Workshop Registration End Date :14 Nov 2026
Virtual Workshop
Gut Microbiome Multi-Omics: Shotgun Metagenomics, Metabolomics & Precision Probiotics
Decode the Gut Microbiome. Integrate Multi-Omics. Design Precision Probiotic Strategies.
Skills you will gain:
About Workshop:
This 3-day workshop provides a practical introduction to gut microbiome multi-omics, combining shotgun metagenomics, metabolomics, machine learning, and precision probiotic design. Participants will learn how to analyze microbial communities, interpret metabolite profiles, integrate multi-omics datasets, and identify biologically meaningful signatures using freely accessible computational tools.
Each day includes a hands-on activity using Google Colab or Jupyter Notebook, making the workshop suitable for researchers and professionals seeking practical exposure to modern microbiome data analysis.
Aim: To equip participants with practical knowledge and computational skills to analyze gut microbiome metagenomic and metabolomic data, integrate multi-omics datasets, and translate microbial signatures into data-driven precision probiotic strategies.
Workshop Objectives:
- Understand the fundamentals of gut microbiome research and shotgun metagenomics.
- Perform taxonomic and functional profiling of microbiome datasets.
- Explore key gut microbial metabolites and metabolomics workflows.
- Apply statistical and machine learning approaches to microbiome data.
- Integrate metagenomic and metabolomic datasets.
- Identify microbial, metabolic, and functional biomarkers.
- Understand microbe–metabolite relationships.
- Explore data-driven approaches for precision probiotic candidate prioritization.
- Gain hands-on experience with open-source and freely accessible bioinformatics tools.
What you will learn?
📅 Day 1: Shotgun Metagenomics for Gut Microbiome Profiling
- Focus: Understanding gut microbiome profiling using shotgun metagenomics, taxonomic analysis, microbial diversity, and functional pathway interpretation.
- Introduction to gut microbiome and host–microbe interactions in health, disease, nutrition, and therapeutic research.
- Understanding the difference between 16S rRNA sequencing and shotgun metagenomics for microbiome analysis.
- Working with FASTQ data, quality control, preprocessing, and sequence-read cleaning for microbiome datasets.
- Taxonomic profiling of gut microbiome samples at species and strain-level resolution.
- Microbial abundance, diversity analysis, functional gene profiling, and pathway-level interpretation.
- Interpreting microbiome signatures linked with gut health, dysbiosis, disease states, and probiotic relevance.
🛠️ Hands-on:
- Taxonomic and functional profiling of a gut microbiome dataset.
🧰 Tools Covered: Google Colab, Python, FastQC, fastp, Kraken2, Bracken, MetaPhlAn, HUMAnN, pandas, Matplotlib
📅 Day 2: Gut Metabolomics & Microbe–Metabolite Analysis
- Focus: Exploring gut metabolomics, microbial metabolites, data normalization, biomarker discovery, and microbe–metabolite association concepts.
- Introduction to targeted and untargeted metabolomics for gut microbiome and host-response research.
- Overview of LC-MS, GC-MS, and NMR-based metabolomics platforms used in gut metabolite profiling.
- Understanding metabolomics data preprocessing, normalization, scaling, and quality assessment.
- Studying key gut-related metabolites such as SCFAs, bile acids, tryptophan metabolites, and TMA/TMAO.
- Applying PCA, sample clustering, and differential metabolite analysis for metabolic signature identification.
- Understanding biomarker discovery and microbe–metabolite association concepts in gut health and disease research.
🛠️ Hands-on:
- Identification and visualization of key gut metabolomic signatures.
🧰 Tools Covered: Google Colab, Python, pandas, NumPy, SciPy, scikit-learn, Matplotlib, MetaboAnalyst, GNPS
📅 Day 3: Multi-Omics Integration, Machine Learning & Precision Probiotics
- Focus: Integrating metagenomics and metabolomics data to discover biomarkers, build prediction models, and prioritize precision probiotic candidates.
- Integration of metagenomics and metabolomics data for gut microbiome multi-omics analysis.
- Microbe–metabolite correlation analysis for identifying functional relationships between microbes and metabolites.
- Multi-omics biomarker discovery, feature selection, and data integration strategies.
- Random Forest-based prediction, ROC-AUC analysis, and model evaluation for gut microbiome datasets.
- Understanding feature importance and introduction to SHAP for interpretable machine learning.
- Identification of microbial and metabolic functional deficits linked with gut health and disease-associated signatures.
- Precision probiotic candidate prioritization, next-generation probiotics, synbiotics, and microbial consortia concepts.
🛠️ Hands-on:
- Build a multi-omics model to identify key microbial/metabolite features and prioritize probiotic candidates.
🧰 Tools Covered: Google Colab, Python, pandas, scikit-learn, SHAP, SciPy, Matplotlib, NetworkX, MOFA2, mixOmics
Mentor Profile
Fee Plan
StudentINR 2499/- OR USD 75
Ph.D. Scholar / ResearcherINR 3499/- OR USD 85
Academician / FacultyINR 4499/- OR USD 95
Industry ProfessionalINR 6499/- OR USD 115
Important Dates
Registration Ends
14 Nov 2026 Indian Standard Timing 4:30 PM
14 Nov 2026 Indian Standard Timing 4:30 PM
Workshop Dates
12 Nov 2026 to 14 Nov 2026 Indian Standard Timing 5:00PM
12 Nov 2026 to 14 Nov 2026 Indian Standard Timing 5:00PM
Get an e-Certificate of Participation!
Intended For :
- Researchers and Research Scholars
- PhD and Postdoctoral Researchers
- Academicians and Faculty Members
- Microbiologists and Microbiome Researchers
- Bioinformaticians and Computational Biologists
- Biotechnology and Life Science Professionals
- Metabolomics and Omics Researchers
- Nutrition and Food Science Researchers
- Probiotic and Functional Food Researchers
- Pharmaceutical and Biotechnology R&D Professionals
- Scientists working in host–microbe interactions and microbial therapeutics
- Professionals interested in multi-omics, machine learning, and precision microbiome research
Career Supporting Skills
Workshop Outcomes
By the end of the workshop, participants will be able to:
- Interpret shotgun metagenomics datasets and microbial abundance profiles.
- Analyze functional genes and metabolic pathways in the gut microbiome.
- Process and visualize gut metabolomics datasets.
- Identify important metabolites and microbial biomarkers.
- Perform microbe–metabolite correlation analysis.
- Apply PCA, Random Forest, ROC-AUC, and feature importance analysis.
- Integrate microbiome and metabolomics datasets for multi-omics interpretation.
- Identify potential functional and metabolic dysbiosis signatures.
- Prioritize potential probiotic strains or microbial consortia based on multi-omics evidence.
- Develop reproducible workflows using Google Colab and open-source tools.