Results 111 to 120 of about 3,086 (177)

Using Machine Learning for the Discovery and Development of Multitarget Flavonoid-Based Functional Products in MASLD. [PDF]

Molecules
Kuznetsov M, Klein E, Velina D, Mutallibzoda S, Orlovtseva O, Tefikova S, Klyuchnikova D, Nikitin I.   +7 more
europepmc   +1 more source

Mining the Hidden Pharmacopeia: Fungal Endophytes, Natural Products, and the Rise of AI-Driven Drug Discovery. [PDF]

Int J Mol Sci
Al Shami R, Mousa WK.
europepmc   +1 more source

The Deep Mining Era: Genomic, Metabolomic, and Integrative Approaches to Microbial Natural Products from 2018 to 2024. [PDF]

Mar Drugs
Wang Z, Yu J, Wang C, Hua Y, Wang H, Chen J.   +5 more
europepmc   +1 more source

Rotaxane synthesis <i>via</i> a dynamic [2]catenane-ring-opening, axle-cleaving double cross metathesis. [PDF]

RSC Adv
Cetin MM, Mazumdar A, Cordes DB, Fidan VG, Yang Z, Mayer MF.   +5 more
europepmc   +1 more source

Adapting CHMTRN (CHeMistry TRaNslator) for a New Use. [PDF]

J Chem Inf Model, 2020
Judson PN, Ihlenfeldt WD, Patel H, Delannée V, Tarasova N, Nicklaus MC.   +5 more
europepmc   +1 more source

FKSUDDAPre: A drug-disease association prediction framework based on F-TEST feature selection and AMDKSU resampling with interpretability analysis. [PDF]

PLoS Comput Biol
Zuo Y, Zhang C, Hua G, Ning Q, Liu X, Zeng X, Deng Z.   +6 more
europepmc   +1 more source

Identify drug-drug interactions via deep learning: A real world study. [PDF]

J Pharm Anal
Li J, Zhao Y, Wang Z, Lei C, Wu L, Zhang Y, He S, Bo X, Xiao J.   +8 more
europepmc   +1 more source

Automation and machine learning augmented by large language models in a catalysis study. [PDF]

Chem Sci
Su Y, Wang X, Ye Y, Xie Y, Xu Y, Jiang Y, Wang C.   +6 more
europepmc   +1 more source