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Cited by in F6Publishing
For: Patel RA, Borca CH, Webb MA. Featurization strategies for polymer sequence or composition design by machine learning. Mol Syst Des Eng 2022;7:661-76. [DOI: 10.1039/d1me00160d] [Cited by in Crossref: 7] [Cited by in F6Publishing: 8] [Article Influence: 7.0] [Reference Citation Analysis]
Number Citing Articles
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2 Martin TB, Audus DJ. Emerging Trends in Machine Learning: A Polymer Perspective. ACS Polym Au 2023. [DOI: 10.1021/acspolymersau.2c00053] [Reference Citation Analysis]
3 Ramesh PS, Patra TK. Polymer sequence design via molecular simulation-based active learning. Soft Matter 2023;19:282-94. [PMID: 36519427 DOI: 10.1039/d2sm01193j] [Reference Citation Analysis]
4 Meyer TA, Ramirez C, Tamasi MJ, Gormley AJ. A User’s Guide to Machine Learning for Polymeric Biomaterials. ACS Polym Au 2022. [DOI: 10.1021/acspolymersau.2c00037] [Reference Citation Analysis]
5 Tamasi MJ, Gormley AJ. Biologic formulation in a self-driving biomaterials lab. Cell Reports Physical Science 2022;3:101041. [DOI: 10.1016/j.xcrp.2022.101041] [Reference Citation Analysis]
6 Tao L, Byrnes J, Varshney V, Li Y. Machine learning strategies for the structure-property relationship of copolymers. iScience 2022;25:104585. [DOI: 10.1016/j.isci.2022.104585] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
7 Bhattacharya D, Kleeblatt DC, Statt A, Reinhart WF. Predicting aggregate morphology of sequence-defined macromolecules with recurrent neural networks. Soft Matter 2022. [PMID: 35748651 DOI: 10.1039/d2sm00452f] [Reference Citation Analysis]
8 Kumar R. Materiomically Designed Polymeric Vehicles for Nucleic Acids: Quo Vadis? ACS Appl Bio Mater 2022. [PMID: 35642794 DOI: 10.1021/acsabm.2c00346] [Reference Citation Analysis]
9 Xu Q, Jiang J. Recent development in machine learning of polymer membranes for liquid separation. Mol Syst Des Eng . [DOI: 10.1039/d2me00023g] [Reference Citation Analysis]
10 Aldeghi M, Coley CW. A graph representation of molecular ensembles for polymer property prediction. Chem Sci . [DOI: 10.1039/d2sc02839e] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]