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Diffstat (limited to 'README.md')
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1 files changed, 126 insertions, 62 deletions
@@ -3,66 +3,104 @@ OpenTox Algorithm - An [OpenTox](http://www.opentox.org) REST Webservice - Implements the OpenTox algorithm API for - - fminer - 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 --------------- - 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 + 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 /lazar - lazar representation 200,404 - lazar algorithm - Get a representation of the GET /feature_selection - feature selection representation 200,404 - feature selection algorithms - Get a representation of the GET /feature_selection/rfe - rfe representation 200,404 - rfe algorithm - - - Create bbrc features POST /fminer/bbrc dataset_uri, URI for feature dataset 200,400,404,500 - feature_uri, - [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 - feature_uri, - [min_frequency=8 %], - [feature_type=trees], - [nr_hits=false] - Create lazar model POST /lazar dataset_uri, URI for lazar model 200,400,404,500 - [prediction_feature], - [feature_generation_uri], - [prediction_algorithm], - [feature_dataset_uri], - [pc_type=null], - [nr_hits=false (class. using wt. maj. vote), true (else)], - [min_sim=0.3 (nominal), 0.4 (numeric features)] - [min_train_performance=0.1] - - Create selected features POST /feature_selection/rfe dataset_uri, URI for dataset 200,400,404,500 - prediction_feature, - feature_dataset_uri, - [del_missing=false] - + 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/<name> - descriptor representation 200,404 + pc algorithm <name> + 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/<name> 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 -------- -- prediction\_algorithm: One of "weighted\_majority\_vote" (default for classification), "local\_svm\_classification", "local\_svm\_regression" (default for regression). "weighted\_majority\_vote" is not applicable for regression. -- pc_type: Mandatory for feature dataset, one of [geometrical, topological, electronic, constitutional, hybrid, cpsa]. -- nr_hits: Whether nominal features should be instantiated with their occurrence counts in the instances. One of "true", "false". -- 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]. -- del_missing: one of true, false +- *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]. -See http://www.maunz.de/wordpress/opentox/2011/lazar-models-and-how-to-trigger-them for a graphical overview. +- *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 @@ -76,17 +114,39 @@ 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 lazar +### Get the OWL-DL representation of pc - curl http://webservices.in-silico.ch/algorithm/lazar + curl http://webservices.in-silico.ch/algorithm/pc + +### Get the OWL-DL representation of fs + + curl http://webservices.in-silico.ch/algorithm/fs * * * -The following creates datasets 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 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 @@ -101,7 +161,7 @@ backbone=false reduces BBRC mining to frequent and correlated subtree mining (mu feature_uri specifies the dependent variable from the dataset. Adding -d nr_hits=true produces frequency counts per pattern and molecule. -Please click [here](http://bbrc.maunz.de#usage) for more guidance on usage. +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. @@ -109,22 +169,26 @@ Please click [here](http://bbrc.maunz.de#usage) for more guidance on usage. feature_uri specifies the dependent variable from the dataset. Adding -d nr_hits=true produces frequency counts per pattern and molecule. -Please click [here](http://last-pm.maunz.de#usage) for guidance for more guidance on usage. +Click [here](http://last-pm.maunz.de#usage) for guidance for more guidance on usage. -* * * -### Create lazar model +* * * -Creates a standard Lazar model. +### Create a feature dataset of physico-chemical descriptors with CDK - 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 + curl -X POST -d dataset_uri={dataset_uri} -d lib=cdk http://webservices.in-silico.ch/test/algorithm/pc/AllDescriptors -[API documentation](http://rdoc.info/github/opentox/algorithm) --------------------------------------------------------------- +lib specifies the library to use. * * * -### Create a feature dataset of selected features - curl -X POST -d dataset_uri={dataset_uri} -d prediction_feature_uri={prediction_feature_uri} -d feature_dataset_uri={feature_dataset_uri} -d del_missing=true http://webservices.in-silico.ch/test/algorithm/feature_selection/rfe +### 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. + |