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Cell Reports|March 19, 2020
Machine Learning Uncovers Food- and Excipient-Drug InteractionsDaniel Reker, Yunhua Shi, Ameya R Kirtane, et al.
Plos Computational Biology|June 3, 2024
Data-driven learning of structure augments quantitative prediction of biological responsesYuanchi Ha, Helena R Ma, Feilun Wu, et al.
ACS Pharmacology & Translational Science|July 15, 2026
Identifying Antibiotic Effects of Investigational Drugs on Commensal Bacteria with Machine LearningHrshita Gowda, Wenbo Lu, Paul Skaluba, et al.
ACS Nano|September 11, 2025
TuNa-AI: A Hybrid Kernel Machine To Design Tunable Nanoparticles for Drug DeliveryZilu Zhang, Yan Xiang, Joe Laforet, et al.
Small (Weinheim an Der Bergstrasse, Germany)|February 6, 2026
Genetically Encoded Sterol-Modification of a Synthetic Intrinsically Disordered Protein Drives Its Self-Assembly Into Diverse MorphologiesSarah Yeon-Kyoung Kim, Taranpreet Kaur, Yulia Shmidov, et al.
Cancer Immunology, Immunotherapy : CII|April 18, 2013
Vaccination with anti-idiotype antibody ganglidiomab mediates a GD(2)-specific anti-neuroblastoma immune responseHolger N Lode, Manuela Schmidt, Diana Seidel, et al.
Angewandte Chemie (International Ed. in English)|June 13, 2015
Fragment-Based De Novo Design Reveals a Small-Molecule Inhibitor of Helicobacter Pylori HtrAAnna M Perna, Tiago Rodrigues, Thomas P Schmidt, et al.
Nature Nanotechnology|May 15, 2024
A large-scale machine learning analysis of inorganic nanoparticles in preclinical cancer researchBárbara B Mendes, Zilu Zhang, João Conniot, et al.
Scientific Reports|May 24, 2019
Predicting protein-ligand interactions based on bow-pharmacological space and Bayesian additive regression treesLi Li, Ching Chiek Koh, Daniel Reker, et al.
Nature Chemistry|November 21, 2014
Revealing the macromolecular targets of complex natural productsDaniel Reker, Anna M Perna, Tiago Rodrigues, et al.
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