QSAR-TID-10472

A resource from the QSAR-TID series, which is a collection of datasets for quantitative structure-activity relationship modeling. No specific details on rows, columns, or content are available in the input. The dataset originates from the OpenML platform.

Use Cases

• QSAR modeling for predicting biological activity endpoints, using molecular descriptors from the TID series.
• Benchmarking machine learning algorithms on standardized QSAR datasets from the TID collection.
• Feature selection and analysis on molecular descriptor data typical of QSAR-TID datasets.

Strengths

• Part of the established QSAR-TID series, a known collection for cheminformatics benchmarking.
• Hosted on OpenML, which provides a standardized platform for dataset access and versioning.

Limitations

• No information is provided on the number of rows, columns, or sample data, preventing assessment of scale and content.
• The absence of column names, descriptions, and sample data makes it impossible to verify data structure or suitability for specific tasks.
• Critical metadata such as license, author, and last update date are unknown, which impacts usability and trust.

Provenance

Source

OpenML