Knowledge Base
Various data available in your network visualization
The knowledge base provides the node and edge properties of network visualization and analysis, based on the Reference Genome data and Protein-Protein Interaction (PPI) network data.
We also have different kinds of data available on the left panel of network visualization page, which allows you to change the network property based on personal needs. The data behind each feature is divided into 2 different types — disease-dependent and disease independent.
Data types are transformed to defined representations, so that they can be handled consistently and displayed intuitively by the frontend.
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Disease-dependent data varies with different diseases, including LogFC (Differential expression in Log2 fold change), GDA(Gene Disease Association score) and Genetics (Odd ratio or Beta-values from population studies).
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Disease-independent data DO NOT vary with different diseases, including Target Prioritization Factors (Rank and prioritize biological targets), Pathway (Pathway membership from KEGG and Reactome), Druggability (Derived from DrugnomeAI), Tissue Enrichment (Tissue-specific expression from GTEX and HPA).
Knowledge Base Summary
| Data type | Representation | Experiment types | Sources |
|---|---|---|---|
| LogFC | [-Inf, +Inf] | RNAseq, Proteomics | Verge, AD (Mayo, ROSMAP, MSBB) |
| GDA | [0, 1] | AI, Meta-scores | Open Targets (v25.03) |
| Genetics | [-1, 1] | GWAS w/ eQTL (OR/Beta), GeneBurden (OR/Beta) | Open Targets Genetics |
| Target Prioritization Factors | [-1, 1] | Open Targets (v24.04) | |
| Pathway | Binary | Curation | KEGG (release 112), Reactome (v90) |
| Druggability | [0, 1] | AI, Meta-scores | DrugnomeAI |
| Tissue Enrichment | [0, +Inf] | single cell RNAseq & single cell databases | GTEx, HPA (v23.0) |