A Deep Learning Framework to Interpret Raw Mass Spectrometry (m/z) Data
Python package for processing direct-infusion mass spectrometry-based metabolomics and lipidomics data
Intrinsic Peak Analysis (IPA) pipeline for peak-picking in large-scale untargeted small molecule analysis including metabolomics, lipidomics, exposomics, and environmental studies.
geoRge: a computational tool for stable isotope labelling detection in LC/MS-based untargeted metabolomics
Collaborative workflow for untargeted metabolomics data processing and analysis using open-source tools. https://doi.org/10.3390/metabo13040463
VOCCluster: Untargeted Metabolomics Feature Clustering Approach for Clinical Breath Gas Chromatography - Mass Spectrometry Data
For untargeted metabolomics, this tool calculates probability scores for metabolic disorders. In addition, it provides visual support with violin plots of the mass spectrometry (DI-HRMS) measurements for the lab specialists.
A Heuristic Strategy for Metabolomics Analysis based on multiple chromatographic gradients to enhance metabolite coverage in untargeted metabolomics analysis.
MetaboFlow: Untargeted LC-MS Metabolomics Quad-Workflow Pipeline | 非靶向代谢组学四工作流集成分析系统 | 4 pathway enrichment workflows (ORA+QEA) | Nature-quality figures | R-based | tidymass + MetaboAnalystR + limma
High Resolution Software for Mass Spectrometry
My MSc thesis focused on the improvement of metabolite biomarkers annotation. The resulting workflow combined common unsupervised-supervised ML models with graph-based analysis of metabolic reconstructions.
M2ara, a R shiny web app for feature selection in cell-based assays.
Detects high variance signals and generates dose-response curves to futher investigate candidate signals.
Shiny-guided R workflow for untargeted LC-MS/MS metabolomics — from .mzML to statistical analysis
Pathway Activity Analysis and Metabolite Annotation for Untargeted Metabolomics using Probabilistic Modeling
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