首页|New Machine Learning Study Findings Reported from University of Minnesota (Polym er Design via Shap and Bayesian Machine Learning Optimizes Pdna and Crispr Ribon ucleoprotein Delivery)
New Machine Learning Study Findings Reported from University of Minnesota (Polym er Design via Shap and Bayesian Machine Learning Optimizes Pdna and Crispr Ribon ucleoprotein Delivery)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - New research on Machine Learning is th e subject of a report. According to news reporting out of Minneapolis, Minnesota , by NewsRx editors, research stated, “We present the facile synthesis of a clic kable polymer library with systematic variations in length, binary composition, pK(a), and hydrophobicity (clog P) to optimize intracellular pDNA and CRISPR-Cas 9 ribonucleoprotein (RNP) performance. We couple physicochemical characterizatio n and machine learning to interpret quantitative structure-property relationship s within the combinatorial design space.”
MinneapolisMinnesotaUnited StatesN orth and Central AmericaCarrier ProteinsCyborgsEmerging TechnologiesMach ine LearningRNA-Binding ProteinsRibonucleoproteinsUniversity of Minnesota
NETL
NSTL
