Fully automated antibody structure prediction using BIOVIA tools: Validation study

Helen Kemmish, Marc Fasnacht, Lisa Yan

Open source

DOI: 10.1371/journal.pone.0177923
Published: 2017-05-18
Container: PLOS ONE
Publisher: Public Library of Science (PLoS)
Open access: unknown

Credibility signals

uncertain Score 64/100 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
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
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:10.1371/journal.pone.0177923,
  title = {Fully automated antibody structure prediction using BIOVIA tools: Validation study},
  author = {Helen Kemmish and Marc Fasnacht and Lisa Yan},
  year = {2017},
  journal = {PLOS ONE},
  doi = {10.1371/journal.pone.0177923},
  url = {https://doi.org/10.1371/journal.pone.0177923}
}

RIS

TY  - JOUR
TI  - Fully automated antibody structure prediction using BIOVIA tools: Validation study
AU  - Helen Kemmish
AU  - Marc Fasnacht
AU  - Lisa Yan
PY  - 2017
JO  - PLOS ONE
DO  - 10.1371/journal.pone.0177923
UR  - https://doi.org/10.1371/journal.pone.0177923
ER  -

APA

Kemmish, H., Fasnacht, M., & Yan, L. (2017). Fully automated antibody structure prediction using BIOVIA tools: Validation study. PLOS ONE. https://doi.org/10.1371/journal.pone.0177923

Source records

crossref · retrieved 2026-09-25T14:05:50.370Z