AI Driven CRISPR Guide RNA Design and Off Target Prediction
AI-Driven CRISPR Guide RNA Design & Off-Target Prediction is a Moderate-level, 3 Days online program by NanoSchool. Master CRISPR-Cas9, AI, and gene editing through hands-on projects, real datasets, and expert mentorship.
- ModeRecorded Lectures
- LevelModerate
- Duration3 Days
| Attribute | Detail |
|---|---|
| Format | Recorded Lectures |
| Level | Moderate |
| Duration | 3 Days |
| Certification | e-Certification + e-Marksheet |
| Fee | Free |
| Tools | DeepCRISPR CRISPR-Net web-based AI platforms |
About the AI Driven CRISPR Guide RNA Design and Off Target Prediction Course
CRISPR-Cas9 has revolutionized genetic engineering, enabling precise editing of DNA.
However, one of the challenges in using CRISPR is the potential for off-target effects that can lead to unintended genetic modifications. This course focuses on leveraging AI to design optimized guide RNAs that improve the specificity and efficiency of CRISPR-based genome editing.
Program Highlights
• Comprehensive coverage of AI Driven CRISPR Guide RNA Design and Off Target Prediction from fundamentals to advanced applications
• Hands-on projects and real-world case studies in biotechnology
• Expert-curated curriculum aligned with current industry standards
• Access to recorded lectures and e-LMS platform for flexible, self-paced learning
• e-Certification and e-Marksheet upon successful completion
• Dedicated mentor support and interactive doubt-clearing sessions
• Practical experience with tools: DeepCRISPR, CRISPR-Net, web-based AI platforms
• Career-oriented training for academic and professional growth in biotechnology
Course Curriculum
Module 1: CRISPR Fundamentals & AI Opportunities
- Exploring CRISPR-Cas9 mechanism and applications
- Defining guide RNA selection criteria for efficiency and specificity
- Introducing AI’s role in gRNA prediction and off-target scoring
Module 2: Practical AI Models for gRNA Design
- Preparing input datasets for AI models
- Utilizing AI tools for scoring potential gRNAs
- Conducting live demos of gRNA design using web-based AI platforms
Module 3: From In-Silico Prediction to Lab Validation
- Integrating AI predictions into wet-lab workflows
- Reducing false positives in off-target effects
- Applying AI-driven CRISPR in therapeutic genome editing
