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        "author": "Tu Vu",
        "author_email": "tvu@ebi.ac.uk",
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            "License :: OSI Approved :: GNU Affero General Public License v3",
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        "description": "\n# DeepOC\n\nDeepOC is the core of [BioModel Classifier](https://bitbucket.org/biomodels/model-classifier/src/master/) - the python application to classify biomodels automatically using Deep Neural Network. DeepOC provides some very low level functions for classifying model based on ontology, which allow us to adapt to any other projects.\n\n## Installing\n\n    pip install deepoc\n\n## Usage\nFirst, you need a ground truth dataset, which is a dict of model and list of it's corresponding ontologies\n\n    {\n\t    \"model_1\": [\"GO:00001\", \"GO:00003\", \"GO:00002\"],\n\t    \"model_2: [\"GO:00004\", \"GO:00002\"]\n    }\nTo generate dataset and train DNN model:\n\n    ground_truth = ...\n    train_file = \"path/to/your train csv file\"\n    test_file = \"path/to/your test csv file\"\n    val_file = \"path/to/your val csv file\"\n    features = deepoc.build_features(ground_truth)\n\n    # Picking the first 300 features  \n    selected_features = [feature['feature'] for idx, feature in enumerate(features) if idx < 300]\n\n    train, test, val = deepoc.generate_dataset(ground_truth, features, classes)\n\n    # Writing dataset to file  \n    deepoc.write_dataset_to_file(train, train_file)  \n    deepoc.write_dataset_to_file(test, test_file)  \n    deepoc.write_dataset_to_file(val, val_file)\n\n    # Configure DNN model to use Gradient Descent optimizer, 1 hidden layer with 150 nodes, learning rate of 0.001 and dropout rate of 0.5\n    classifier = DeepOCClassifier(workspace, 'GD', [150], 0.001, train_file, test_file, classes, 0.5)\n    # Train the model with 3000 epoch, validate every 10 epochs and batch size of 16\n    classifier.train_dll_model(3000, 10, 16)\n\n    # Validate the result:\n    for record in val:\n\t    model = record['model']\n\t    predict_result = classifier.predict(record)  \n\t    logger.info('Model %s: %s', model, predict_result)\n\nMore examples can be found in *tests* folder.\n\n### Classify model based on any ontology other than Gene Ontology\nTo make this library work with other kind of ontology, implement the [OntologyService](https://bitbucket.org/biomodels/deepoc/src/master/deepoc/ontology/ontology_service.py) according to your ontology and instantize your object at [https://bitbucket.org/biomodels/deepoc/src/master/deepoc/ontology/__init__.py](https://bitbucket.org/biomodels/deepoc/src/master/deepoc/ontology/__init__.py) \n\n## Developers\n\n-   [Vu Tu](https://bitbucket.org/vmtu)\n\n## Contact\n\n## Licensing\n\nBiological Model Classifier source code is distributed under the GNU Affero General Public License.  \nPlease read  [license.txt](LICENSE)  for information on the software availability and distribution.\n\n",
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