CATO Blog

AI data analysis and literature review, explained for researchers

CATO is an AI data analysis and literature review tool for biomedical researchers, built by NYRUS AI.

• CATO vs SPSS: a researcher's comparison

  How CATO, an AI data analysis tool for researchers, compares to IBM SPSS for statistical analysis, pricing, transparency, and ease of use.

• CATO vs GraphPad Prism: statistics and publication figures

  CATO and GraphPad Prism compared for biomedical statistics, publication-quality figures, file support, and price.

• CATO vs ChatGPT for research data analysis

  Why researchers use CATO instead of (or alongside) ChatGPT for statistics: real code execution on real datasets, verifiable citations, and reviewer-ready outputs.

• CATO vs Julius AI: specialized vs general AI data analysis

  CATO and Julius AI both analyze data conversationally. CATO is purpose-built for biomedical research, with domain toolkits, literature search, and reviewer-ready outputs.

• The best AI tools for biomedical research in 2026

  A practical guide to AI tools for biomedical researchers: data analysis, literature review, figures, and writing, including where CATO fits.

• What an AI literature review tool should actually do

  The checklist for AI literature review software: multi-database search, PICO extraction, verifiable citations, and export, with CATO as the worked example.

• Systematic review software with AI: from question to cited review

  How AI-assisted systematic reviews work in CATO: multi-database search, PICO extraction, synthesis, QA-checked citations, and Word export.

• No-code statistical analysis that still shows the code

  How researchers run rigorous statistics without programming, and why no-code should never mean no-transparency.

• AI data analysis for researchers: what it is and how it works

  A plain explanation of AI data analysis for research: upload a dataset, ask in plain language, get verifiable statistics, figures, and citations.

• Running Kaplan-Meier survival analysis with AI

  How to run a Kaplan-Meier survival analysis, log-rank test, and Cox model from a CSV in minutes using CATO, with the code exposed for review.

• RNA-seq differential expression analysis with AI

  From counts matrix to volcano plot with an AI analysis workspace: differential expression, enrichment, and publication figures with transparent code.

• How to open and analyze SPSS .sav files without SPSS

  Analyze SPSS .sav files without an SPSS license: upload to CATO, keep labels and types, and run the same statistics with transparent code.

• Publication-quality figures with an AI no-code editor

  How CATO generates journal-ready figures from real analyses and lets you restyle them without code: labels, palettes, versions, and SVG/PDF export.

• Is my research data safe with AI analysis tools?

  The security and privacy questions researchers should ask AI tools, and how CATO answers them: sandboxed execution, no training on your data, and data ownership.

• AI for clinical trial data analysis

  How clinical research teams use AI to go from raw trial exports to audited, cited, reviewer-ready figures and tables in minutes.

• Single-cell RNA-seq analysis with an AI workspace

  Load H5AD, Loom, or 10x matrices and run QC, clustering, annotation, and differential expression conversationally, with the code exposed.

• Literature watches: standing alerts for new papers in your field

  How CATO's literature watches monitor PubMed, preprints, trials, and patents for new work matching your saved searches.

• CATO pricing explained: Standard, Pro, Pay-as-you-go, and Labs

  What each CATO plan includes: Standard at $20/month, Pro at $100/month with systematic reviews, metered Pay-as-you-go, and CATO for Labs at $100/seat.

• AI statistics and reproducibility: why the code must be visible

  Reproducibility requires the exact code, assumptions, and data decisions behind every result. How transparent AI analysis addresses the crisis black-box tools created.

• One workspace for 50+ biomedical data formats

  The research data formats CATO reads natively: SPSS, SAS, Stata, FASTA, FASTQ, VCF, H5AD, DICOM, NIfTI, PDB, mzML, FCS, and more, with no conversion.

• How researchers use AI for analysis without learning to code

  A realistic picture of AI-assisted research for non-programmers: what plain-language analysis can do today, and where human judgment stays essential.

Try CATO at cato.nyrus.ai or learn more at nyrus.ai/cato.