Frequently Asked Questions

Motif compresses months of manual biomarker literature review into structured, citable evidence. You ask a research question in plain English and receive outputs that organize relevant biomarker associations for faster decision-making.

Every association links back to its original source with a PMID citation and supporting evidence, so you can verify the finding directly in the literature. Separately, the biomedical entities Motif extracts (genes, proteins, diseases, drugs) are cross-referenced against 50+ specialized databases including CIViC, ClinVar, gnomAD, Reactome, and FDA resources to ensure they are correctly identified. Motif does not validate or cross-check the associations themselves; that is what the cited literature is for.

Full queries run search, extraction, cross-referencing, gap evaluation, and synthesis, with total time varying by scope and configuration. Work that takes weeks of manual reading and cross-checking is accelerated substantially.

You get four things: (1) Structured biomarker data, organized lists of biomarker-disease-drug relationships with citations, (2) A visual knowledge graph showing connections you'd never find in a spreadsheet, (3) Follow-up Q&A on your evidence so you can ask questions in plain English, and (4) Export-ready documentation including PDF reports, Excel data, and slides with full citations.

Yes. Motif exports grant-ready evidence with proper citations in standard formats (APA, Vancouver, etc.). Every finding includes evidence tables, cited literature reviews, and methodology descriptions. Exports are designed to drop into grant proposals, publications, or research reports. You write the proposal; Motif supplies the cited evidence.

Motif exports cited evidence you can use in background and significance sections: literature reviews, evidence tables, and methodology descriptions with proper citations. Motif does not write your grant proposal; it supplies the structured, source-linked evidence you need to draft it faster.

Every biomarker result in Motif includes direct citations to the original research papers with PMIDs. You can export these citations in standard formats (APA, Vancouver, etc.) and use them directly in your publications. Motif doesn't generate new claims. It organizes and cross-references existing research, so you cite the original sources, not Motif.

You can upload articles directly into Motif's paper library. Motif will extract findings from them, pull associations into your knowledge graph, and treat them the same as any search result, complete with provenance and citations. Your graph grows with your research, not just ours.

Type your research question in plain English, review the structured outputs, explore the knowledge graph, ask follow-ups, and export your findings. Join the waitlist for early access.

Manual PubMed searches often require weeks of reading, cross-referencing, and synthesis. Motif automates much of this work and returns structured, source-linked outputs as the pipeline completes, without replacing careful review of critical findings.

Motif is built for teams navigating biomarker evidence in precision oncology, translational research, and companion diagnostic development: bioinformaticians, translational scientists, and clinical development teams working on treatment response and patient selection. It also supports broader biomarker-focused work across oncology, rare disease, cardiovascular, neurological, autoimmune, metabolic, and infectious disease contexts.

Yes. Motif helps surface resistance-related biomarker evidence and associated context so teams can prioritize follow-up analysis.

Single-database tools focus on one source. Motif combines multi-source evidence retrieval with natural-language workflows and structured outputs designed for faster review.

Motif uses a GRADE-adapted formula that produces a score from 0 to 1 and places each association into one of four tiers: High (0.85-1.00), Moderate (0.60-0.84), Low (0.35-0.59), or Very Low (below 0.35). Scoring works in three steps. First, a starting level is assigned based on study design and the type of claim being made: RCTs start at High for therapeutic claims, prospective cohorts start at High for diagnostic or prognostic claims, and preclinical studies start at Very Low. Second, the score is adjusted up or down based on methodological concerns such as imprecision or indirectness, and large effect sizes can raise the score by one or two levels. Third, within each tier the final position is refined by sample size and, for therapeutic and predictive claims, p-value strength. Associations without sufficient metadata to compute a score are marked Unknown.

Yes. Motif is useful for rare disease research where evidence is often fragmented and difficult to synthesize manually.

Scientific literature often contains contradictory findings. Motif presents all perspectives with their supporting evidence, weights results by study quality and recency, highlights consensus vs. contested claims, and shows how understanding has evolved over time. This transparency helps you navigate controversies and form evidence-based conclusions.

Yes. Motif includes enterprise features like team collaboration, enterprise security controls, and professional export formats. Whether you're a solo researcher or part of a large pharma team, Motif scales to your needs.

Motif has limitations we believe you should know about. Deliberately excluded: Conference abstracts and non-English publications are not indexed. Abstracts lack the methodology detail needed for reliable extraction, and non-English coverage is not yet at a quality we're comfortable with. Coverage gaps: Papers not yet indexed in PubMed won't appear in Motif. That's a PubMed lag, not a Motif one. Preprints can be included via settings if you want broader coverage. AI extraction errors: AI may occasionally misclassify relationships or miss nuanced context. Always verify critical findings by reading the original papers. Not a replacement for expert review: Motif accelerates research but doesn't replace domain expertise. Database lag: External databases update on their own schedules, so very recent findings may not be immediately reflected. For full details, see the Methodology & Limitations section on our Features page.