{"title":"用于内皮细胞给药 DPD 模拟的性能空间映射机器学习","authors":"Saeed Akbari Shandiz, Soumya Ray, Fei Zhou, Xiao Chen, Joao Maia","doi":"10.1080/08927022.2024.2333903","DOIUrl":null,"url":null,"abstract":"Despite huge effort over the years, the design of functionalised nanocarriers (NCs) for targeted drug delivery to endothelial cells is still to be completely unveiled. Dissipative particle dynamics...","PeriodicalId":18863,"journal":{"name":"Molecular Simulation","volume":"116 1","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Machine learning of performance space mapping for the DPD simulation of drug delivery to endothelial cells\",\"authors\":\"Saeed Akbari Shandiz, Soumya Ray, Fei Zhou, Xiao Chen, Joao Maia\",\"doi\":\"10.1080/08927022.2024.2333903\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Despite huge effort over the years, the design of functionalised nanocarriers (NCs) for targeted drug delivery to endothelial cells is still to be completely unveiled. Dissipative particle dynamics...\",\"PeriodicalId\":18863,\"journal\":{\"name\":\"Molecular Simulation\",\"volume\":\"116 1\",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Molecular Simulation\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://doi.org/10.1080/08927022.2024.2333903\",\"RegionNum\":4,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"CHEMISTRY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Simulation","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1080/08927022.2024.2333903","RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
Machine learning of performance space mapping for the DPD simulation of drug delivery to endothelial cells
Despite huge effort over the years, the design of functionalised nanocarriers (NCs) for targeted drug delivery to endothelial cells is still to be completely unveiled. Dissipative particle dynamics...
期刊介绍：
Molecular Simulation covers all aspects of research related to, or of importance to, molecular modelling and simulation.
Molecular Simulation brings together the most significant papers concerned with applications of simulation methods, and original contributions to the development of simulation methodology from biology, biochemistry, chemistry, engineering, materials science, medicine and physics.
The aim is to provide a forum in which cross fertilization between application areas, methodologies, disciplines, as well as academic and industrial researchers can take place and new developments can be encouraged.
Molecular Simulation is of interest to all researchers using or developing simulation methods based on statistical mechanics/quantum mechanics. This includes molecular dynamics (MD, AIMD), Monte Carlo, ab initio methods related to simulation, multiscale and coarse graining methods.
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