tooluniverse▌

When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.

Retrieve gene expression experiments and multi-omics datasets with disambiguation and quality assessment.

Systematically assess clinical trial feasibility by analyzing 6 research dimensions. Produces comprehensive feasibility reports with quantitative enrollment projections, endpoint recommendations, and regulatory pathway analysis.

Comprehensive drug investigation using 50+ ToolUniverse tools across chemical databases, clinical trials, adverse events, pharmacogenomics, and literature.

Provide actionable treatment recommendations for cancer patients based on their molecular profile using CIViC, ClinVar, OpenTargets, ClinicalTrials.gov, and structure-based analysis.

Retrieve DNA, RNA, and protein sequences from NCBI and ENA with automatic gene disambiguation and cross-database handling. \n \n Searches NCBI Nucleotide by organism, gene name, strain, and sequence type; automatically disambiguates genes across species and resolves accession prefixes to the correct database \n Handles RefSeq (NC_, NM_, NP_) and GenBank accessions with intelligent fallback between NCBI and ENA; never attempts ENA queries on RefSeq-only accessions \n Returns detailed sequence pro