DTIAM: A unified framework for predicting drug-target interactions, binding affinities and activation/inhibition mechanisms

23 December 2023

Papers citing "DTIAM: A unified framework for predicting drug-target interactions, binding affinities and activation/inhibition mechanisms"

7 / 7 papers shown

Title
GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation Minkai Xu Lantao Yu Yang Song Chence Shi Stefano Ermon Jian Tang BDL DiffM 164 521 0 06 Mar 2022
AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data Nick Erickson Jonas W. Mueller Alexander Shirkov Hang Zhang Pedro Larroy Mu Li Alex Smola LMTD 218 631 0 13 Mar 2020
Self-Attention Based Molecule Representation for Predicting Drug-Target Interaction Bonggun Shin Sungsoo Park Keunsoo Kang Joyce C. Ho 63 138 0 15 Aug 2019
GuacaMol: Benchmarking Models for De Novo Molecular Design Nathan Brown Marco Fiscato Marwin H. S. Segler Alain C. Vaucher ELM 114 713 0 22 Nov 2018
DeepAffinity: Interpretable Deep Learning of Compound-Protein Affinity through Unified Recurrent and Convolutional Neural Networks Mostafa Karimi Di Wu Zhangyang Wang Yang Shen 77 361 0 20 Jun 2018
DeepDTA: Deep Drug-Target Binding Affinity Prediction Hakime Öztürk E. Olmez Arzucan Özgür 113 1,080 0 30 Jan 2018
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 598 7,496 0 04 Apr 2017