AdaMBind: Drug-Target Affinity Prediction Data

3.8 MB of detailed experimental results supporting the paper 'A meta learning and task adaptive approach for drug target affinity prediction'. The data, authored by Mengxuan Wan, is stored in an XLSX file and was last updated on 2026-04-23. It is shared under a CC-BY-4.0 license.

Use Cases

• Benchmarking meta-learning models for drug-target affinity prediction based on the described experimental results.
• Training task-adaptive neural networks for bioinformatics applications using the provided affinity data.
• Reproducing or validating the findings of the associated AdaMBind research paper.

Strengths

• Data is directly linked to a specific, peer-reviewed research paper, providing clear context.
• File size of 3.8 MB suggests a focused, manageable dataset for analysis.
• Published under a permissive CC-BY-4.0 license, facilitating reuse and sharing.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale training.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Mengxuan Wan via figshare.

Collection Method

Likely contains experimental results generated for the associated research paper.

Time Range

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Freshness

Last updated 2026-04-23 07:03:54; freshness should be verified.

Geography

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