NeoGen-BC: A synergistic framework combining generative protein language models and multi-window deep learning for designing shared neoantigens in breast cancer.
- DOI
- 10.1016/j.bbrc.2026.154567
- Published
- 2026 Sep 9
- Container
- Biochemical and biophysical research communications
- Publisher
- Not recorded
- Open access
- no
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.
- 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.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- 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:10.1016/j.bbrc.2026.154567,
title = {NeoGen-BC: A synergistic framework combining generative protein language models and multi-window deep learning for designing shared neoantigens in breast cancer.},
author = {Le VT and Yuune JPT and Lai JI and Ou YY},
year = {2026},
journal = {Biochemical and biophysical research communications},
doi = {10.1016/j.bbrc.2026.154567},
url = {https://doi.org/10.1016/j.bbrc.2026.154567}
}RIS
TY - JOUR TI - NeoGen-BC: A synergistic framework combining generative protein language models and multi-window deep learning for designing shared neoantigens in breast cancer. AU - Le VT AU - Yuune JPT AU - Lai JI AU - Ou YY PY - 2026 JO - Biochemical and biophysical research communications DO - 10.1016/j.bbrc.2026.154567 UR - https://doi.org/10.1016/j.bbrc.2026.154567 ER -
APA
VT, L., JPT, Y., JI, L., & YY, O. (2026). NeoGen-BC: A synergistic framework combining generative protein language models and multi-window deep learning for designing shared neoantigens in breast cancer.. Biochemical and biophysical research communications. https://doi.org/10.1016/j.bbrc.2026.154567
Source records
- pubmed · retrieved 2026-09-26T00:52:05.217Z
- europe-pmc · retrieved 2026-09-26T00:52:05.226Z