Random Promoter DREAM Challenge 2022: Synthetic Yeast Promoter Sequences

HuggingFaceBio repackaged the Random Promoter DREAM Challenge 2022 files from Zenodo for use with datasets. The dataset contains synthetic yeast promoter sequences for a sequence-to-expression regression task. It includes supervised training, validation, and test splits.

Use Cases

• Train sequence-to-expression regression models based on synthetic promoter sequences.
• Benchmark machine learning models for genomics tasks based on the DREAM Challenge framework.
• Validate gene expression prediction algorithms based on labeled designed test promoters.

Strengths

• Dataset is structured for a canonical supervised learning task with defined train, validation, and test splits.
• Data originates from a recognized DREAM Challenge, suggesting a benchmark standard.

Limitations

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

Provenance

Source

Zenodo record 10633252

Collection Method

Repackaged processed files from the Random Promoter DREAM Challenge 2022.

Time Range

2022

Freshness

Last updated 2026-05-18 10:50:23; freshness should be verified.