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.