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OpenTox lazar
=============
* An OpenTox REST Webservice (http://www.opentox.org)
* Ruby implementation of the lazar algorithm
* Implements a subset of the OpenTox algorithm/model API (http://opentox.org/wiki/opentox/Structure).
* Current version runs at http://webservices.in-silico.ch/lazar/v0
REST API
Description Method URI Parameters Result Status codes
Get index of all GET /models List of model URIs 200, 500
models
Get model description GET /model{id} YAML with model 200, 202, 404, 500
representation
Create a prediction POST / dataset_uri Model URI 200, 500
model
Delete a model DELETE /{id} 200, 404, 500
Create a prediction POST /{id} compound_uri Prediction URI 200, 404, 500
Get index of all GET /predictions List of prediction 200, 500
predictions URIs
Show a prediction GET /prediction/{id} YAML with prediction 200, 202, 404, 500
result
Show neighbors for a GET /prediction/{id} YAML with neighbors 200, 404, 500
prediction /neighbors
Show relevant features GET /prediction/{id} YAML with relevant 200, 404, 500
for a prediction /features features
Delete a prediction DELETE /prediction/{id} 200, 404, 500
EXAMPLES
Model creation:
Create a dataset from a csv file:
curl -X POST -F name="Hamster carcinogenicity" -F file=@hamster_carcinogenicity.csv http://webservices.in-silico.ch/dataset/v0/
returns a {dataset_uri}
Create a prediction model from a dataset:
curl -X POST -d dataset_uri={dataset_uri} http://webservices.in-silico.ch/lazar/v0/models
returns a {model_uri}
Get model information:
curl {model_uri} (returns status code 202, if model is still under construction)
Prediction:
Create a compound URI:
curl -X POST -d name=Phenylhydrazine http://webservices.in-silico.ch/compound/v0/
returns http://webservices.in-silico.ch/compound/v0/NNc1ccccc1
Predict the compound:
curl -X POST -d compound_uri=http://webservices.in-silico.ch/compound/v0/NNc1ccccc1 {model_uri}
returns a {prediction_uri}
Show the prediction:
curl {prediction_uri} (returns status code 202, if prediction is still running)
Show prediction neighbors:
curl {prediction_uri}/neighbors
Show relevant features for a prediction:
curl {prediction_uri}/features
INSTALLATION
Run 'rake install' to install the required gems
Copyright (c) 2009 Christoph Helma. See LICENSE for details.
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