Topological benchmarking of algorithms to infer gene regulatory networks from single-cell RNA-seq data.
- DOI
- 10.1093/bioinformatics/btae267
- Published
- 2024 May 2
- Container
- Bioinformatics (Oxford, England)
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- supportingOpen access status: Normalized open-access status: open.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.1093/bioinformatics/btae267,
title = {Topological benchmarking of algorithms to infer gene regulatory networks from single-cell RNA-seq data.},
author = {Stock M and Popp N and Fiorentino J and Scialdone A},
year = {2024},
journal = {Bioinformatics (Oxford, England)},
doi = {10.1093/bioinformatics/btae267},
url = {https://doi.org/10.1093/bioinformatics/btae267}
}RIS
TY - JOUR TI - Topological benchmarking of algorithms to infer gene regulatory networks from single-cell RNA-seq data. AU - Stock M AU - Popp N AU - Fiorentino J AU - Scialdone A PY - 2024 JO - Bioinformatics (Oxford, England) DO - 10.1093/bioinformatics/btae267 UR - https://doi.org/10.1093/bioinformatics/btae267 ER -
APA
M, S., N, P., J, F., & A, S. (2024). Topological benchmarking of algorithms to infer gene regulatory networks from single-cell RNA-seq data.. Bioinformatics (Oxford, England). https://doi.org/10.1093/bioinformatics/btae267
Source records
- pubmed · retrieved 2026-09-25T02:35:17.616Z
- europe-pmc · retrieved 2026-09-25T02:35:17.654Z