Erlwood Knime Open Source Cheminformatics version 3.3.0.v201701271213 by Erlwood
Computes set of popular performance estimations for a virtual screening. The input is expect to be sorted according to the ranking criteria (performance estimate), such that the most promising compound is in the first row. The measure computed are the enrichment factor in the top X%, the area under the ROC curve (AUROC), the robust initial enhancement (RIE, Sheridan et al, JCICS, 2001, 41, 1395−1406) and the Boltzmann-enhanced discrimination of ROC (BEDROC, Truchon and Bayly, JCIM, 2007, 47 (2), pp 488–508)
To use this node in KNIME, install Erlwood Knime Open Source Cheminformatics from the following update site:
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