Part 1: Advancing biology through single cell phenomics (Prof dr. Bart Deplancke, Laboratory of Systems Biology and Genetics, EPFL, Lausanne, Switzerland)

"In my presentation, I will discuss recent advancements from our laboratory in single-cell phenomic analysis technologies. These include: 1) IRIS ("Interconnecting a Robotic Image of a cell to its scRNA-seq profile"), a novel and unpublished technology that pairs the transcriptomic fingerprint of a single cell with its high-resolution image. I will present proof-of-concept examples demonstrating how IRIS provides an unprecedented opportunity to: i) Leverage machine learning to uncover the molecular determinants of single-cell phenotypes and vice versa, contributing to an integrated understanding of cellular function and structure; and ii) transform clinical practices through paired single-cell imaging and transcriptomics. 2) scTF-seq, an approach for quantifying transcriptomic changes based on transcription factor dosage in single cells, offering insights into cell fate determination and the heterogeneity underlying cellular reprogramming. And 3) Live-seq (time permitting), a methodology for extracting single-cell transcriptomes without compromising cell viability, enabling temporal analyses of cellular responses and bridging the gap between transcriptomic profiling and functional behavior over time. These breakthroughs significantly enhance our ability to unravel complex biological processes at the single-cell level with high precision and temporal resolution. As such, they hold broad implications for gene regulation, cellular reprogramming, and developmental biology, opening new avenues for research and therapeutic strategies."

Part 2: Learning from single cell atlases (Prof dr. Irene Papatheodorou, Eerlham Institute, Norwich, UK)

"In my talk I will discuss insights we can learn from whole body or tissue specific cell atlases. First, I will present advancements in leveraging cell atlases to learn disease trajectories from larger disease cohorts or understand tissue microenvironment. Then, I will focus on using whole body cell atlas data to understand functional similarities and differences cross-species, across evolutionary distances. I will discuss how this information can help us test the orthologue conjecture. Throughout the talk I will highlight computational tools, workflows, as well as strengths and limitations of the different analyses or datasets.” "