Omics to Insight: Building AI Pipelines for Precision Biotechnology
Transform Omics Data into Precision Biotechnology Insights with AI
About This Course
This workshop introduces participants to the design of end-to-end AI pipelines for omics data, covering data cleaning, integration, feature engineering, predictive modeling, validation, and result interpretation. Participants will explore how AI supports applications such as biomarker discovery, strain optimization, disease classification, and precision biotechnology product development. The focus is on practical, dry-lab workflows using real-world biological datasets and reproducible computational tools.
Aim
This workshop aims to train participants in building AI-driven pipelines that transform raw omics data into actionable biological and biotechnological insights. It focuses on integrating genomics, transcriptomics, proteomics, and related datasets with machine learning workflows for prediction, classification, and decision-making.
Workshop Objectives
- Understand the structure and challenges of multi-omics datasets.
- Learn to build AI workflows for preprocessing, integration, and feature extraction.
- Apply machine learning models for prediction and biological classification.
- Evaluate pipeline performance with statistical and biological validation.
- Interpret AI outputs for biomarker discovery and precision biotechnology decisions.
Workshop Structure
Day 1: Omics Data and AI Workflow Foundations
- Genomics, transcriptomics, proteomics, metabolomics
- Data formats and biological meaning & Precision biotech use cases
- Data collection, preprocessing & feature engineering & training and validation
- Hands-on: Loading and cleaning omics datasets
- Exploratory analysis and feature preparation
- Tools: Google Colab/ Python/ Pandas/ NumPy/ Scanpy/ BioPython/ Matplotlib
Day 2: Machine Learning for Omics Analysis
- Classification and regression tasks
- Biomarker discovery & Patient/sample stratification
- Multimodal and Integrative Analysis
- Combining multiple omics layers
- Dimensionality reduction
- Clustering and representation learning
- Hands-on: Train a model on omics data
- Perform PCA/UMAP and clustering
- Compare model performance
- Tools: Scikit-learn, XGBoost, Scanpy, UMAP & TensorFlow or PyTorch
Day 3: End-to-End Precision Biotechnology Pipeline
- Feature importance, model interpretation
- translating predictions into biology
- Deploying a Practical Omics Pipeline
- Workflow automation, reproducibility & reporting results
- Hands-on: Build a mini omics AI pipeline from raw input to biological insight dashboard
- Tools: Google Colab / Jupyter/ SHAP/ Streamlit/ GitHub/ CSV/Excel integration tools
Who Should Enrol?
- Undergraduate/postgraduate degree in Bioinformatics, Biotechnology, Computational Biology, Genomics, Molecular Biology, Data Science, or related fields.
- Professionals working in biotech, pharma, healthcare analytics, diagnostics, or omics research sectors.
- Data scientists and AI/ML engineers interested in applying machine learning to biological and biotechnology datasets.
- Individuals with a keen interest in precision biotechnology, omics analytics, and AI-driven discovery.
Important Dates
Registration Ends
04/20/2026
IST 7:00 PM IST
Workshop Dates
04/20/2026 – 04/22/2026
IST 8:00 PM IST
Workshop Outcomes
Participants will be able to:
- Build AI pipelines for handling and analyzing omics datasets.
- Integrate multiple biological data layers into predictive workflows.
- Apply machine learning models to identify patterns and biomarkers.
- Interpret results in a biologically meaningful and translational context.
- Create reproducible omics-to-insight pipelines for research and industry use.
Fee Structure
Student Fee
₹2499 | $75
Ph.D. Scholar / Researcher Fee
₹3499 | $85
Academician / Faculty Fee
₹4499 | $95
Industry Professional Fee
₹5499 | $105
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
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