OpenTox Algorithm ================= - An [OpenTox](http://www.opentox.org) REST Webservice - Implements the OpenTox algorithm API for - lazar - subgraph descriptor calculation (fminer) - physico-chemical descriptor calculation (pc) for more than 300 descriptors - feature selection (fs) using recursive feature elimination (rfe) - See [opentox-ruby on maunz.de](http://opentox-ruby.maunz.de) for high-level workflow documentation REST operations --------------- DESCRIPTION TYPE ADDRESS ARGUMENTS RETURN TYPE RETURN CODE Get a representation of the GET /lazar - lazar representation 200,404 lazar algorithm Get a list of all algorithms GET / - URIs of algorithms 200 Get a representation of the GET /fminer/ - fminer representation 200,404 fminer algorithms Get a representation of the GET /fminer/bbrc - bbrc representation 200,404 bbrc algorithm Get a representation of the GET /fminer/last - last representation 200,404 last algorithm Get a representation of the GET /pc - URIs of algorithms 200,404 pc algorithms Get a representation of the GET /pc/ - descriptor representation 200,404 pc algorithm Get a representation of the GET /fs - URIs of algorithms 200,404 fs algorithms Get a representation of the GET /fs/rfe - rfe representation 200,404 rfe algorithm Create lazar model POST /lazar dataset_uri, URI for lazar model 200,400,404,500 [prediction_feature], [feature_generation_uri], [feature_dataset_uri], [prediction_algorithm], [pc_type=null], [lib=null], [nr_hits=false (cl+wmv), true (else)], [min_sim=0.3 (nominal), 0.4 (numeric features)], [min_train_performance=0.1] Create bbrc features POST /fminer/bbrc dataset_uri, URI for feature dataset 200,400,404,500 prediction_feature, [min_frequency=5 per-mil], [feature_type=trees], [backbone=true], [min_chisq_significance=0.95], [nr_hits=false] Create last features POST /fminer/last dataset_uri, URI for feature dataset 200,400,404,500 prediction_feature, [min_frequency=8 %], [feature_type=trees], [nr_hits=false] Create features POST /pc/AllDescriptors dataset_uri, URI for dataset 200,400,404,500 [pc_type=constitutional, topological,geometrical, electronic,cpsa,hybrid], [lib=cdk,joelib,openbabel] Create feature POST /pc/ dataset_uri URI for dataset 200,400,404,500 Select features POST /fs/rfe dataset_uri, URI for dataset 200,400,404,500 prediction_feature, feature_dataset_uri, [del_missing=false] Synopsis -------- - *del_missing*: one of - *true* - *false* - *feature\_type*: Type of subgraphs when no feature dataset is supplied, one of - *trees* - *paths* - *lib*: Mandatory for feature datasets that do not contain appropriate feature metadata, one of - *cdk* - *openbabel* - *joelib* - *min_sim*: The minimum similarity threshold for neighbors. Numeric value in [0,1]. - *min_train_performance*. The minimum training performance for *local\_svm\_classification* (Accuracy) and *local\_svm\_regression* (R-squared). Numeric value in [0,1]. - *nr_hits*: Whether nominal features should be instantiated with their occurrence counts in the instances. One of - *true* - *false* - *pc_type*: Mandatory for feature datasets that do not contain appropriate feature metadata, one of - *geometrical* - *topological* - *electronic* - *constitutional* - *hybrid* - *cpsa* - *prediction\_algorithm*: One of - *weighted\_majority\_vote* (default for classification, n.a. for regression) - *local\_svm\_classification* - *local\_svm\_regression* (default for regression). Supported MIME formats ---------------------- - application/rdf+xml (default): read/write OWL-DL - application/x-yaml: read/write YAML Examples -------- NOTE: http://webservices.in-silico.ch hosts the stable version that might not have complete functionality yet. **Please try http://ot-test.in-silico.ch** for latest versions. ### Get the OWL-DL representation of lazar curl http://webservices.in-silico.ch/algorithm/lazar ### Get the OWL-DL representation of fminer curl http://webservices.in-silico.ch/algorithm/fminer ### Get the OWL-DL representation of pc curl http://webservices.in-silico.ch/algorithm/pc ### Get the OWL-DL representation of fs curl http://webservices.in-silico.ch/algorithm/fs * * * ### Create lazar model Creates a standard Lazar model with subgraph descriptors. curl -X POST -d dataset_uri={datset_uri} -d prediction_feature={feature_uri} -d feature_generation_uri=http://webservices.in-silico.ch/algorithm/fminer/bbrc http://webservices.in-silico.ch/test/algorithm/lazar Creates a Lazar model with physico-chemical descriptors. curl -X POST -d dataset_uri={datset_uri} -d prediction_feature={feature_uri} -d feature_dataset_uri={feature_dataset_uri} http://webservices.in-silico.ch/test/algorithm/lazar feature_uri specifies the dependent variable from the dataset. * * * Creates subgraph descriptors with backbone refinement class representatives or latent structure patterns, using supervised graph mining, see http://cs.maunz.de. These features can be used e.g. as structural alerts, as descriptors (fingerprints) for prediction models or for similarity calculations. ### Create the full set of frequent and significant subtrees curl -X POST -d dataset_uri={datset_uri} -d prediction_feature={feature_uri} -d min_frequency={min_frequency} -d "backbone=false" http://webservices.in-silico.ch/algorithm/fminer/bbrc feature_uri specifies the dependent variable from the dataset. backbone=false reduces BBRC mining to frequent and correlated subtree mining (much more descriptors are produced). ### Create [BBRC](http://bbrc.maunz.de) features, recommended for large and very large datasets. curl -X POST -d dataset_uri={datset_uri} -d prediction_feature={feature_uri} -d min_frequency={min_frequency} http://webservices.in-silico.ch/algorithm/fminer/bbrc feature_uri specifies the dependent variable from the dataset. Adding -d nr_hits=true produces frequency counts per pattern and molecule. Click [here](http://bbrc.maunz.de#usage) for more guidance on usage. ### Create [LAST-PM](http://last-pm.maunz.de) descriptors, recommended for small to medium-sized datasets. curl -X POST -d dataset_uri={datset_uri} -d prediction_feature={feature_uri} -d min_frequency={min_frequency} http://webservices.in-silico.ch/algorithm/fminer/last feature_uri specifies the dependent variable from the dataset. Adding -d nr_hits=true produces frequency counts per pattern and molecule. Click [here](http://last-pm.maunz.de#usage) for guidance for more guidance on usage. * * * ### Create a feature dataset of physico-chemical descriptors with CDK curl -X POST -d dataset_uri={dataset_uri} -d lib=cdk http://webservices.in-silico.ch/test/algorithm/pc/AllDescriptors lib specifies the library to use. * * * ### Select features from a feature dataset curl -X POST -d dataset_uri={dataset_uri} -d prediction_feature={feature_uri} -d feature_dataset_uri={feature_dataset_uri} http://webservices.in-silico.ch/test/algorithm/fs/rfe feature_uri specifies the dependent variable from the dataset. * * * Copyright (c) 2009-2011 Christoph Helma, Martin Guetlein, Micha Rautenberg, Andreas Maunz, David Vorgrimmler, Denis Gebele. See LICENSE for details.