Predicting cell-penetrating peptides using machine learning algorithms and navigating in their chemical space
- DOI
- 10.1038/s41598-021-87134-w
- Published
- 2021-04-07
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- 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.
- supportingDOI resolves: A matching record was returned by Crossref.
- 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.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1038/s41598-021-87134-w,
title = {Predicting cell-penetrating peptides using machine learning algorithms and navigating in their chemical space},
author = {Ewerton Cristhian Lima de Oliveira and Kauê Santana and Luiz Josino and Anderson Henrique Lima e Lima and Claudomiro de Souza de Sales Júnior},
year = {2021},
journal = {Scientific Reports},
doi = {10.1038/s41598-021-87134-w},
url = {https://doi.org/10.1038/s41598-021-87134-w}
}RIS
TY - JOUR TI - Predicting cell-penetrating peptides using machine learning algorithms and navigating in their chemical space AU - Ewerton Cristhian Lima de Oliveira AU - Kauê Santana AU - Luiz Josino AU - Anderson Henrique Lima e Lima AU - Claudomiro de Souza de Sales Júnior PY - 2021 JO - Scientific Reports DO - 10.1038/s41598-021-87134-w UR - https://doi.org/10.1038/s41598-021-87134-w ER -
APA
Oliveira, E. C. L. D., Santana, K., Josino, L., Lima, A. H. L. E., & Júnior, C. D. S. D. S. (2021). Predicting cell-penetrating peptides using machine learning algorithms and navigating in their chemical space. Scientific Reports. https://doi.org/10.1038/s41598-021-87134-w
Source records
- crossref · retrieved 2026-11-10T10:27:08.832Z