KNIME provides non-programmers with access to a toolkit for developing algorithms and repeating procedures, and has a large number of nodes covering a wide range of activities. Researchers within Lhasa Limited frequently use KNIME to support data exploration, processing, mining and exploratory work in cheminformatics, as well as (Q)SAR modelling and machine learning.
The research group at Lhasa Limited has developed a collection of new nodes internally. Lhasa believes in ‘shared knowledge, shared progress’ and so have released a portion of these nodes for public use1. Currently the released nodes cover table manipulation and supporting activities for the assessment of binary classification models as well as running SmartCyp2,3 and WhichCyp4 for metabolism predictions.
Example KNIME Workflow: reads in a dataset of cytochrome P450 metabolised structures with recorded sites of metabolism (SOM). Uses SMARTCyp to predict the SOM and then extract some details.
If you are interested in KNIME nodes, Dr. Sam Webb, Research Scientist at Lhasa Limited, will present a webinar on “Lhasa trusted community KNIME nodes: data processing and metabolism predictions” on the 18thof May. Find out more here.
References
[1] S. J. Webb. Lhasa trusted community KNIME nodes: data processing and metabolism prediction, Lhasa Limited, 2016
[2] P. Rydberg, D. E. Gloriam, J. Zaretzki, C. Breneman and L. Olsen. SMARTCyp: A 2D Method for Prediction of Cytochrome P450-Mediated Drug Metabolism, ACS Medicinal Chemistry Letters, 2010, 1, 96-100.
[3] P. Rydberg, D.E. Gloriam, L. Olsen. The SMARTCyp cytochrome P450 metabolism prediction server, Bioinformatics, 2010, 26, 2988-2989.
[4] M. Rostkowski, O. Spiuth, P Rydberg. WhichCyp: Prediciton of Cytovhromes P450 Inhibition, Bioinformatics, 2013, 29, 2051-2052
