Work

A fragment based approach towards curating, comparing and developing machine learning models applied in photochemistry

Year: 2025

Type: article

Abstract: In light of the development of new machine learning models for photochemical property prediction, we show that model development and database construction should focus on chromophore moieties for good extrapolation across chemical space.

Source: Chemical Science

DOI: 10.1039/d5sc05615b

Authors: Raúl Pérez-Soto, Mihai V. Popescu, Sabari Kumar, Leticia A. Gomes, Changyeob Lee, Elijah Shore, Steven A. Lopez, Robert S. Paton, Seonah Kim

Institutions: Colorado State University, Northeastern University

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funders: National Science Foundation, Colorado State University, Division of Chemistry

Awards: G3695624535, G4337423062, G8175416713, CCI Phase I: NSF Center for Sustainable Photoredox Catalysis (SuPRCat)

OpenAlex ID: W4415226823

FWCI:

Cites: 59

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Related to: 10