Generates a Flare™ kNN regression or classification model for activity from a set of aligned molecules.
The molecules must be pre-aligned except when using kNN with 2D descriptors (see below): the ‘pyflare’ executable with the ‘align.py’ python script or the 'Flare Align' node can be used to perform the alignment.
The following types of models can be generated.
k Nearest Neighbor (kNN) regression or classification
The kNN methodology is a well-known and robust machine learning approach where the activity for each compound is predicted as the weighted average activity of its k nearest neighbors (most similar compounds) in the training set.
The similarity between the molecules is calculated using either Cresset's 3D field/shape similarity or by using 2D circular fingerprints (ECFP4, ECFP6, FCFP4, or FCFP6).
These kNN models can be used within the 'Flare Score kNN' node (wrapping the 'pyflare' executable) to predict an activity value for newly designed molecules.
Please refer to the Flare manual for a detailed description of the science behind each of these model types in Flare and the corresponding model building options.
This node wraps the 'pyflare' executable, which must be installed with a valid license for this node to work. If this is installed in the default location on Windows, then it should be found automatically. Otherwise, you must either set the 'Cresset Home' preference or the CRESSET_HOME environment variable to the base Cresset software install directory. You may also set the ‘pyflare Path' preference or the CRESSET_PYFLARE_EXE environment variable to point directly at the executable itself.
The Flare Build kNN node can be configured to use additional resources to perform calculations. The time taken for the node to run will be drastically reduced using the Cresset Engine Broker™. To use this facility either set the 'Cresset Engine Broker' preference or the CRESSET_BROKER environment variable to point to the location of your local Engine Broker. If you do not currently have the Cresset Engine Broker then contact Cresset (email@example.com) for pricing on local and cloud based brokers.
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.
A zipped version of the software site can be downloaded here.
Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.Try NodePit Runner!
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 botsin.space/@nodepit on Mastodon.
Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.