Friday, January 28, 2022
11:00 am - 12:00pm
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Livnat Jerby, PhD 
Assistant Professor of Genetics
School of Medicine, Stanford University 

Title: Reprogramming multicellular circuits to unleash targeted immune responses

Friday, February 18, 2022
11:00am - 12:00pm
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Olivier Elemento, PhD

Weill Cornell Medicine 

 

Title: Towards AI-driven Cancer Precision Medicine 

Friday, March 18, 2022
11:00am - 12:00pm
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Dana Pe'er, PhD
Chair, Computational and Systems Biology Program
Scientific Director, Alan and Sandra Gerry Metastasis and Tumor Ecosystems Center 

Sloan Kettering Institute

Title: Cellular Plasticity in Cancer 

Friday, April 15, 2022
11:00am - 12:00pm
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Menna Clatworthy, FMedSci
NIHR Research Professor and Professor of Translational Immunology, University of Cambridge
Honorary Consultant Nephrologists, Cambridge University Hospitals NHS Foundation Trust 
Associate Faculty Cellular Genetics, Wellcome Sanger Institute

 

Title: Resolving the Immune Landscape of Human Prostate at a Single Cell Level in Health and Cancer

Friday, May 20, 2022
11:00am - 12:00pm 
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Oliver Stegle, PhD
Associate Faculty in the Cellular Genetics Programme  
Head, Division of Computational Genomics and Systems Genetics

German Cancer Research Center, Heidelberg 

Wellcome Sanger Institute, UK

TitleExtracting knowledge from multi-modal and spatio-temporal single-cell omics

Biomedicine is advancing to increasing complex and comprehensive experimental designs. Today’s studies have progressed from conventional omics profiling to apply a growing range of complex omics modalities, such as combining DNA sequencing, transcriptome sequencing, proteomics and single-cell technologies. While the dynamics to advance experimental designs and technologies is unprecedented, analysis strategies that allow for fully exploiting the resulting data remain limited. In this talk, I will describe statistical approaches and machine learning models to address both the computational needs and opportunities posed by multi-modal and spatio-temporal experimental designs. I will cover novel strategies to derive latent variables and molecular signatures from multiple omics in parallel, and which enable leveraging spatial and temporal dimensions. Finally, we will describe novel strategies for leveraging large population-scale single-cell variation datasets to map regulatory effects of genetic variants with single-cell resolution.

Friday, June 17, 2022
11:00am - 12:00pm 
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Darryl Shibata, MD
Professor of Pathology
Keck School of Medicine
University of Southern California

Title: How to barcode and analyze human cells without trying very hard

Lineage fate markers can reconstruct cell dynamics, but it is impractical to experimentally “barcode” human cells in vivo. Instead, genomic alterations are used as “molecular clocks”. A weakness of current molecular clocks is their relatively low error rates, which hampers documentation of more recent changes. We have developed a new faster clock where DNA methylation fluctuates like a pendulum between 0, 50 and 100%. Such well-behaved fluctuating CpG sites (fCpGs) have similar methylation and demethylation rates, oscillate every few years, and can be identified because their average methylation in a polyclonal population is about 50%.

fCpGs are measured with DNA methylation arrays, where unimodal peaks near 50% indicate a polyclonal population whereas trimodal “W” shaped distributions with peaks at 0, 50 and 100% indicate a recent clonal expansion. These patterns are seen in human intestinal crypts where thousands of fCpGs that have unimodal ~50% methylation in bulk intestine, and trimodal “W-shaped” distributions in single human crypts. The W-shape reflects the methylation of the clonal stem cell population, which provides information on crypt stem cell dynamics.  fCpGs are cell type specific and are further found in human blood, with unimodal distributions in normal polyclonal blood and W-shaped distributions in acute and chronic leukemias. DNA methylation is relatively easy to measure, and it may be possible to uniquely “barcode” the trillions of cells within a human with just a few hundred well-behaved fCpG sites.