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Advancing Single-Cell Analysis: A Comparative Exploration of Foundation Models

December 17, 2024
11 AM PST / 2 PM EST

Join us for an in-depth webinar where we explore the forefront of single-cell analysis through foundation models like scGPT, Geneformer, Nicheformer, Universal Cell Embedding (UCE), and Pinnacle. This session offers a comprehensive comparison of these leading models across critical applications, including cell type annotation, batch effect correction, perturbation prediction, and in-silico gene perturbation.We will walk you through the architectures and training objectives that underpin each model, examining how they represent genes and cells. By highlighting the strengths and limitations of each approach, we aim to provide valuable insights into their practical utility in various biological contexts.Additionally, we will present findings from our own evaluations of these models across multiple tasks. We'll discuss our hypotheses on the key factors that enhance model performance and propose methodologies for evaluating these models in biologically meaningful ways.

Who should attend?

This webinar is ideal for researchers, bioinformaticians, and professionals keen on leveraging single-cell foundation models for advanced biological insights.

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Real-World Applications We’ll Cover

  • Scaling clinico-genomic data integration: Large pharmaceutical organizations working with external data providers used Polly to build interoperable clinico-genomic data products 6x faster.
    Although purchased datasets are often labeled as "clean," they still lack interoperability—Polly's pipelines bridge this gap with robust integration and harmonization.

  • Information Retrieval: Drug safety monitoring teams used Polly's Knowledge Graph powered co-scientist to conversationally retrieve the right cohorts & assess drug response—cutting discovery time by 70%.

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What You’ll Learn

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Meet the Experts of this discussion
Key Takeaways
How data providers ensure adherence to quality standards through validation and compliance.
How GUI-based workflows, CLI tools, and collaborative workspaces enable streamlined data ingestion and synchronization at scale.
Understand how automated pipelines assess conformance, plausibility, and consistency, ensuring high-quality, AI-ready data products.
Key Takeaways
Reduce operational costs by streamlining data delivery through reusable, governed products.
Accelerate diagnostic development and clinical trial execution by delivering compliant, high-quality data at scale.
Improve audit readiness and regulatory confidence through governed data products and built-in quality assurance.
Equip cross-functional teams to act on trusted data—faster, and with greater confidence.
Who Should Attend?

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