Chemoinformatics and Metabolism

The Steinbeck Group's research in cheminformatics aims to understand the small-molecule metabolism of organism through computer-assisted structure elucidation of metabolites and prediction of metabolomes. We develop machine-learning methods to predict mass- and nuclear magnetic resonance spectra for identifcation and structure elucidation. We also develop the Chemistry Development Kit (CDK), an open source cheminformatics library and Bioclipse, an Eclipse-based rich client application.

Steinbeck Group

Selected publications

Performance Validation of Neural Network Based 13C NMR Prediction Using a Publicly Available Data Source. Blinov K.A., Smurnyy Y.D., Elyashberg M.E., Churanova T.S., Kvasha M., Steinbeck C., Lefebvre B.A., Williams A.J. (2008) Journal of Chemical Information and Modeling 48(3): 550–555.

Building blocks for automated elucidation of metabolites: Machine learning methods for NMR prediction. Kuhn S., Egert B., Neumann S. and Steinbeck C. (2008) BMC Bioinformatics. 2008 Sep 25;9(1):400.

Userscripts for the Life Sciences. BMC Bioinformatics. Willighagen E.L., O´Boyle N.O., Gopalakrishnan H., Jiao D., Guha R., Steinbeck C., Wild D.J. (2007) 8(1): 487.