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Cited by in F6Publishing
For: Liu L, Zhang L, Feng H, Li S, Liu M, Zhao J, Liu H. Prediction of the Blood-Brain Barrier (BBB) Permeability of Chemicals Based on Machine-Learning and Ensemble Methods. Chem Res Toxicol 2021;34:1456-67. [PMID: 34047182 DOI: 10.1021/acs.chemrestox.0c00343] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
Number Citing Articles
1 Jeong K, Lee JY, Woo S, Kim D, Jeon Y, Ryu TI, Hwang SR, Jeong WH. Vapor Pressure and Toxicity Prediction for Novichok Agent Candidates Using Machine Learning Model: Preparation for Unascertained Nerve Agents after Chemical Weapons Convention Schedule 1 Update. Chem Res Toxicol 2022. [PMID: 35317551 DOI: 10.1021/acs.chemrestox.1c00410] [Reference Citation Analysis]
2 Sakiyama H, Fukuda M, Okuno T. Prediction of Blood-Brain Barrier Penetration (BBBP) Based on Molecular Descriptors of the Free-Form and In-Blood-Form Datasets. Molecules 2021;26:7428. [PMID: 34946509 DOI: 10.3390/molecules26247428] [Reference Citation Analysis]
3 Kim T, You BH, Han S, Shin HC, Chung KC, Park H. Quantum Artificial Neural Network Approach to Derive a Highly Predictive 3D-QSAR Model for Blood-Brain Barrier Passage. Int J Mol Sci 2021;22:10995. [PMID: 34681653 DOI: 10.3390/ijms222010995] [Reference Citation Analysis]
4 Zheng M, Li C, Zhou M, Jia R, Cai G, She F, Wei L, Wang S, Yu J, Wang D, Calcul L, Sun X, Luo X, Cheng F, Li Q, Wang Y, Cai J. Discovery of Cyclic Peptidomimetic Ligands Targeting the Extracellular Domain of EGFR. J Med Chem 2021;64:11219-28. [PMID: 34297567 DOI: 10.1021/acs.jmedchem.1c00607] [Reference Citation Analysis]
5 de Oliveira ECL, da Costa KS, Taube PS, Lima AH, Junior CDSDS. Biological Membrane-Penetrating Peptides: Computational Prediction and Applications. Front Cell Infect Microbiol 2022;12:838259. [DOI: 10.3389/fcimb.2022.838259] [Reference Citation Analysis]