Grounded in your evidence
Every response draws on EV evidence records, ranked entities, and source-backed provenance from the active result — nothing is fabricated or inferred from outside your search.
Search any miRNA, mRNA, or protein — EVd3x maps it across EV evidence, pathways, disease, and cell context in one workspace.
EVd3x moves you from a list of cargo hits to testable biological insight in four steps — each grounded in EV-specific evidence, not generic enrichment.
Quantify EV-supported evidence for every molecule — direct database records, inferred associations, and source-level provenance.
Connect cargo to pathways, diseases, cell types, and interaction networks from the active graph — not from a separate tool.
Pivot across analysis views, adjust filters, and reshape top-N windows to stress-test hypotheses before committing to bench work.
Export prioritized candidates with full evidence tables and graph context — structured for targeted validation planning.
The assistant reasons from your active graph, summary state, and analysis tabs — never from outside the loaded context. It routes you to the right surface and explains what it finds.
Every response draws on EV evidence records, ranked entities, and source-backed provenance from the active result — nothing is fabricated or inferred from outside your search.
Ask a question in natural language and the assistant opens the relevant module — pathway, disease, cell context, L-R, or PPI — with the right filters applied.
It reshapes top-N lists, adjusts subsets, and structures exports so your hypotheses are experiment-ready — all within browser-safe compute limits.
Evidence, pathway, interaction, and disease layers unified in a single graph-native workspace.
Every module operates on your active graph and summary state. Switch tabs freely — the loaded context follows you.
See which databases support each molecule, drill into provenance rows, filter by sample type, and trace back to EV-TRACK-linked studies.
Run enrichment across integrated pathway sources and connect your cargo to biological programs — not isolated gene lists.
Surface direct and predicted disease associations with publication-backed evidence and ranked system-level summaries.
Identify the most relevant cell types for your cargo and use cell-level context as the starting point for communication analysis.
Project ligand-receptor pairs from your active system using relevance-ranked starter sets designed to run efficiently in the browser.
Expand proteins into STRING interaction neighborhoods, inspect context, and export figures or data tables without leaving your analysis.
Canonical identifiers, database provenance, and publication-linked records stay attached across summaries, tabs, and exports — so nothing loses its origin.
Canonical IDs link molecules across pathway, interaction, and disease layers in a single connected graph.
Every analysis tab preserves source-level rows with publication and database provenance intact.
Display caps keep views responsive; exports include the full candidate set when available.
Ranking cell types...
Review selected source cells, then click Update Communication to apply changes.
Running analysis...
Analyzing ligands & receptors...
Running enrichment analysis...
Analyzing disease associations...