683 citations · 697 across the 7 of their papers we have counts for
7 papers
The N-ary in the Coal Mine: Avoiding Mixture Model Failure with Proper Validation
Travis Maxfield, Joshua Hochuli, James Wellnitz +4
Modeling the properties of chemical mixtures is a difficult but important part of any modeling process intended to be applicable to the often messy and impure phenomena of everyday…
PLANTAIN: Diffusion-inspired Pose Score Minimization for Fast and Accurate Molecular Docking
Michael Brocidiacono, Konstantin I. Popov, David Ryan Koes +1
Molecular docking aims to predict the 3D pose of a small molecule in a protein binding site. Traditional docking methods predict ligand poses by minimizing a physics-inspired scori…
Text Mining to Identify and Extract Novel Disease Treatments From Unstructured Datasets
Rahul Yedida, Saad Mohammad Abrar, Cleber Melo-Filho +3
Objective: We aim to learn potential novel cures for diseases from unstructured text sources. More specifically, we seek to extract drug-disease pairs of potential cures to disease…
The AFLOW Fleet for Materials Discovery
Cormac Toher, Corey Oses, David Hicks +48
The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data driven research. With the intent to accelerate the development and the d…
AFLOW-ML: A RESTful API for machine-learning predictions of materials properties
Eric Gossett, Cormac Toher, Corey Oses +8
Machine learning approaches, enabled by the emergence of comprehensive databases of materials properties, are becoming a fruitful direction for materials analysis. As a result, a p…
Universal Fragment Descriptors for Predicting Electronic Properties of Inorganic Crystals
Olexandr Isayev, Corey Oses, Cormac Toher +3
Historically, materials discovery has been driven by a laborious trial-and-error process. The growth of materials databases and emerging informatics approaches finally offer the op…