Health AI Central
Share:
Peer-Reviewed Publication
J Cheminform2024;16(1):105.August 29, 2024Journal Article

Evaluating the generalizability of graph neural networks for predicting collision cross section.

Chloe Engler Hart1, António José Preto1, Shaurya Chanana1, David Healey1, Tobias Kind1, Daniel Domingo-Fernández2
1Enveda Biosciences, Inc., 5700 Flatiron Pkwy, Boulder, CO, 80301, USA.
2Enveda Biosciences, Inc., 5700 Flatiron Pkwy, Boulder, CO, 80301, USA. daniel.domingo-fernandez@envedabio.com.
PubMed PMC DOI PDF

Abstract

Ion Mobility coupled with Mass Spectrometry (IM-MS) is a promising analytical technique that enhances molecular characterization by measuring collision cross-section (CCS) values, which are indicative of the molecular size and shape. However, the effective application of CCS values in structural analysis is still constrained by the limited availability of experimental data, necessitating the devel…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free AccountSign In

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.