activity
20182020
collaborators

5 papers

physics.chem-ph2020

Exploring the impacts of conformer selection methods on ion mobility collision cross section predictions

Felicity F. Nielson, Sean M. Colby, Dennis G. Thomas +2

The prediction of structure dependent molecular properties, such as collision cross sections as measured using ion mobility spectrometry, are crucially dependent on the selection o…

q-bio.BM2020

Application and Assessment of Deep Learning for the Generation of Potential NMDA Receptor Antagonists

Katherine J. Schultz, Sean M. Colby, Yasemin Yesiltepe +3

Uncompetitive antagonists of the N-methyl D-aspartate receptor (NMDAR) have demonstrated therapeutic benefit in the treatment of neurological diseases such as Parkinson's and Alzhe…

q-bio.BM2019

Deep learning to generate in silico chemical property libraries and candidate molecules for small molecule identification in complex samples

Sean M. Colby, Jamie R. Nuñez, Nathan O. Hodas +2

Comprehensive and unambiguous identification of small molecules in complex samples will revolutionize our understanding of the role of metabolites in biological systems. Existing a…

q-bio.BM2018

Advancing Standards-Free Methods for the Identification of Small Molecules in Complex Samples

Jamie R. Nuñez, Sean M. Colby, Dennis G. Thomas +7

The current gold standard for unambiguous identification in metabolomics analysis is based on comparing two or more orthogonal properties from the analysis of authentic, pure refer…

q-bio.BM2018

ISiCLE: A molecular collision cross section calculation pipeline for establishing large in silico reference libraries for compound identification

Sean M. Colby, Dennis G. Thomas, Jamie R. Nunez +8

Comprehensive and confident identifications of metabolites and other chemicals in complex samples will revolutionize our understanding of the role these chemically diverse molecule…