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Update SKILL.md files to add double quotation marks for all skills, ensuring clarity and consistency across all entries.

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Haoxuan "Orion" Li
2025-10-20 20:51:50 -07:00
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scientific-packages/pyopenms/SKILL.md
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---
name: pyopenms
description: Toolkit for mass spectrometry data analysis with pyOpenMS, supporting proteomics and metabolomics workflows including LC-MS/MS data processing, peptide identification, feature detection, quantification, and chemical calculations. Use this skill when: (1) Working with mass spectrometry file formats (mzML, mzXML, FASTA, mzTab, mzIdentML, TraML, pepXML/protXML) and need to read, write, or convert between formats; (2) Processing raw LC-MS/MS data including spectral smoothing, peak picking, noise filtering, and signal processing; (3) Performing proteomics workflows such as peptide digestion simulation, theoretical fragmentation, modification analysis, and protein identification post-processing; (4) Conducting metabolomics analysis including feature detection, adduct annotation, isotope pattern matching, and small molecule identification; (5) Implementing quantitative proteomics pipelines with feature detection, alignment across samples, and statistical analysis; (6) Calculating chemical properties including molecular formulas, isotopic distributions, amino acid properties, and peptide masses; (7) Integrating with search engines (Comet, Mascot, MSGF+) and post-processing tools (Percolator, MSstats); (8) Building custom MS data analysis workflows that require low-level access to spectra, chromatograms, and peak data; (9) Performing quality control on MS data including TIC/BPC calculation, retention time analysis, and data validation; (10) When you need Python-based alternatives to vendor software for MS data processing and analysis.
description: "Toolkit for mass spectrometry data analysis with pyOpenMS, supporting proteomics and metabolomics workflows including LC-MS/MS data processing, peptide identification, feature detection, quantification, and chemical calculations. Use this skill when: (1) Working with mass spectrometry file formats (mzML, mzXML, FASTA, mzTab, mzIdentML, TraML, pepXML/protXML) and need to read, write, or convert between formats; (2) Processing raw LC-MS/MS data including spectral smoothing, peak picking, noise filtering, and signal processing; (3) Performing proteomics workflows such as peptide digestion simulation, theoretical fragmentation, modification analysis, and protein identification post-processing; (4) Conducting metabolomics analysis including feature detection, adduct annotation, isotope pattern matching, and small molecule identification; (5) Implementing quantitative proteomics pipelines with feature detection, alignment across samples, and statistical analysis; (6) Calculating chemical properties including molecular formulas, isotopic distributions, amino acid properties, and peptide masses; (7) Integrating with search engines (Comet, Mascot, MSGF+) and post-processing tools (Percolator, MSstats); (8) Building custom MS data analysis workflows that require low-level access to spectra, chromatograms, and peak data; (9) Performing quality control on MS data including TIC/BPC calculation, retention time analysis, and data validation; (10) When you need Python-based alternatives to vendor software for MS data processing and analysis."
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# pyOpenMS