Machine learning–driven identification of PIM2 kinase inhibitors through QSAR modeling and molecular dynamics simulations
- DOI
- 10.1016/j.jgeb.2026.100759
- Published
- 2026-09
- Container
- Journal of Genetic Engineering and Biotechnology
- Publisher
- Elsevier BV
- 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:10.1016/j.jgeb.2026.100759,
title = {Machine learning–driven identification of PIM2 kinase inhibitors through QSAR modeling and molecular dynamics simulations},
author = {Aamir Fahira and Muhammad Shahab and Zaheer Ud Din and Xiaoan Li and Xuemin Jian},
year = {2026},
journal = {Journal of Genetic Engineering and Biotechnology},
doi = {10.1016/j.jgeb.2026.100759},
url = {https://doi.org/10.1016/j.jgeb.2026.100759}
}RIS
TY - JOUR TI - Machine learning–driven identification of PIM2 kinase inhibitors through QSAR modeling and molecular dynamics simulations AU - Aamir Fahira AU - Muhammad Shahab AU - Zaheer Ud Din AU - Xiaoan Li AU - Xuemin Jian PY - 2026 JO - Journal of Genetic Engineering and Biotechnology DO - 10.1016/j.jgeb.2026.100759 UR - https://doi.org/10.1016/j.jgeb.2026.100759 ER -
APA
Fahira, A., Shahab, M., Din, Z. U., Li, X., & Jian, X. (2026). Machine learning–driven identification of PIM2 kinase inhibitors through QSAR modeling and molecular dynamics simulations. Journal of Genetic Engineering and Biotechnology. https://doi.org/10.1016/j.jgeb.2026.100759
Source records
- crossref · retrieved 2026-09-25T12:15:09.613Z