Raw Experimental Data for RELB-Driven Oncogenic and Inflammatory Network Analysis

Raw experimental data supporting the research 'Explainable machine learning reveals a RELB-driven oncogenic and inflammatory network orchestrating.' The dataset, authored by jiaying Dai, is a 188.9 MB ZIP file published on figshare under a CC-BY-4.0 license and last updated on April 23, 2026.

Use Cases

• Training explainable ML models to identify oncogenic drivers based on experimental data.
• Analyzing the role of the RELB transcription factor in inflammatory networks.
• Validating gene expression patterns associated with specific oncogenic pathways.

Strengths

• Dataset is 188.9 MB, indicating a medium-scale collection of raw experimental data.
• Published under a permissive CC-BY-4.0 license, allowing for broad reuse and distribution.

Limitations

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

Provenance

Source

jiaying Dai via figshare

Collection Method

Raw experimental data, likely from laboratory experiments.

Time Range

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Freshness

Last updated 2026-04-23 09:50:01; freshness should be verified.

Geography

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