Retracted: DeepCRISTL: deep transfer learning to predict CRISPR/Cas9 functional and endogenous on-target editing efficiency

Shai Elkayam, Yaron Orenstein

DOI: 10.1093/bioinformatics/btac218
Published: 2022-06-24
Container: Bioinformatics
Publisher: Oxford University Press (OUP)
Open access: unknown

Credibility signals

serious concern Score 29/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

supportingDOI registered: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
supportingDOI resolves: A matching record was returned by Crossref. 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
serious concernRetraction Watch retraction: 1 retraction notice matched this DOI. 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
supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.1093/bioinformatics/btac218,
  title = {Retracted: DeepCRISTL: deep transfer learning to predict CRISPR/Cas9 functional and endogenous on-target editing efficiency},
  author = {Shai Elkayam and Yaron Orenstein},
  year = {2022},
  journal = {Bioinformatics},
  doi = {10.1093/bioinformatics/btac218},
  url = {https://doi.org/10.1093/bioinformatics/btac218}
}

RIS

TY  - JOUR
TI  - Retracted: DeepCRISTL: deep transfer learning to predict CRISPR/Cas9 functional and endogenous on-target editing efficiency
AU  - Shai Elkayam
AU  - Yaron Orenstein
PY  - 2022
JO  - Bioinformatics
DO  - 10.1093/bioinformatics/btac218
UR  - https://doi.org/10.1093/bioinformatics/btac218
ER  -

APA

Elkayam, S., & Orenstein, Y. (2022). Retracted: DeepCRISTL: deep transfer learning to predict CRISPR/Cas9 functional and endogenous on-target editing efficiency. Bioinformatics. https://doi.org/10.1093/bioinformatics/btac218

Source records

crossref · retrieved 2026-09-24T18:57:33.736Z