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Computational Biology Seminar Series

Thursday, February 24, 2022

Speaker: Adam Dupuy, PhD, Associate Professor of Anatomy and Cell Biology, Department of Pathology, University of Iowa

Customizing single cell applications to interrogate mechanisms of acquired drug resistance in cancer

We have recently developed a simple forward genetic screening method that can be used to identify genes associated with a specific cellular phenotype. This method utilizes a transposon mutagenesis approach to generate a genetically diverse population of cells with distinct transposon-tagged mutations. Various selection methods are then used to identify cells with the desired phenotype, and rapid transposon insertion site profiling then identifies candidate genes associated with the selected phenotype. We have recently applied this method to identify drivers of resistance to targeted oncology drugs. More recently, we have developed a novel approach to perform transposon insertion site profiling within the 10X Multiomic method such that we are able to obtain transposon insertion site, ATAC-seq, and gene expression profiles from individual cells. This novel approach provides the potential to perform phenotype-driven genetics screens at the single cell level.

Wednesday, September 4, 2019
Speaker: Dr. Andrew Severin, Adjunct Assistant Professor, Iowa State University

Transforming big data into informative data to accelerate scientific discovery
The role of bioinformatics has become increasingly important in the analysis of highthroughput
sequencing data used to answer scientific questions today. I will discuss how
collaboration with your local bioinformatics facility can accelerate scientific discovery,
increase extramural grant success and decrease time to publication. Having a centralized hub
of bioinformatics knowledge and expertise is as important today as having a shared supercomputing

Thursday, December 12, 2019
Speaker: Dr. Chris Vollmers, Assistant Professor, University of California - Santa Cruz

Realizing the potential of full-length transcriptome sequencing

Summary: Over the last decade, the analysis of transcriptomes using RNA-seq has become an integral part of biomedical research. However, because RNA-seq requires the fragmentation of transcripts, a lot of information on the analyzed transcriptome is lost in the process. Sequencing full-length transcripts using long-read sequencers like the ONT MinION could overcome this limitation but faces its own set of challenges. Dr. Vollmers will talk about how his lab has started to address these challenges using both molecular and computational biology. Finally, Dr. Vollmers will present full-length transcriptome data of human immune cells on the bulk and single-cell level to show the types of information we can now extract from this type of data.