From single cells to multicellular organization: spatiotemporal learning from static omics data
Huck Distinguished Lecture Series

Abstract:
Cells make fate decisions in response to dynamic environments, and multicellular structures emerge from multiscale interplays among cells and genes across space and time. While single-cell omics data provides an unprecedented opportunity to profile cellular heterogeneity, the technology requires cell fixation, leading to a loss of critical spatiotemporal and intercellular interaction information. To address this, we must ask: How can we reconstruct temporal dynamics from static snapshots of single-cell omics data? How can we recover interactions among cells, for example, cell-cell communication? I will present a suite of our recently developed computational methods, including AI tools, to learn the single-cell omics data as a spatiotemporal and interactive system. Those methods are built on a strong interplay among systems biology modeling, dynamical systems approaches, machine-learning methods, and optimal transport techniques. We demonstrate the discovery power of these tools across various complex systems in development, regeneration, and disease. Finally, I will discuss the ongoing methodological challenges in the spatiotemporal learning of single-cell data.

About the Speaker:
Dr. Qing Nie is the University of California Presidential Chair, the UCI Excellence in Teaching Chair, and a Distinguished Professor of Mathematics and Systems Biology at the University of California, Irvine (UCI). He serves as the director of the UCI Center for Complex Biological Systems and the NSF-Simons Center for Multiscale Cell Fate Research. His research utilizes data-driven approaches, systems biology modeling, and AI tools to dissect complex biological systems, with a particular focus on single-cell analysis, multiscale modeling, cellular plasticity, stem cells, embryonic development, and their downstream applications to human disease. As a mentor, Dr. Nie has trained and supervised over 60 postdoctoral fellows and PhD students at the interface of mathematics and biology, with many transitioning into successful careers at academic institutions. He has been elected a Fellow of the American Association for the Advancement of Science (AAAS), the International Society for Computational Biology (ISCB), the American Physical Society (APS), the Society for Industrial and Applied Mathematics (SIAM), and the American Mathematical Society (AMS). Notably, ScholarGPS ranked Dr. Nie #1 globally over the last five years in both Single-cell Transcriptomics and Transcriptomics Technologies, based on the high impact, productivity, and citation analytics of his scholarly publications.

Contact

  Wenrui Hao
  wxh64@psu.edu