford, England) · 2026Article
- Article
- Targeting homologous recombination deficiency in uterine leiomyosarcoma.Journal of experimental & clinical cancer research : CR · 2023Article
- The microtubule inhibitor eribulin demonstrates efficacy in platinum-resistant and refractory high-grade serous ovarian cancer patient-derived xenograft models.Therapeutic advances in medical oncology · 2023Article
- Toward practical transparent verifiable and long-term reproducible research using Guix.Scientific data · 2022Article
- Unifying package managers, workflow engines, and containers: Computational reproducibility with BioNix.GigaScience · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
motivationA challenge for computational biologists is to make our analyses reproducible-i.e. to rerun, combine, and share, with the assurance that equivalent runs will generate identical results. Current best practice aims at this using a combination of package managers, workflow engines, and containers.
resultsWe present BioNix, a lightweight library built on the Nix deployment system. BioNix manages software dependencies, computational environments, and workflow stages together using a single abstraction: pure functions. This lets users specify workflows in a clean, uniform way, with strong reproducibility guarantees. AVAILABILITY AND IMPLEMENTATION: BioNix is implemented in the Nix expression language and is released on GitHub under the 3-clause BSD license: https://github.com/PapenfussLab/bionix (biotools:BioNix) (BioNix, RRID:SCR_017662).
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.