Erlwood Knime Open Source Cheminformatics version 4.0.0.v201906261333 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:
You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.
Do you have feedback, questions, comments about NodePit, want to support this platform, or want your own nodes or workflows listed here as well? Do you think, the search results could be improved or something is missing? Then please get in touch! Alternatively, you can send us an email to firstname.lastname@example.org, follow @NodePit on Twitter, or chat on Gitter!
Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.