New Year Offer End Date: 30th April 2024
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Program

AI-Driven CRISPR Guide RNA Design & Off-Target Prediction

Optimizing Gene Editing Precision with AI-Driven CRISPR Guide RNA Design.

Skills you will gain:

About Program:

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 workshop focuses on leveraging AI to design optimized guide RNAs that improve the specificity and efficiency of CRISPR-based genome editing. By integrating machine learning algorithms and large-scale genomic data, participants will learn to predict and minimize off-target effects in gene editing experiments.
Over three days, the workshop will cover the fundamentals of CRISPR-Cas9 technology, the design of gRNAs using AI, and methods to predict and validate off-target effects. Hands-on sessions will allow participants to practice designing guide RNAs and running prediction models for off-target identification using AI-based tools.

Aim: This workshop aims to explore the application of AI in CRISPR-Cas9 technology, focusing on guide RNA (gRNA) design and off-target prediction. Participants will learn how to utilize AI algorithms to optimize gRNA sequences for precise gene editing and predict potential off-target effects, ensuring the accuracy and efficiency of CRISPR-based therapies.

Program Objectives:

  • Understand the fundamentals of CRISPR-Cas9 and its applications in gene editing.
  • Learn how AI can be applied to optimize guide RNA design for CRISPR.
  • Gain hands-on experience in using AI algorithms to predict off-target effects.
  • Explore methods for validating and minimizing off-target effects in CRISPR experiments.
  • Understand the implications of off-target effects and how to mitigate them in genome editing.

What you will learn?

Day 1 – CRISPR Fundamentals & AI Opportunities

  • CRISPR-Cas9 mechanism and applications
  • Guide RNA selection criteria (efficiency, specificity)
  • AI’s role in gRNA prediction and off-target scoring
  • Case study: DeepCRISPR, CRISPR-Net tools

Day 2 – Practical AI Models for gRNA Design

  • Input datasets for AI models (genomic sequences, PAM sites)
  • Using AI tools for scoring potential gRNAs
  • Live demo: Running a gRNA design using web-based AI platforms
  • Limitations and accuracy considerations

Day 3 – From In-Silico Prediction to Lab Validation

  • Integrating AI predictions into wet-lab workflows
  • Reducing false positives in off-target effects
  • Applications in therapeutic genome editing

Capstone Discussion: Designing a CRISPR experiment with AI support

Mentor Profile

Fee Plan

INR 1999 /- OR USD 50

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2024Certfiacte

Intended For :

  • Undergraduate/postgraduate degree in Genetics, Biotechnology, Bioinformatics, Molecular Biology, or related fields.
  • Professionals in genomic research, molecular biology, gene therapy, and genetic engineering.
  • Data scientists and AI/ML engineers interested in applying AI to genetic editing technologies.
  • Individuals with a strong interest in CRISPR technology and gene editing applications.

Career Supporting Skills

CRISPR Design Guide RNA Optimization Off-Target Prediction AI Algorithms Genetic Engineering

Program Outcomes

  • Knowledge of the CRISPR-Cas9 technology and its applications in gene editing.
  • Skills in designing optimized guide RNAs using AI-based tools.
  • Ability to predict and assess off-target effects in CRISPR-based experiments.
  • Practical experience with predictive modeling and off-target identification methods.
  • Understanding of how to minimize off-target effects and increase the precision of gene editing.