Discover Biomedical Knowledge Beyond Literature Search
Powered by Insilicom's large-scale biomedical knowledge graph, IExplore enables researchers to search biomedical knowledge at the entity-and-relationship level, explore interactive knowledge graphs, inspect supporting evidence, and generate explainable hypotheses.
Navigate connections. Inspect evidence. Follow reasoning paths.
A researcher-facing platform for biomedical discovery
IExplore transforms Insilicom's large-scale biomedical knowledge graph—integrating structured knowledge from PubMed literature, public databases, and genomics analyses—into an interactive research environment for precise retrieval, evidence synthesis, mechanism exploration, and hypothesis generation.
Relationship-level search
Search for specific relationships among diseases, genes, proteins, drugs, compounds, variants, pathways, biological processes, anatomical structures, and other biomedical entities.
Interactive exploration
Navigate interactive biomedical knowledge graphs to explore direct and indirect relationships among diseases, genes, proteins, drugs, pathways, variants, and other biomedical entities.
Evidence-backed relationships
Every discovered relationship links directly to supporting sentences and source publications, enabling transparent inspection and verification of the underlying evidence.
Move beyond conventional literature search
Traditional search engines return documents. IExplore helps researchers retrieve, connect, and interpret biomedical knowledge.
Precision search controls
Refine queries by entity type, relationship type, causal direction, biological context, publication date, and other criteria to focus the evidence most relevant to your research question.
Traditional search
- Returns lists of papers based on keywords
- Requires manual extraction of entities and relationships
- Makes cross-paper synthesis time-consuming
- Provides limited support for mechanism exploration
- Rarely exposes interpretable reasoning paths
IExplore
- Searches at the entity-and-relationship level
- Filters by relationship type, direction, context, and date
- Displays results as navigable knowledge graphs
- Links each relationship to supporting evidence
- Surfaces explainable direct and indirect connections
Reveal plausible paths when no direct link is known
IExplore uses Insilicom's Probabilistic Semantic Reasoning framework to identify and rank plausible indirect relationships through intermediate genes, proteins, pathways, or biological processes.
Rather than returning an unexplained prediction, the platform exposes the reasoning path and its supporting evidence for expert review.
Each step can be examined through the evidence supporting the relationship, making generated hypotheses transparent and testable.
Answer complex biomedical questions
Use direct search or follow connected evidence to investigate questions such as:
Disease biology
Which genes are associated with or causally contribute to a disease?
Drug-target relationships
Which compounds activate or inhibit a particular protein?
Drug-disease evidence
Which diseases are treated by, associated with, or potentially caused by a drug?
Safety mechanisms
Which biological mechanisms may connect a drug with an adverse event?
Indirect connections
Which intermediate genes, proteins, or pathways may connect two entities?
Research gaps
Where is evidence sparse, conflicting, or missing across the current knowledge network?
Applications across biomedical research
IExplore supports a broad range of discovery and evidence-synthesis workflows through a cloud-based platform optimized for sophisticated, real-time exploration of large-scale biomedical knowledge.
Explore biomedical knowledge with greater precision
See how IExplore can help your research team connect evidence, understand biological mechanisms, and generate interpretable hypotheses.