PyOpenMS
Skill Verifiziert AktivComplete mass spectrometry analysis platform. Use for proteomics workflows feature detection, peptide identification, protein quantification, and complex LC-MS/MS pipelines. Supports extensive file formats and algorithms. Best for proteomics, comprehensive MS data processing. For simple spectral comparison and metabolite ID use matchms.
To enable AI agents to perform complex mass spectrometry data analysis for proteomics and metabolomics research, including feature detection, peptide identification, and quantitative analysis.
Funktionen
- Complete mass spectrometry analysis platform
- Supports proteomics workflows and metabolomics
- Feature detection, peptide identification, protein quantification
- Handles extensive file formats (mzML, idXML, etc.)
- Integrates advanced algorithms and processing pipelines
Anwendungsfälle
- Processing and analyzing LC-MS/MS data for proteomics studies
- Performing untargeted metabolomics feature detection and identification
- Identifying peptides and proteins from raw spectral data
- Quantitative analysis of protein and metabolite abundance
Nicht-Ziele
- Simple spectral comparison or metabolite ID (use matchms)
- Acting as a generic data analysis tool outside of mass spectrometry
Workflow
- Load mass spectrometry data (mzML, mzXML, etc.)
- Process raw spectra (smoothing, filtering, peak picking)
- Detect features or identify peptides/proteins
- Link features across samples for quantification
- Annotate and export results (idXML, featureXML, consensusXML)
Installation
npx skills add K-Dense-AI/claude-scientific-skillsFührt das Vercel skills CLI (skills.sh) via npx aus — benötigt Node.js lokal und mindestens einen installierten skills-kompatiblen Agent (Claude Code, Cursor, Codex, …). Setzt voraus, dass das Repo dem agentskills.io-Format folgt.
Qualitätspunktzahl
VerifiziertVertrauenssignale
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