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[http://sea.docking.org sea.docking.org] | [http://sea.docking.org sea.docking.org] | ||
[[install SEA]] | |||
== How to generate a model to run SEA == | |||
We need the files: reference.smi ; reference.set ; reference.fp | |||
First we need to generate the background Z-score distribution: | |||
[prompt]$ sea-background reference.set.gz | |||
This generated the file model.out | |||
Then we need to fit data the data from this background model and build a fit parameter file: | |||
[prompt]$ sea-fit model.out | |||
This generates the file model.out.distfit, containing the values for the best fit of the background distribution to a normal and an extreme value distribution. From this distribution, we need to select the optimal cutoff and then use it to get the fit file. | |||
[prompt]$ sea-fit -c cutoff model.out | |||
Revision as of 19:33, 30 August 2012
SEA, the similarity ensemble approach. sea.docking.org
How to generate a model to run SEA
We need the files: reference.smi ; reference.set ; reference.fp
First we need to generate the background Z-score distribution:
[prompt]$ sea-background reference.set.gz
This generated the file model.out
Then we need to fit data the data from this background model and build a fit parameter file:
[prompt]$ sea-fit model.out
This generates the file model.out.distfit, containing the values for the best fit of the background distribution to a normal and an extreme value distribution. From this distribution, we need to select the optimal cutoff and then use it to get the fit file.
[prompt]$ sea-fit -c cutoff model.out