Latest

• 2024-06-05 Paper accepted in Nature
• Structure and topography of the synaptic V-ATPase–synaptophysin complex
• Nonlinear Dynamic Changes During Human Aging Revealed in Multi-omics Profiles
• 2024-04-10 Paper accepted in Cell Host & Microbe
• Generalized reporter score-based enrichment analysis for omics data
• 2024-03-27 Paper accepted in Briefings in Bioinformatics
• Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease
• 🔬 Research
• 2023-11-23 Opportunities in Shen Lab
• Nonlinear Dynamic Changes During Human Aging Revealed in Multi-omics Profiles
• microbiomedataset A tidyverse-style framework for organizing and processing microbiome data
• Nonlinear Dynamic Changes During Human Aging Revealed in Multi-omics Profiles
• 2023-09-08 Xiaotao Shen presented on 2023 BAMM.
• 2023-9-1 Xiaotao Shen presented the nonlinear aging work on 2023 Stanford University Biox Symposium.
• Multi-Omics Microsampling for The Profiling of Lifestyle-Associated Changes in Health
• 2023-8-29 Xiaotao Shen presented on CASMS2023.
• 2023-8-29 Xiaotao Shen received the CASMS Young Investigator Award!😀
• Semi-supervised Cooperative Learning for Multiomics Data Fusion
• Multi-Omics Microsampling for The Profiling of Lifestyle-Associated Changes in Health
• Organism-wide, cell-type-specific secretome mapping of exercise training in mice
• Multi-Omics Microsampling for The Profiling of Lifestyle-Associated Changes in Health
• Multi-omics microsampling for the profiling of lifestyle-associated changes in health
• Deep learning-based pseudo-mass spectrometry imaging analysis for precision medicine
• Deep learning-based pseudo-mass spectrometry imaging analysis for precision medicine
• massDatabase utilities for the operation of the public compound and pathway database
• Deep learning-based pseudo-mass spectrometry imaging analysis for precision medicine
• Deep learning-based pseudo-mass spectrometry imaging analysis for precision medicine
• Tidymass An Object-oriented Computational Framework for LC-MS Data Processing and Analysis
• Multiomic analysis reveals cell-type-specific molecular determinants of COVID-19 severity
• Deep learning-based pseudo-mass spectrometry imaging analysis for precision medicine
• TidyMass an object-oriented reproducible analysis framework for LC–MS data
• Longitudinal Urine Metabolic Profiling and Gestational Age Prediction in Pregnancy
• Tidymass An Object-oriented Computational Framework for LC-MS Data Processing and Analysis
• Precision environmental health monitoring by longitudinal exposome and multi-omics profiling
• Longitudinal interactions between levels of serum cytokine and the microbiome from four body sites
• metID: an R package for automatable compound annotation for LC− MS-based data
• metID A R package for Automatable Compound Annotation for LC−MS-based Data
• Common and rare variant analyses combined with single-cell multiomics reveal cell-type-specific molecular mechanisms of COVID-19 severity
• Integration and comparison of multi-omics profiles of NGLY1 deficiency plasma and cellular models to identify clinically relevant molecular phenotypes
• A serum metabolomics analysis reveals a panel of screening metabolic biomarkers for esophageal squamous cell carcinoma
• Decoding links between the exposome and health outcomes by multi-omics analysis
• The mediation effect of serum metabolites on the relationship between long-term smoking exposure and esophageal squamous cell carcinoma
• Serum metabolomics analysis for the progression of esophageal squamous cell carcinoma
• Metabolic dynamics and prediction of gestational age and time to delivery in pregnant women
• MetFlow: an interactive and integrated workflow for metabolomics data cleaning and differential metabolite discovery
• Metabolic reaction network-based recursive metabolite annotation for untargeted metabolomics
• LipidIMMS Analyzer integrating multi-dimensional information to support lipid identification in ion mobility—mass spectrometry based lipidomics
• Development of a correlative strategy to discover colorectal tumor tissue derived metabolite biomarkers in plasma using untargeted metabolomics
• Predicting the pathological response to neoadjuvant chemoradiation using untargeted metabolomics in locally advanced rectal cancer
• Metabolic Reaction Network-based Recursive Metabolite Identification for Untargeted Metabolomics
• LipidCCS prediction of collision cross-section values for lipids with high precision to support ion mobility–mass spectrometry-based lipidomics
• Normalization and Integration of Large-Scale Mass Spectrometry-based Metabolomics Data Using Support Vector Regression
• Serum metabolomics for early diagnosis of esophageal squamous cell carcinoma by UHPLC-QTOF/MS
• Normalization and integration of large-scale metabolomics data using support vector regression