GenMAS: A Machine Learning-Based Modeling and Assessment Strategy for ADMET Profiling and its Application in PBPK Simulation
- DOI
- 10.1021/acs.molpharmaceut.6c00563
- Published
- 2026-10-12
- Container
- Molecular Pharmaceutics
- Publisher
- American Chemical Society (ACS)
- 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:10.1021/acs.molpharmaceut.6c00563,
title = {GenMAS: A Machine Learning-Based Modeling and Assessment Strategy for ADMET Profiling and its Application in PBPK Simulation},
author = {Yaxin Gu and Peng Qi and Lingling Ma and Guodong Zhang and Biao Lu and Fanglong Yang and Haizhou Zhang and Xiaozhen Wang and Hongcan Ren},
year = {2026},
journal = {Molecular Pharmaceutics},
doi = {10.1021/acs.molpharmaceut.6c00563},
url = {https://doi.org/10.1021/acs.molpharmaceut.6c00563}
}RIS
TY - JOUR TI - GenMAS: A Machine Learning-Based Modeling and Assessment Strategy for ADMET Profiling and its Application in PBPK Simulation AU - Yaxin Gu AU - Peng Qi AU - Lingling Ma AU - Guodong Zhang AU - Biao Lu AU - Fanglong Yang AU - Haizhou Zhang AU - Xiaozhen Wang AU - Hongcan Ren PY - 2026 JO - Molecular Pharmaceutics DO - 10.1021/acs.molpharmaceut.6c00563 UR - https://doi.org/10.1021/acs.molpharmaceut.6c00563 ER -
APA
Gu, Y., Qi, P., Ma, L., Zhang, G., Lu, B., Yang, F., Zhang, H., Wang, X., & Ren, H. (2026). GenMAS: A Machine Learning-Based Modeling and Assessment Strategy for ADMET Profiling and its Application in PBPK Simulation. Molecular Pharmaceutics. https://doi.org/10.1021/acs.molpharmaceut.6c00563
Source records
- crossref · retrieved 2026-11-07T19:50:13.504Z