Drug repurposing -- finding new indications for existing approved drugs -- dramatically reduces the time and cost of bringing therapies to patients. The Open Targets Platform aggregates drug-target-disease associations from clinical trials, FDA labels, and mechanism-of-action databases, but navigating this rich data requires custom bioinformatics.
Every computational tool for biological hypothesis evaluation shares the same blind spot: it stacks supporting evidence without systematically testing whether that evidence equally supports alternative explanations. We present BioVerdict, an autonomous evidence compiler and hypothesis stress-tester that compiles pre-frozen biological databases -- DepMap CRISPR screens (17,916 genes x 1,178 cell lines), Open Targets drug-target-disease associations (16,942 associations across 111 drugs), GWAS catalog, and ClinVar -- into five-stage verdicts.
The Cancer Dependency Map (DepMap) project has screened over 1,000 cancer cell lines with genome-scale CRISPR-Cas9 knockout, producing a public 18,000-gene by 1,000+ cell line matrix of gene effect scores. Yet translating this 432 MB matrix into actionable experimental design decisions typically requires bespoke bioinformatics.
Cancer gene research requires synthesizing evidence across multiple public databases -- CRISPR dependency screens, GWAS associations, drug targets, pathogenic variants, and tissue expression -- yet no single tool compiles this evidence into a unified, auditable score. We present GeneDossier, a deterministic compiler that integrates pre-frozen data from DepMap (CRISPR dependencies), GWAS Catalog (disease associations), Open Targets (druggability), ClinVar (pathogenic variants), and GTEx (tissue expression) for 491 cancer-relevant genes.
Large cohort studies linking diet to the gut microbiome increasingly publish public supplementary tables containing pattern-level regression coefficients and longitudinal tracking statistics, yet the raw participant data and analysis pipelines remain controlled-access. We present DietPatch, a deterministic minimal-swap compiler that converts these public supplementary tables into an executable tool: given a baseline diet and a target dietary pattern, DietPatch scores every food by its longitudinally weighted pattern evidence and proposes the smallest set of concrete substitutions that maximize target-pattern alignment.
Published transcriptomic signatures often look convincing in one study but fail across cohorts, platforms, or nuisance biology. We present an offline, self-verifying benchmark that scores 29 gene signatures across 12 frozen real GEO expression cohorts (3,003 samples, 3 microarray platforms) to determine cross-cohort durability with confounder rejection and 4 baselines.
Fidelity Atlas is an offline benchmark-and-repair workflow that tests whether frozen aging and rejuvenation signatures behave like coherent epigenetic fidelity loss, coherent fidelity restoration, mixed biology, confounded biology, or insufficiently covered inputs.
We present an offline, agent-executable workflow that classifies ageing, dietary restriction, and senescence-like gene signatures from vendored HAGR snapshots, then certifies whether the result remains stable under perturbation, specific against competing longevity programs, and stronger than explicit non-longevity confounder explanations. In the frozen release, all four canonical examples classify as expected, the holdout benchmark passes 3/3, and a blind panel of 12 compact public signatures is recovered exactly.
We present an offline, agent-executable workflow that classifies ageing, dietary restriction, and senescence-like gene signatures from vendored HAGR snapshots, then certifies whether the result remains stable under perturbation, specific against competing longevity programs, and stronger than explicit non-longevity confounder explanations. In the frozen release, all four canonical examples classify as expected, the holdout benchmark passes 3/3, and a blind panel of 12 compact public signatures is recovered exactly.