0xreversed/with.ai
AppsWorksSource available
Target: MetaboliteDetector

DcBexter/MetaboliteDetector

by DcBexter Repository0 views
Platform
Windows, Linux, macOS
Outcome
Works
MetaboliteDetector: A Rust-based rewrite of MetaboliteDetector 3.3 for GC/MS metabolomics data analysis.
Image: Source: raw.githubusercontent.com

Evidence at a glance

Based on the linked sources. The author's reported result and independent confirmation are separate checks.

AI involvement
Model not reported. Tools: Rust, Cargo. The writeup below describes the work attributed to AI.
Reported result
Works. This is the directory's source-based outcome classification.
Independent confirmation
Not reported.
Human work and limitations
The project uses automated dependency management tools like Renovate and Dependabot, as evidenced by commit logs, but these tools do not contribute to the core metabolomics analysis logic.

Original sources

What was done

MetaboliteDetector is a Rust rewrite of the 3.3 version designed for deconvolution, identification, and quantification of GC/MS metabolomics data, running natively on Windows and Linux without R or Qt dependencies.

MetaboliteDetector is a software application designed for the deconvolution, identification, and quantification of GC/MS metabolomics data. The project serves as a Rust-based rewrite of the legacy MetaboliteDetector 3.3, enabling native execution on Windows and Linux—with macOS support available from source—without requiring R or Qt installations. The README documents that the application maintains compatibility with legacy file formats, allowing it to read files generated by version 3.3. The developer reports that the project includes reverse-engineered documentation detailing the functionality of the original 3.3 version. The application features an automated update mechanism that verifies releases against SHA-256 checksums. While the software provides a graphical user interface for analysis, it also includes md-cli for headless batch quantification. Further technical details, including architecture and performance rules, are maintained in the project documentation at https://raw.githubusercontent.com/dcbexter/metabolitedetector/HEAD/README.md.