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20222026
most citedComputer-Aided Multi-Objective Optimization in Small Molecule Discovery

136 citations · 152 across the 7 of their papers we have counts for

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5 papers · 1 filter

q-bio.QM2026

Generative structural elucidation from mass spectra as an iterative optimization problem

Mrunali Manjrekar, Runzhong Wang, Samuel Goldman +2

Liquid chromatography tandem mass spectrometry (LC-MS/MS) is a critical analytical technique for molecular identification across metabolomics, environmental chemistry, and chemical…

q-bio.QM2025

Optimal compound downselection to promote diversity and parallel chemistry

Jenna C. Fromer, Alexandra D. Volkova, Connor W. Coley

Early stage drug discovery and molecular design projects often follow iterative design-make-test cycles. The selection of which compounds to synthesize from all possible candidate…

q-bio.QM2023★ 3 cited

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…

q-bio.QM2023

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…

q-bio.QM2022★ 136 cited

Computer-Aided Multi-Objective Optimization in Small Molecule Discovery

Jenna C. Fromer, Connor W. Coley

Molecular discovery is a multi-objective optimization problem that requires identifying a molecule or set of molecules that balance multiple, often competing, properties. Multi-obj…