HOST-MICROBIOME INTERACTIONS ANALYSIS FOR MICROBIOME-BASED THERAPEUTICS DEVELOPMENT
image credit: `ili spatial data mapping
What We Do
LONGITUDINAL MICROBIOME AND METABOLOME DATA ANALYSIS AND VARIATION IN HOST CLINICAL RESPONSE
MECHANISMS OF HOST-MICROBIOME INTERACTIONS IN MODULATION OF DRUG METABOLISM AND RESPONSE
MICROBIOME AND METABOLOME MACHINE LEARNING MODELS ON DISEASE BIOMARKER DISCOVERY COHORTS
Longitudinal microbiome-metabolome data analysis in clinical research
How We Do It
Identification of molecules or species predictive of response
Statistical analysis to identify microbes, metabolites or proteins predictive of metadata responses (such as disease phenotype, sample time collection, protein measurements in blood). Microbe data can be in form of 16S, shotgun metagenomics, RNA-Seq or microarray.
Untargeted metabolomics for novel molecule biomarker leads
Raw tandem MS/MS spectra from untargeted liquid or gas chromatography (LC/GC) mass spectrometry are converted into analyte feature tables and molecular annotations are explored beyond simple library matching using molecular networking and in silico screening.
Microbiome-metabolome or proteome correlation analysis
Paired samples are analyzed to identify significant correlations between microbes, metabolites or proteins, yielding insight into microbial-derived metabolites and their metabolic pathways. Microbe data can be in form of 16S, shotgun metagenomics, RNA-Seq or microarray.
Who We Are
Bringing together worldwide experts in mass spectrometry and next-generation sequencing, on the cloud, to elucidate how human microbiota communicate with their host and provide valuable insights for clinical research.