Improving comparative analyses of Hi-C data via contrastive self-supervised learning.

Li H, He X, Kurowski L, Zhang R, Zhao D, Zeng J

DOI: 10.1093/bib/bbad193
Published: 2023 Jul 20
Container: Briefings in bioinformatics
Publisher: Not recorded
Open access: unknown

Credibility signals

limited evidence Score 43/100 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. Source: Crossref; license: CC0 metadata
cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.1093/bib/bbad193,
  title = {Improving comparative analyses of Hi-C data via contrastive self-supervised learning.},
  author = {Li H and He X and Kurowski L and Zhang R and Zhao D and Zeng J},
  year = {2023},
  journal = {Briefings in bioinformatics},
  doi = {10.1093/bib/bbad193},
  url = {https://doi.org/10.1093/bib/bbad193}
}

RIS

TY  - JOUR
TI  - Improving comparative analyses of Hi-C data via contrastive self-supervised learning.
AU  - Li H
AU  - He X
AU  - Kurowski L
AU  - Zhang R
AU  - Zhao D
AU  - Zeng J
PY  - 2023
JO  - Briefings in bioinformatics
DO  - 10.1093/bib/bbad193
UR  - https://doi.org/10.1093/bib/bbad193
ER  -

APA

H, L., X, H., L, K., R, Z., D, Z., & J, Z. (2023). Improving comparative analyses of Hi-C data via contrastive self-supervised learning.. Briefings in bioinformatics. https://doi.org/10.1093/bib/bbad193

Source records

pubmed · retrieved 2026-09-26T02:08:17.667Z