330 citations · 2.7k across the 74 of their papers we have counts for
10 papers · 1 filter
Predictive Chemistry Augmented with Text Retrieval
Yujie Qian, Zhening Li, Zhengkai Tu +2
This paper focuses on using natural language descriptions to enhance predictive models in the chemistry field. Conventionally, chemoinformatics models are trained with extensive st…
An algorithmic framework for synthetic cost-aware decision making in molecular design
Jenna C. Fromer, Connor W. Coley
Small molecules exhibiting desirable property profiles are often discovered through an iterative process of designing, synthesizing, and testing sets of molecules. The selection of…
Pareto Optimization to Accelerate Multi-Objective Virtual Screening
Jenna C. Fromer, David E. Graff, Connor W. Coley
The discovery of therapeutic molecules is fundamentally a multi-objective optimization problem. One formulation of the problem is to identify molecules that simultaneously exhibit…
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks
Yanqiao Zhu, Jeehyun Hwang, Keir Adams +10
Molecular Representation Learning (MRL) has proven impactful in numerous biochemical applications such as drug discovery and enzyme design. While Graph Neural Networks (GNNs) are e…
MIST-CF: Chemical formula inference from tandem mass spectra
Samuel Goldman, Jiayi Xin, Joules Provenzano +1
Chemical formula annotation for tandem mass spectrometry (MS/MS) data is the first step toward structurally elucidating unknown metabolites. While great strides have been made towa…
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
Xuan Zhang, Limei Wang, Jacob Helwig +60
Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural sciences. Today, AI has started to advance natural sciences by improving, accelerating…
RxnScribe: A Sequence Generation Model for Reaction Diagram Parsing
Yujie Qian, Jiang Guo, Zhengkai Tu +2
Reaction diagram parsing is the task of extracting reaction schemes from a diagram in the chemistry literature. The reaction diagrams can be arbitrarily complex, thus robustly pars…
Evaluating the roughness of structure-property relationships using pretrained molecular representations
David E. Graff, Edward O. Pyzer-Knapp, Kirk E. Jordan +2
Quantitative structure-property relationships (QSPRs) aid in understanding molecular properties as a function of molecular structure. When the correlation between structure and pro…
Generating Molecular Fragmentation Graphs with Autoregressive Neural Networks
Samuel Goldman, Janet Li, Connor W. Coley
The accurate prediction of tandem mass spectra from molecular structures has the potential to unlock new metabolomic discoveries by augmenting the community's libraries of experime…
Prefix-Tree Decoding for Predicting Mass Spectra from Molecules
Samuel Goldman, John Bradshaw, Jiayi Xin +1
Computational predictions of mass spectra from molecules have enabled the discovery of clinically relevant metabolites. However, such predictive tools are still limited as they occ…