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Webinar
Application Note
Case Study
Twist Bioscience HQ
681 Gateway Blvd
South San Francisco, CA 94080
Building Better AI With High-Resolution Functional Genomics Data
Ci Chu at Xaira explores new approaches to generating large-scale, single-cell perturbation datasets that overcome key challenges in throughput, variability and batch effects.
Presented by
Ci Chu, PhD
Vice President, Early Discovery, Xaira
Covered in this Webinar
Learn about the application and limitations of perturbation data generation methods and how to overcome these bottlenecks to enable scalable, high-quality single-cell transcriptomic profiling
Explore the features of FiCS Perturb-seq and the X-Atlas/Orion dataset and how they form a resource for training biological foundation models
Discover how dose-dependent genetic effects, captured through single guide RNA abundance, enhance the predictive power of AI models in functional genomics and sequence optimization
Results are specific to the institution where they were obtained and may not reflect the results achievable at other institutions.
For research use only, not for use in diagnostic procedures.
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