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Nathaniel Morgan Charest

Cheminformatician III

Underwriters Laboratories Research Institutes

United States

Research Interests

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Articles (15)

Collaborators (2)

Katie Friedman

Director, Center for Chemical Informatics and Screening

Underwriters Laboratories Research Institutes

UNITED STATES

Krystal Godri Pollitt

Associate Professor

Yale University

UNITED STATES

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Nathaniel Morgan Charest

Research Interests

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Articles (15)

Collaborators (2)

Katie Friedman

Krystal Godri Pollitt

Make your next move.

Nathaniel Morgan Charest

Research Interests

Make your next move.

Explore related searches

Articles (15)

Application of a Quantitative Non-targeted Analysis Workflow to Characterize PFAS in Environmental Waters

Filling the Gaps in PFAS Detection: Integrating GC-MS Non-Targeted Analysis for Comprehensive Environmental Monitoring and Exposure Assessment

Correction to: Examining the effects of analytical replication on data quality in a non‑targeted analysis experiment

Physicochemical Property Models for Poly- and Perfluorinated Alkyl Substances and Other Chemical Classes

Curating and Visualizing the Analytical Methods and the Open Spectral Database’s Chemical Functional Use Taxonomy

Prediction of Fraction Unbound in Human Plasma for Per- and Polyfluoroalkyl Substances: Evaluating Transfer Learning as an Algorithmic Solution to the Problem of Sparse Data

Examining structure-based surrogate selection for quantitative non-targeted analysis

Examining the effects of analytical replication on data quality in a non-targeted analysis experiment

Correction to Citation in “Combined In Vitro and In Silico Workflow to Deliver Robust, Transparent, and Contextually Rigorous Models of Bioactivity”

Combined In Vitro and In Silico Workflow to Deliver Robust, Transparent, and Contextually Rigorous Models of Bioactivity

Molecular similarity in chemical informatics and predictive toxicity modeling: from quantitative read-across (q-RA) to quantitative read-across structure–activity relationship (q-RASAR) with the application of machine learning

Improving predictions of compound amenability for liquid chromatography–mass spectrometry to enhance non-targeted analysis

Free and open-source QSAR-ready workflow for automated standardization of chemical structures in support of QSAR modeling

Discovering pathways through ribozyme fitness landscapes using information theoretic quantification of epistasis

Transparency in Modeling through Careful Application of OECD’s QSAR/QSPR Principles via a Curated Water Solubility Data Set

Collaborators (2)

Katie Friedman

Krystal Godri Pollitt

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