167 citations · 291 across the 16 of their papers we have counts for
17 papers
A Comparative Study of QSPR Methods on a Unique Multitask PAMPA dataset
Andrs Formanek, Anna Vincze, Richrd Bicsak +3
We present a unique, multitask dataset comprising 143 drug and drug candidate molecules, each evaluated on in vitro, parallel artificial-membrane permeability assays (PAMPA) using…
Enhancing Uncertainty Quantification in Drug Discovery with Censored Regression Labels
Emma Svensson, Hannah Rosa Friesacher, Susanne Winiwarter +3
In the early stages of drug discovery, decisions regarding which experiments to pursue can be influenced by computational models. These decisions are critical due to the time-consu…
Achieving Well-Informed Decision-Making in Drug Discovery: A Comprehensive Calibration Study using Neural Network-Based Structure-Activity Models
Hannah Rosa Friesacher, Ola Engkvist, Lewis Mervin +2
In the drug discovery process, where experiments can be costly and time-consuming, computational models that predict drug-target interactions are valuable tools to accelerate the d…
Atom-Level Optical Chemical Structure Recognition with Limited Supervision
Martijn Oldenhof, Edward De Brouwer, Adam Arany +1
Identifying the chemical structure from a graphical representation, or image, of a molecule is a challenging pattern recognition task that would greatly benefit drug development. Y…
Weakly Supervised Knowledge Transfer with Probabilistic Logical Reasoning for Object Detection
Martijn Oldenhof, Adam Arany, Yves Moreau +1
Training object detection models usually requires instance-level annotations, such as the positions and labels of all objects present in each image. Such supervision is unfortunate…
Industry-Scale Orchestrated Federated Learning for Drug Discovery
Martijn Oldenhof, Gergely Ács, Balázs Pejó +44
To apply federated learning to drug discovery we developed a novel platform in the context of European Innovative Medicines Initiative (IMI) project MELLODDY (grant n°831472), whic…