For seminar recording, please click here Talk Title: Dissecting intra-tumor heterogeneity by single cell RNA-seq    Abstract: Each tumor is composed of diverse malignant, immune and stromal cells that interact with one another and collectively determine tumor biology and clinical phenotypes. Over the past nine years, we have been applying single cell RNA-seq (scRNA-seq) to...Read More

Talk Title: Measuring and predicting cancer evolution with genomic data   Abstract: We combine theoretical population genetics models of evolving populations with machine learning methods to analyze cancer genomic data, with specific focus on whole-genome sequencing. This allows deconvoluting the signal in the data to measure clonal structures, selective advantage coefficients of subclones, and mutation...Read More

Talk Title: Somatic mutation and clonal expansion in normal tissues   Abstract: Cancers develop by somatic mutation and clonal selection within our tissues. Over the past decade, the ability to sequence cancer genomes has transformed our understanding of the genetics and evolution of a wide range of cancers. However, owing to technical limitations, little is...Read More

Talk Title: Molecular subtypes of Pancreatic Cancer and Ph+ lymphoblastic leukemia  Read More

Talk Title: Inference of field cancerization using stochastic models to improve cancer control Talk Summary: Early cancer detection strategies focus on screening individuals to find obvious precancerous lesions and removing them when possible. However, screening programs often suffer from both under-diagnosis due to inadequate screening, and over-diagnosis due to ineffective patient stratification in surveillance protocols....Read More

Talk Title: Computational Approaches for Genomics-Guided Pediatric Precision Cancer Medicine Talk Summary: My talk will focus on the methods and computational pipelines we are utilizing in molecular characterization of pediatric cancer patients with rare, relapsed or treatment refractory cancers.  I will illustrate these approaches with specific case examples and a summary of our progress to-date. Read More

Talk Title: Learning to summarize medical evidence Talk Summary: Decisions about patient care should be supported by data. But most clinical evidence — from notes in electronic health records to published reports of clinical trials — is stored as unstructured text and so not readily accessible. The body of such unstructured evidence is already vast...Read More

Talk Title: Enabling the robust characterization of spatial gene expression architecture in tissue sections at increased resolution using Bayesian modeling Talk Summary: New single-cell technologies such as single-cell RNA-seq and high-dimensional flow cytometry enable the unprecedented interrogation of single-cell phenotypes (and functions) under various biological conditions. A common statistical problem is the discovery and characterization...Read More

Talk Title: Cancer Data Science: Mutation, Selection and Computation Talk Summary: The Gerstung lab develops statistical algorithms to learn more about the causes and consequences of cancer from large data sets. I will provide an overview about recent advances in the areas of cancer evolution, mutational signature analysis, as well as digital pathology and spatial genomics....Read More

Talk Title: Coevolution of the cancer genome and MHC in immune surveillance by T cells   Talk Summary: Antigen presentation via the Major Histocompatibility Complex Class (MHC) is an essential component of anti-tumor immunity induced by immune checkpoint inhibition. MHC molecules expose peptide fragments on the cell surface, allowing T-Cell elimination of cells displaying antigen...Read More