Methodology & Limitations
Transparency about how Motif works, what it can do, and where its limitations lie.
Query Processing Time
When we say queries complete in "~6 minutes," this is based on average completion times observed during internal testing with typical biomarker research queries.
What this measures: Time from query submission to delivery of structured results, including literature search, biomarker extraction, database cross-referencing, and result ranking.
Factors affecting time: Query complexity, number of relevant papers, database response times, and current system load. Simple queries may complete faster; complex queries spanning multiple diseases or rare conditions may take longer.
Database Coverage (50+ Sources)
Motif integrates data from 50+ databases across seven categories. The carousel on our homepage shows highlights; here is the complete list:
literature Databases (3)
clinical Databases (7)
genes Databases (5)
genomic variants Databases (3)
proteins Databases (3)
pathways Databases (3)
immunological Databases (7)
metabolites Databases (4)
glycans Databases (2)
ontologies Databases (3)
chemical Databases (1)
regulatory Databases (2)
rna Databases (1)
epigenetic Databases (1)
ptm Databases (1)
gene signatures Databases (1)
cellular Databases (1)
taxonomy Databases (2)
Database availability and update frequency vary by source. Some databases update daily, others weekly or monthly.
AI Technology
Motif uses large language models to extract biomarker-disease-drug relationships from scientific literature. Our approach combines:
- Named entity recognition for biomarkers, diseases, drugs, and genes
- Relationship extraction to identify associations between entities
- Cross-referencing against curated databases to validate extracted relationships
- Confidence scoring based on evidence strength and source quality
All AI-extracted results include citations to original sources. We do not generate novel claims; we organize and cross-reference existing published research.
Query Optimization
For each research question, Motif generates 3-5 complementary search queries to maximize coverage:
- MeSH-optimized queries - Use standardized Medical Subject Headings for precise matching
- Free-text queries - Catch recent articles not yet indexed with MeSH terms (typically 3-6 months ahead)
- Synonym-expanded queries - Include alternative gene names, disease synonyms, and drug aliases
Biomarker Recognition (50+ Types)
Motif recognizes 50+ biomarker entity types across 15 categories:
Relationship Types (25+)
Motif extracts 25+ relationship types between biomarkers and conditions:
Limitations
Like all AI research tools, Motif has limitations. We believe honest disclosure helps researchers use our tool appropriately.
Coverage Gaps
Motif searches indexed databases and may miss preprints, conference abstracts, non-English publications, or very recent papers not yet indexed. Niche research areas may have limited coverage.
AI Extraction Errors
AI may occasionally misclassify relationships, miss nuanced context, or extract incorrect associations. Always verify critical findings by reading the original papers.
Not a Replacement for Expert Review
Motif accelerates literature review but does not replace domain expertise. Researchers should apply their judgment to interpret results, especially for clinical decisions.
Database Lag
External databases update on their own schedules. Very recent publications or database updates may not be immediately reflected in Motif results.
Confidence Scores Are Not Predictions
Our confidence scores reflect evidence strength from available literature, not clinical validity predictions. A high confidence score means strong literature support, not guaranteed clinical utility.
Best Practices
To get the most accurate results from Motif:
- Verify key findings by reading original source papers
- Use confidence scores to prioritize which results to review first
- Cross-check critical findings against multiple sources
- Apply domain expertise to interpret results in context
- Report any errors or unexpected results to help us improve
Questions?
If you have questions about our methodology or want to report an issue, please contact us.