Merge pull request #2048 from miaecle/master

                         data_dir=None,

                         save_dir=None,

                         **kwargs):

  """Load bace datasets."""

  """ Load BACE dataset, regression labels

  The BACE dataset provides quantitative IC50 and qualitative (binary label)

  binding results for a set of inhibitors of human beta-secretase 1 (BACE-1).

  All data are experimental values reported in scientific literature over the

  past decade, some with detailed crystal structures available. A collection

  of 1522 compounds is provided, along with the regression labels of IC50.

  Scaffold splitting is recommended for this dataset.

  The raw data csv file contains columns below:

  - "mol" - SMILES representation of the molecular structure

  - "pIC50" - Negative log of the IC50 binding affinity

  - "class" - Binary labels for inhibitor

  References

  ----------

  .. [1] Subramanian, Govindan, et al. "Computational modeling of β-secretase 1

     (BACE-1) inhibitors using ligand based approaches." Journal of chemical

     information and modeling 56.10 (2016): 1936-1949.

  """

  # Featurize bace dataset

  logger.info("About to featurize bace dataset.")

  if data_dir is None:

                             data_dir=None,

                             save_dir=None,

                             **kwargs):

  """Load bace datasets."""

  """ Load BACE dataset, classification labels

  BACE dataset with classification labels ("class").

  """

  # Featurize bace dataset

  logger.info("About to featurize bace dataset.")

  if data_dir is None:

              data_dir=None,

              save_dir=None,

              **kwargs):

  """Load blood-brain barrier penetration datasets """

  """Load BBBP dataset

  The blood-brain barrier penetration (BBBP) dataset is designed for the

  modeling and prediction of barrier permeability. As a membrane separating

  circulating blood and brain extracellular fluid, the blood-brain barrier

  blocks most drugs, hormones and neurotransmitters. Thus penetration of the

  barrier forms a long-standing issue in development of drugs targeting

  central nervous system.

  This dataset includes binary labels for over 2000 compounds on their

  permeability properties.

  Scaffold splitting is recommended for this dataset.

  The raw data csv file contains columns below:

  - "name" - Name of the compound

  - "smiles" - SMILES representation of the molecular structure

  - "p_np" - Binary labels for penetration/non-penetration

  References

  ----------

  .. [1] Martins, Ines Filipa, et al. "A Bayesian approach to in silico

     blood-brain barrier penetration modeling." Journal of chemical

     information and modeling 52.6 (2012): 1686-1697.

  """

  # Featurize bbb dataset

  logger.info("About to featurize bbbp dataset.")

  if data_dir is None:

                 data_dir=None,

                 save_dir=None,

                 **kwargs):

  """Load clintox datasets.

  """Load ClinTox dataset

  The ClinTox dataset compares drugs approved by the FDA and

  drugs that have failed clinical trials for toxicity reasons.

  The dataset includes two classification tasks for 1491 drug

  compounds with known chemical structures: (1) clinical trial

  toxicity (or absence of toxicity) and (2) FDA approval status.

  compounds with known chemical structures: 

  #. clinical trial toxicity (or absence of toxicity)

  #. FDA approval status.

  List of FDA-approved drugs are compiled from the SWEETLEAD

  database, and list of drugs that failed clinical trials for

  toxicity reasons are compiled from the Aggregate Analysis of

  ClinicalTrials.gov(AACT) database.

  The data file contains a csv table, in which columns below are used:

  "smiles" - SMILES representation of the molecular structure

  "FDA_APPROVED" - FDA approval status

  "CT_TOX" - Clinical trial results

  Random splitting is recommended for this dataset.

  The raw data csv file contains columns below:

  - "smiles" - SMILES representation of the molecular structure

  - "FDA_APPROVED" - FDA approval status

  - "CT_TOX" - Clinical trial results

  References

  ----------

  .. [1] Gayvert, Kaitlyn M., Neel S. Madhukar, and Olivier Elemento.

     "A data-driven approach to predicting successes and failures of clinical trials."

     "A data-driven approach to predicting successes and failures of clinical

     trials."

     Cell chemical biology 23.10 (2016): 1294-1301.

  .. [2] Artemov, Artem V., et al. "Integrated deep learned transcriptomic and

     structure-based predictor of clinical trials outcomes." bioRxiv (2016): 095653.

  .. [3] Novick, Paul A., et al. "SWEETLEAD: an in silico database of approved drugs,

     regulated chemicals, and herbal isolates for computer-aided drug discovery."

     PloS one 8.11 (2013): e79568.

     structure-based predictor of clinical trials outcomes." bioRxiv (2016): 

     095653.

  .. [3] Novick, Paul A., et al. "SWEETLEAD: an in silico database of approved

     drugs, regulated chemicals, and herbal isolates for computer-aided drug 

     discovery." PloS one 8.11 (2013): e79568.

  .. [4] Aggregate Analysis of ClincalTrials.gov (AACT) Database.

     https://www.ctti-clinicaltrials.org/aact-database

  """

                 data_dir=None,

                 save_dir=None,

                 **kwargs):

  """Load delaney datasets.

  """Load delaney dataset

  The Delaney datasets are extracted from the following paper

  The Delaney(ESOL) dataset a regression dataset containing structures and 

  water solubility data for 1128 compounds. The dataset is widely used to 

  validate machine learning models on estimating solubility directly from 

  molecular structures (as encoded in SMILES strings).

  Delaney, John S. "ESOL: estimating aqueous solubility directly from molecular structure." Journal of chemical information and computer sciences 44.3 (2004): 1000-1005.

  Random splitting is recommended for this dataset.

  This dataset contains 2874 measured aqueous solubility

  values. The source dataset is available in the supplemental

  material of the original paper.

  The raw data csv file contains columns below:

  - "Compound ID" - Name of the compound

  - "smiles" - SMILES representation of the molecular structure

  - "measured log solubility in mols per litre" - Log-scale water solubility 

    of the compound, used as label

  References

  ----------

  .. [1] Delaney, John S. "ESOL: estimating aqueous solubility directly from 

     molecular structure." Journal of chemical information and computer 

     sciences 44.3 (2004): 1000-1005.

  """

  # Featurize Delaney dataset

  logger.info("About to featurize Delaney dataset.")

             data_dir=None,

             save_dir=None,

             **kwargs):

  """Load hiv datasets. Does not do train/test split

  """Load HIV dataset

  The HIV dataset was introduced by the Drug Therapeutics

  Program (DTP) AIDS Antiviral Screen, which tested the ability

  latter two labels, making it a classification task between

  inactive (CI) and active (CA and CM).

  The data file contains a csv table, in which columns below are used:

  Scaffold splitting is recommended for this dataset.

  The raw data csv file contains columns below:

  - "smiles": SMILES representation of the molecular structure

  - "activity": Three-class labels for screening results: CI/CM/CA

  - "HIV_active": Binary labels for screening results: 1 (CA/CM) and 0 (CI)

  References

  ----------

  .. [1] AIDS Antiviral Screen Data. https://wiki.nci.nih.gov/display/NCIDTPdata/AIDS+Antiviral+Screen+Data

  .. [1] AIDS Antiviral Screen Data. 

     https://wiki.nci.nih.gov/display/NCIDTPdata/AIDS+Antiviral+Screen+Data

  """

  # Featurize hiv dataset

  logger.info("About to featurize hiv dataset.")