Detects high variance signals and generates dose-response curves to futher investigate candidate signals.
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Updated
Sep 6, 2024 - R
Detects high variance signals and generates dose-response curves to futher investigate candidate signals.
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.
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.
A Heuristic Strategy for Metabolomics Analysis based on multiple chromatographic gradients to enhance metabolite coverage in untargeted metabolomics analysis.
Pathway Activity Analysis and Metabolite Annotation for Untargeted Metabolomics using Probabilistic Modeling
High Resolution Software for Mass Spectrometry
M²ara, a R shiny web app for feature selection in cell-based assays.
Intrinsic Peak Analysis (IPA) pipeline for peak-picking in large-scale untargeted small molecule analysis including metabolomics, lipidomics, exposomics, and environmental studies.
A Deep Learning Framework to Interpret Raw Mass Spectrometry (m/z) Data
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
geoRge: a computational tool for stable isotope labelling detection in LC/MS-based untargeted metabolomics
Python package for processing direct-infusion mass spectrometry-based metabolomics and lipidomics data
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