Data Sheet 7_Geometric multidimensional representation of omic signatures.zip

Higor Almeida Cordeiro Nogueira's dataset provides geometric representations of multi-omic signatures for metabolic regulatory circuitries. It contains data for 24,796 circuitries reconstructed across 32 TCGA cancer types, embedded in an 18-dimensional latent space. The dataset was last updated on 2026-04-17 and is available under a CC-BY-4.0 license.

Use Cases

• Comparing multi-omic biomarkers based on geometric descriptors like barycenter distance and volume.
• Stratifying metabolic pathways and superfamilies using geometric phenotypes.
• Analyzing concordance and divergence in metabolic regulatory systems across cancer types.
• De-redundancy of multi-omic signatures using a geometric framework.

Strengths

• Contains data for 24,796 metabolic regulatory circuitries.
• Covers 32 distinct TCGA cancer types.
• Data is embedded in a defined 18-dimensional latent space.
• Includes derived geometric descriptors like volume and anisotropy.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the primary data table is unknown, which may limit suitability assessment.
• The dataset is small (73.0 KB), suggesting it contains processed descriptors rather than raw omics data.

Provenance

Source

figshare, author Higor Almeida Cordeiro Nogueira

Collection Method

Geometric framework applied to reconstructed metabolic circuitries from TCGA data.

Freshness

Last updated 2026-04-17 05:22:14; freshness should be verified.