OpenTox Algorithm

  • An OpenTox 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 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/<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

  • 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 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 for more guidance on usage.

Create LAST-PM 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 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.