Source Data for AI-Discovered Protein Fragment Regulators

Source data associated with the research article 'AI-discovered protein fragments as generalizable regulators of biomolecular condensates' by Savinov et al. (2026). The data was published on figshare by author Andrew Savinov on May 8, 2026. It supports the findings of the bioRxiv preprint.

Use Cases

• Training AI models for protein fragment discovery based on the described research.
• Validating the regulatory effects of AI-discovered fragments on biomolecular condensates.
• Reproducing the analysis from the associated bioRxiv article.
• Benchmarking new protein design algorithms against the published results.

Strengths

• Data is directly linked to a peer-reviewed scientific preprint (bioRxiv 2026).
• Associated code for the FragFold method is publicly available on GitHub.
• Published under a permissive CC-BY-4.0 license for reuse.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and file formats are unknown, which may limit suitability assessment.

Provenance

Source

figshare, associated with research from Savinov and Sadasivan et al.

Collection Method

Likely generated via computational AI methods (FragFold) as described in the linked article.

Time Range

Associated with research published in 2026.

Freshness

Last updated 2026-05-08 19:17:35.

Geography

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