Happening @ Michigan https://events.umich.edu/list/rss RSS Feed for Happening @ Michigan Events at the University of Michigan. CCMB / DCMB Weekly Seminar Series (March 10, 2021 4:00pm) https://events.umich.edu/event/82479 82479-21108092@events.umich.edu Event Begins: Wednesday, March 10, 2021 4:00pm
Location: Off Campus Location
Organized By: DCMB Seminar Series

Abstract: Single-cell technologies have transformed biomedical research in the last few years. With single-cell sequencing, we can now simultaneously measure thousands of genomics features in a large number of cells, which provides an ultrahigh resolution phenotypic map for each individual. However, single-cell protocols are complex. Even with the most sensitive platforms, the data are often sparse and noisy. Recent development of single-cell multi-omics and spatial transcriptomics technologies further imposed additional challenges on data integration. In this talk, I will present several machine learning methods that my group recently developed for single-cell and spatial transcriptomics data analysis. I will discuss methods for simultaneous denoising, clustering and batch effect correction, single-cell multi-omics data integration, identification of spatially variable genes, generation of super-resolution gene expression, and inference of cell type distribution in spatial transcriptomics. I will illustrate our methods by showing results from ongoing collaborations on cardiometabolic disease and applications to brain and cancer data.
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Biography: Dr. Li’s research interests include statistical genetics and genomics, bioinformatics, and computational biology. The central theme of her current research is to use statistical and computational approaches to understand cellular heterogeneity in human-disease-relevant tissues, to characterize gene expression diversity across cell types, to study the patterns of cell state transition and crosstalk of various cells using data generated from single-cell and spatial transcriptomics studies, and to translate these findings to the clinics. In addition to methods development, Dr. Li is also interested in collaborating with researchers seeking to identify complex disease susceptibility genes and acting cell types. She is Director of Biostatistics for the Gene Therapy Program at Penn, where she advises biostatistics and bioinformatics analysis for various gene therapy studies. She is also Chair of the Graduate Program in Biostatistics. Dr. Li actively serves in the scientific community. She served as a regular member for the NIH Genomics, Computational Biology and Technology (GCAT) study section for 6 years, and the NHGRI Center for Inherited Disease Research (CIDR) for 3 years. She is an Associate Editor of Annals of Applied Statistics, Statistics in Biosciences, PLOS Computational Biology, and Human Genetics and Genomics Advances. She is an elected member of the International Statistical Institute and a Fellow of the American Statistical Association.

https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

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Livestream / Virtual Wed, 24 Feb 2021 12:57:46 -0500 2021-03-10T16:00:00-05:00 2021-03-10T17:00:00-05:00 Off Campus Location DCMB Seminar Series Livestream / Virtual
CCMB / DCMB Weekly Seminar Series featuring Sriram Chandrasekaran (Assistant Professor, Biomedical Engineering) (March 17, 2021 4:00pm) https://events.umich.edu/event/82825 82825-21179592@events.umich.edu Event Begins: Wednesday, March 17, 2021 4:00pm
Location: Off Campus Location
Organized By: DCMB Seminar Series

Abstract: Drug combinations have the potential to greatly expand our pharmacopeia while reducing both cost and drug resistance. Yet the current drug-discovery approach is unable to screen the astronomical number of possible combinations in different cell types and does not account for the complex environment inside the body. We have developed AI tools - INDIGO and MAGENTA - that predict the efficacy of drug combinations based on the properties of the drugs, the pathogen, and the infection environment. We are also using modeling to identify drugs that work in synergy with the host immune system. Using INDIGO and MAGENTA, we have identified highly synergistic combinations of repurposed drugs to treat drug resistant infections including Tuberculosis, the deadliest bacterial infection. INDIGO also accurately predicts the outcome of past clinical trials of drug combinations. Our ultimate goal is to create a personalized approach to treat infections using AI.
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Biography: Chandrasekaran received his bachelor’s degree in Biotechnology from Anna University in 2008, and a PhD in Biophysics from the University of Illinois at Urbana-Champaign in 2013. He worked at Harvard University and MIT as a Harvard Junior Fellow between 2013 and 2016 and became an Assistant Professor at UM in 2017. His lab develops systems biology algorithms for drug discovery. Computer models from his lab like INDIGO and MAGENTA are being used to design effective therapies against drug resistant pathogens. His lab also develops systems biology algorithms to understand metabolic regulation. The approaches that they have created (PROM, ASTRIX, DFA, EGEM and GEMINI) perform complementary functions in modeling of metabolic and regulatory networks. Chandrasekaran’s research has been published in Cell, Genome Biology, mBio, and PNAS. For his work, Chandrasekaran previously received the 2013 Harvard Junior Fellowship, the 2011 Howard Hughes Medical Institute (HHMI) International Predoctoral Fellowship, the 2014 William Milton Fund award, 2018 UM Precision Health Investigator Award, and the 2018 Distinguished Young Investigator Award from the AICHE COBRA society.


https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

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Livestream / Virtual Fri, 05 Mar 2021 14:44:14 -0500 2021-03-17T16:00:00-04:00 2021-03-17T17:00:00-04:00 Off Campus Location DCMB Seminar Series Livestream / Virtual Sriram Chandrasekaran, PhD (Assistant Professor, Biomedical Engineering)
CCMB / DCMB Weekly Seminar Series Featuring Duncan K. Ralph (Fred Hutchinson Cancer Research Center) (March 24, 2021 4:00pm) https://events.umich.edu/event/82733 82733-21169592@events.umich.edu Event Begins: Wednesday, March 24, 2021 4:00pm
Location: Off Campus Location
Organized By: DCMB Seminar Series

Abstract: Antibodies are an integral part of the adaptive immune response, and are a critical component of both vaccine-induced and naturally-acquired immunity. The development of deep sequencing approaches in recent years has allowed us to sample a significant fraction of the diverse repertoire of B cell receptor sequences from which antibodies are made. These sequences encode a wealth of information on the somatic rearrangement and evolutionary processes that determine the contours of our antibody repertoires, and thus our ability to respond appropriately to pathogens and vaccines. Extracting this information, however, requires a careful inference approach across several different analysis steps. I will describe the computational approaches that we have taken to solving these problems, which constitute the partis software package, and describe their application in several projects, including HIV and Dengue data.

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Biography: Duncan attended the University of California at Santa Cruz for his undergraduate studies in physics, completing his thesis on energy transport in condensed matter theory in 2005. He completed his PhD at the Massachusetts Institute of Technology in 2014, working on the Large Hadron Collider at the European particle physics laboratory (CERN). His thesis described the observation of Higgs boson decays to four leptons. Since 2014, he has worked in Frederick Matsen’s lab at the Fred Hutchinson Cancer Research Center, first as a postdoctoral researcher and more recently as a staff scientist, writing new computational methods for the analysis of B cell receptor deep sequencing data.

https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

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Livestream / Virtual Thu, 04 Mar 2021 11:20:24 -0500 2021-03-24T16:00:00-04:00 2021-03-24T17:00:00-04:00 Off Campus Location DCMB Seminar Series Livestream / Virtual
CCMB / DCMB Weekly Seminar (March 31, 2021 4:00pm) https://events.umich.edu/event/83395 83395-21369780@events.umich.edu Event Begins: Wednesday, March 31, 2021 4:00pm
Location: Off Campus Location
Organized By: DCMB Seminar Series

Abstract:

Large, deeply phenotyped cohorts are reshaping the world of environmental epidemiology. Two such “big data” resources that are reshaping how we understand environmental health are electronic health records and human cohorts with genome-wide molecular phenotyping. Each provides a unique perspective that is moving the field closer towards “personalized” insights into environmental health risks. Here I will talk about a series of studies which utilize electronic health records and molecularly phenotyped cohorts to investigate vulnerable populations, gene-environment interactions, and epigenetic biomarkers of environmental sensitivity. Together these studies are helping us to understand environmental health risks in a new light.

Short bio:

Dr. Cavin Ward-Caviness is a Principal Investigator in the Public Health and Integrated Toxicology Division of the US Environmental Protection Agency. With a background in computational biology and environmental epidemiology, Dr. Ward-Caviness seeks to understand the environmental factors which influence health in vulnerable populations and the molecular mechanisms that influence environmental health risks. The Ward-Caviness lab uses a variety of “big data” approaches, and Dr. Ward-Caviness is the PI of the EPA CARES research resource, which allows researchers to study environmental health effects in vulnerable patient populations, e.g. individuals with heart failure, using large electronic health record databases. Dr. Ward-Caviness is also interested in how epigenetics and metabolomics can serve as an early indicator of adverse health effects from chemical and social environmental exposures and in particular how molecular biomarkers can give us insight into how the environment may accelerate the aging process and thus contribute to chronic disease. By integrating molecular and clinical data, Dr. Ward-Caviness seeks to understand environmental health as a way to advance personalized medicine and reduce health disparities.

https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

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Livestream / Virtual Mon, 29 Mar 2021 15:15:11 -0400 2021-03-31T16:00:00-04:00 2021-03-31T17:00:00-04:00 Off Campus Location DCMB Seminar Series Livestream / Virtual
CCMB / DCMB Weekly Seminar Series (April 7, 2021 4:00pm) https://events.umich.edu/event/83241 83241-21320453@events.umich.edu Event Begins: Wednesday, April 7, 2021 4:00pm
Location: Off Campus Location
Organized By: DCMB Seminar Series

Abstract: More than 3,000 new Marine recruits were studied prospectively during their initial Marine-mandated two-week quarantine and their subsequent basic training at Parris Island. The COVID Health Action Response for Marines (CHARM) studied completed 20,000 study visits and obtained more than 70,000 biosamples including pre- to post- SARS-CoV-2 infections in more than 1000 recruits. Serological, transcriptomic, and epigenetic analyses identify the response signature to SARS-CoV-2 infection in these largely asymptomatic young adults. Phylogenetic analysis and modeling provide insight into epidemiology and guidance for public health measures.

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Specialty: Neurology

Research Topics: Addiction, Apoptosis/Cell Death, Basal Ganglia, Bioinformatics, Brain, Cellular Immunity, Cerebral Cortex, Mathematical and Computational Biology, Multiple Sclerosis, Neuro-degeneration/protection, Receptors, Reproductive Biology, Signal Transduction, Theoretical Biology, Vaccine Development, Viruses and Virology

https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

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Livestream / Virtual Tue, 23 Mar 2021 11:23:58 -0400 2021-04-07T16:00:00-04:00 2021-04-07T17:00:00-04:00 Off Campus Location DCMB Seminar Series Livestream / Virtual
CCMB / DCMB Weekly Seminar (April 14, 2021 4:00pm) https://events.umich.edu/event/83595 83595-21436485@events.umich.edu Event Begins: Wednesday, April 14, 2021 4:00pm
Location: Off Campus Location
Organized By: DCMB Seminar Series

Abstract:
My lab's research involves the development and application of systems biology approaches—combining computation, machine learning, quantitative modeling, and experiments—to study the immune system in health and disease. Recent technological and computational advances allow comprehensive interrogation of multiple modalities (e.g., proteins, mRNAs, immune receptor sequences) in single cell resolution in the human population. Here I will highlight our work in the analysis human and single cell variations along the axes of early immune development, vaccination, and COVID-19. If time permits, I will also discuss the integration of tissue imaging, machine learning, and multiscale dynamical modeling of immune cell interactions to investigate the homeostatic regulation of autoreactive T cells.

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Biography: Dr. Tsang is a senior investigator in the NIH Intramural Research Program and leads a laboratory focusing on systems and quantitative immunology at the National Institute of Allergy and Infectious Diseases (NIAID). He also co-directs the Trans-NIH Center for Human Immunology (CHI) and leads its research program in systems human immunology. Dr. Tsang trained in computer engineering and computer science at the University of Waterloo and received his Ph.D. in biophysics from Harvard University. Dr. Tsang has worked as a software engineer and pursued systems biology research in both academia and industry including Rosetta Inpharmatics, Caprion Proteomics, MIT, and Merck Research Laboratories. Dr. Tsang has won several awards for his research, including NIAID Merit Awards for the development of a data reuse and crowdsourcing platform OMiCC and for leading a system biology study of human immune variability and influenza vaccination, which was selected as a top NIAID Research Advances of 2014. He currently serves as the founding chief editor of systems immunology for Frontiers in Immunology. He has served as a scientific advisor for a number of programs and organizations including ImmPort (the clinical and molecular data repository for NIAID), the Committee on Precision Medicine for the World Allergy Organization, the NIAID Modeling Immunity for Biodefense Program, the Allen Institute, the Immuno-Epidemiology Program at the National Cancer Institute, and the Human Vaccines Project.

https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

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Livestream / Virtual Wed, 07 Apr 2021 08:59:05 -0400 2021-04-14T16:00:00-04:00 2021-04-14T17:00:00-04:00 Off Campus Location DCMB Seminar Series Livestream / Virtual
Special Joint Seminar between DCMB, Mathematics, MIDAS, and Smale Institute (April 22, 2021 1:00pm) https://events.umich.edu/event/83615 83615-21491327@events.umich.edu Event Begins: Thursday, April 22, 2021 1:00pm
Location: Off Campus Location
Organized By: DCMB Seminar Series

Abstract:

The quest to understand consciousness, once the purview of philosophers and theologians, is now actively pursued by scientists of many stripes. This talk looks at consciousness from the perspective of theoretical computer science. It formalizes the Global Workspace Theory (GWT) originated by cognitive neuroscientist Bernard Baars and further developed by him, Stanislas Dehaene, and others. Our major contribution lies in the precise formal definition of a Conscious Turing Machine (CTM), also called a Conscious AI. We define the CTM in the spirit of Alan Turing’s simple yet powerful definition of a computer, the Turing Machine (TM). We are not looking for a complex model of the brain nor of cognition but for a simple model of (the admittedly complex concept of) consciousness. After formally defining CTM, we give a formal definition of consciousness in CTM. We then suggest why the CTM has the feeling of consciousness. The reasonableness of the definitions and explanations can be judged by how well they agree with commonly accepted intuitive concepts of human consciousness, the range of related concepts that the model explains easily and naturally, and the extent of its agreement with scientific evidence.

https://umich.zoom.us/j/95135773568

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Livestream / Virtual Wed, 14 Apr 2021 10:17:45 -0400 2021-04-22T13:00:00-04:00 2021-04-22T14:00:00-04:00 Off Campus Location DCMB Seminar Series Livestream / Virtual
Department of Computational Medicine & Bioinformatics || Weekly Seminar Series (September 8, 2021 4:00pm) https://events.umich.edu/event/86237 86237-21632210@events.umich.edu Event Begins: Wednesday, September 8, 2021 4:00pm
Location: Off Campus Location
Organized By: DCMB Seminar Series

Abstract:

Structural variants (SVs) are a source of pathogenic variants in a clinical referral population, however, they are often under-reported due to technical limitations of detection and difficulty with clinical interpretation. For example, mobile element insertions (MEIs) are estimated to lead to a positive finding in 1 out of 1000 rare genetic disease cases, yet the numbers are far lower in clinical diagnostic laboratories. Targeted NGS with short insert size libraries, unlike genome sequencing, will have very few discordant read pairs to indicate the presence of an SV. We, therefore, developed an SV detection tool called SCRAMble (Soft Clipped Read Alignment Mapper) to identify SV breakpoints in targeted NGS.

We applied SCRAMble to a prospective clinical referral cohort for exome sequencing to identify deletions and MEIs. We also applied SCRAMble to a hereditary cancer panel assay for the identification of a large inversion involving the MSH2 gene that causes Lynch syndrome. Adding breakpoint detection to clinical targeted sequencing identifies positive findings which were missed by prior testing and by other variant callers. Detecting breakpoints allows for more precise interpretation and for more targeted confirmation assays. By applying SV breakpoint detection, we are able to diagnose ~0.3% more cases. While this is a modest gain in diagnostic yield, for the patients and families involved, a positive diagnosis, even after prior testing, can have a meaningful impact on their lives.

Zoom link: https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

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Livestream / Virtual Thu, 02 Sep 2021 14:28:18 -0400 2021-09-08T16:00:00-04:00 2021-09-08T17:00:00-04:00 Off Campus Location DCMB Seminar Series Livestream / Virtual Rebecca Torene, Associate Director of Genomics Research | Data Science at GeneDx
Department of Computational Medicine & Bioinformatics Weekly Seminar Series (September 15, 2021 4:00pm) https://events.umich.edu/event/86598 86598-21635116@events.umich.edu Event Begins: Wednesday, September 15, 2021 4:00pm
Location: Off Campus Location
Organized By: DCMB Seminar Series

Abstract:

Chromosomal instability (CIN) results in the accumulation of large-scale losses, gains, and rearrangements of DNA. The broad genomic complexity caused by CIN is a hallmark of cancer, however, there is no systematic framework to measure different types of CIN and their impact on clinical phenotypes. Here, we evaluate the extent, diversity and origin of chromosomal instability across 7,880 tumors representing 33 cancer types from the TCGA collection. We present a compendium of 17 copy number signatures characterizing specific types of CIN, with putative aetiologies supported by multiple independent data sources. The signatures predict drug response and identify new drug targets. Our framework refines the understanding of impaired homologous recombination, one of the most therapeutically targetable types of CIN. Our results illuminate a fundamental structure underlying genomic complexity and provide a resource to guide future CIN
research in human cancers.

Bio:

Florian Markowetz is a Senior Group Leader at the Cancer Research UK Cambridge Institute. He is a Royal Society Wolfson Research Merit Award holder and received a CRUK Future Leader in Cancer Research prize. He holds degrees in Mathematics (Dipl. math.) and Philosophy (M.A.) from the University of Heidelberg and a Dr. rer. nat. (PhD equivalent) in Computational Biology from Free University Berlin, for which he was awarded an Otto-Hahn Medal by the Max Planck Society. His group at the CRUK Cambridge Institute combines computational work on cancer evolution and image analysis of the tumor tissue with experimental work on understanding key cancer mechanisms like the estrogen receptor.

Zoom link: https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

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Livestream / Virtual Thu, 09 Sep 2021 11:24:05 -0400 2021-09-15T16:00:00-04:00 2021-09-15T17:00:00-04:00 Off Campus Location DCMB Seminar Series Livestream / Virtual Florian Markowetz (Senior Group Leader at the Cancer Research UK Cambridge Institute)
Department of Computational Medicine & Bioinformatics Weekly Seminar (September 22, 2021 4:00pm) https://events.umich.edu/event/87282 87282-21640718@events.umich.edu Event Begins: Wednesday, September 22, 2021 4:00pm
Location: Off Campus Location
Organized By: DCMB Seminar Series

Abstract:

Histones are small proteins that package DNA into chromosomes, and a large number of studies have showed that several post-translational modification (PTM) sites on the histones are associated with both gene activation and silencing. Along with DNA and small non-coding RNA, histone PTMs make up epigenetic mechanisms that control gene expression patterns outside of DNA sequence mutations. Dysregulation of these chromatin networks underlie several human diseases such as cancer. Here I will give an update on technology advancements that have allowed for high-throughput quantitative analyses of histone PTMs and chromatin structure, and how we are applying these methods to understand epigenetic reprogramming found in malignant peripheral nerve sheath tumors (MPNSTs). MPNST is an aggressive sarcoma with recurrent loss of function alterations in polycomb-repressive complex 2 (PRC2), a histone-modifying complex involved in transcriptional silencing.

Zoom Link: https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

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Livestream / Virtual Mon, 20 Sep 2021 15:27:41 -0400 2021-09-22T16:00:00-04:00 2021-09-22T17:00:00-04:00 Off Campus Location DCMB Seminar Series Livestream / Virtual
Department of Computational Medicine & Bioinformatics Weekly Seminar (September 29, 2021 4:00pm) https://events.umich.edu/event/87515 87515-21642906@events.umich.edu Event Begins: Wednesday, September 29, 2021 4:00pm
Location: Off Campus Location
Organized By: DCMB Seminar Series

Abstract:

Human complex traits result from genetic and environmental factors, and from their interactions. Many of these effects are mediated by changes in gene regulation. Indeed, most genetic variants associated with complex trait variation in humans are in regulatory regions. I will present some of our recent studies on gene-environment interactions in gene regulation, with a specific focus on cardiovascular health. I will present evidence that gene-environment interactions in molecular phenotypes are frequent, account for a substantial portion of complex trait variation and modify genetic risk for disease.

Research Focus:

My lab is interested in understanding the genetic and molecular basis of inter-individual and inter-population differences in complex phenotypes. We combine evolutionary and functional genomics approaches to study intermediate phenotypes (e.g.: transcription factor binding, gene expression, protein secretion, etc.) and how they are affected by gene-environment interactions. Our research is funded by the NIH.

Zoom link: https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

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Livestream / Virtual Fri, 24 Sep 2021 14:01:53 -0400 2021-09-29T16:00:00-04:00 2021-09-29T17:00:00-04:00 Off Campus Location DCMB Seminar Series Livestream / Virtual Francesca Luca, PhD (Wayne State University)
Department of Computational Medicine & Bioinformatics Weekly Seminar (October 13, 2021 4:00pm) https://events.umich.edu/event/86441 86441-21634316@events.umich.edu Event Begins: Wednesday, October 13, 2021 4:00pm
Location: Off Campus Location
Organized By: DCMB Seminar Series

Abstract:

Understanding the genetic and molecular architecture of human disease is accelerated by robust model development and large-scale molecular profiling. I will present two studies leveraging big data analytics or automated machine learning to dissect human disease complexities: 1) Molecular and clinical signatures of SARS-CoV-2 infection in the US marines. This analysis revealed strong antiviral innate immunity set point in females contributing to sex differences in both molecular and clinical response to SARS-CoV-2 infection. A set of accurate biomarkers capable of detecting PCR false negative infections was implemented on small footprint devices. 2) Automated machine learning to interpret the effects of genetic variants. An automated framework, AMBER, was developed for efficiently searching neural network architectures to model genomic sequences. AMBER is useful in various biological applications, including fine mapping variants, partitioning genetic heritability, and in personalized medicine enabled by CRISPR/Cas9 genome editing. Together, these efforts demonstrate quantitative methods coupled with large-scale biomedical data as an effective avenue to decode human regulatory and disease biology.

Short Bio:

Frank Zhang is a Flatiron research fellow with Olga Troyanskaya at the Simons Foundation and Princeton University since 2019. Prior to that, he obtained his PhD at UCLA with Yi Xing. His research focuses on machine learning and statistical method developments for the prediction and interpretation of human molecular and genetic variations using biological big data. Recently, he works on adopting and developing cutting-edge neural architecture search methods to automate the design of deep neural networks in genomics. He is also interested in making deep learning in biomedicine more interpretable and equitable.

Zoom link: https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

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Livestream / Virtual Tue, 07 Sep 2021 14:45:38 -0400 2021-10-13T16:00:00-04:00 2021-10-13T17:00:00-04:00 Off Campus Location DCMB Seminar Series Livestream / Virtual
Department of Computational Medicine & Bioinformatics Weekly Seminar (October 20, 2021 4:00pm) https://events.umich.edu/event/88315 88315-21652404@events.umich.edu Event Begins: Wednesday, October 20, 2021 4:00pm
Location: Off Campus Location
Organized By: DCMB Seminar Series

Abstract:

The Ye lab is focused on harnessing the power of single cell and computational genomics to understand how immune cells sense and respond to their environment. Utilizing new experimental methods we have developed to enable multiplexed single-cell sequencing, I will describe results from sequencing 1.2M cells from ~250 samples to understand the cellular and molecular bases of systemic lupus erythmatosus and COVID-19. I will also describe how population scale single cell sequencing can enable dissection of the genetic architecture of gene expression and annotation of disease associated variants. Finally, I’ll touch on novel experimental workflows to further increase the throughput of single-cell genomics and for encoding orthogonal information into single-cell sequencing assays.

Research Overview:

The Ye lab is interested in how the interaction between genetics and environment affect human variation at the level of molecular phenotypes. To study these interactions, the lab couples high-throughput sequencing approaches that measure cellular response under environmental challenges with population genetics where such measurements are collected and analyzed across large patient cohorts. The lab develops novel experimental approaches that enable the large-scale collection of functional genomic data *en masse* and computational approaches that translate the data into novel biological insights. This approach is used to initially study primary human immune cells in both healthy and diseased patients to understand host pathogen interactions and its role in autoimmunity.

Zoom link: https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

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Livestream / Virtual Fri, 15 Oct 2021 14:50:45 -0400 2021-10-20T16:00:00-04:00 2021-10-20T17:00:00-04:00 Off Campus Location DCMB Seminar Series Livestream / Virtual
Department of Computational Medicine & Bioinformatics Weekly Seminar (October 27, 2021 4:00pm) https://events.umich.edu/event/88276 88276-21652019@events.umich.edu Event Begins: Wednesday, October 27, 2021 4:00pm
Location: Off Campus Location
Organized By: DCMB Seminar Series

Abstract:
Molecular classification has transformed the diagnosis and treatment of diffuse gliomas, creating targets for precision therapies. However, timely and efficient access to molecular diagnostic methods remains difficult, causing a significant barrier to deliver molecularly-targeted therapies. We aim to develop an innovative point-of-care diagnostic screening method that provides rapid and accurate molecular classification of diffuse gliomas through artificial intelligence and optical imaging in order to improve the comprehensive care of brain tumor patients.

Bio:
Dr. Todd Hollon is a neurosurgeon and research scientist who specializes in brain tumors. He is an Assistant Professor of Neurosurgery. He completed his postdoctoral training in the UM Translational Molecular Imaging Laboratory under the supervision of Drs. Daniel Orringer and Honglak Lee. His postdoctoral work focused on the application of deep neural networks to advanced imaging methods to improve the speed and accuracy of intraoperative brain tumor diagnosis. He hopes to be part of the next generation of young scientists that uses computation and machine learning to make scientific breakthroughs.

Host: Josh Welch, PhD

https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

In-Person: Forum Hall, Palmer Commons

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Livestream / Virtual Thu, 14 Oct 2021 14:26:31 -0400 2021-10-27T16:00:00-04:00 2021-10-27T17:00:00-04:00 Off Campus Location DCMB Seminar Series Livestream / Virtual
Department of Computational Medicine & Bioinformatics Weekly Seminar (November 3, 2021 4:00pm) https://events.umich.edu/event/88449 88449-21654119@events.umich.edu Event Begins: Wednesday, November 3, 2021 4:00pm
Location: Off Campus Location
Organized By: DCMB Seminar Series

Abstract
My research group works in the area of mathematical oncology, where we use mathematical models to decipher the complex networks of reactions inside of cancer cells and interactions between cells. Immune cells use hundreds of biochemical reactions to respond to their environment, become activated, and kill cancer cells. Understanding the complexity of these reaction networks requires computational tools and mathematical models. We combine detailed, mechanistic modeling with machine learning to study these networks, better understand cancer and immune cells, and predict ways to control tumor growth. In this talk, I will present our recent work aimed at predicting the dynamics of immune cell behaviors across three scales: intracellular signaling pathways in CAR T cells, the collective behavior of a heterogeneous population of immune cells, and tumor-immune interactions at the tissue scale. Our models generate novel mechanistic insight into immune cell activation and predict the effects of immunotherapeutic strategies.


Biography
Stacey D. Finley is the Gordon S. Marshall Early Career Chair and Associate Professor of Biomedical Engineering at the University of Southern California. Dr. Finley received her B.S. in Chemical Engineering from Florida A & M University and obtained her Ph.D. in Chemical Engineering from Northwestern University. She completed postdoctoral training at Johns Hopkins University in the Department of Biomedical Engineering. Dr. Finley joined the faculty at USC in 2013, and she leads the Computational Systems Biology Laboratory. Dr. Finley has joint appointments in the Departments of Chemical Engineering and Materials Science and Quantitative and Computational Biology, and she is a member of the USC Norris Comprehensive Cancer Center. Dr. Finley is also the Founding Director of the Center for Computational Modeling of Cancer at USC. Her research is supported by grants from NSF, NIH, and the American Cancer Society.

Selected honors. 2016 NSF Faculty Early CAREER Award; 2016 Young Innovator by the Cellular and Molecular Bioengineering journal; Leah Edelstein-Keshet Prize from the Society of Mathematical Biology; Junior Research Award from the USC Viterbi School of Engineering; the Hanna Reisler Mentorship Award; 2018 AACR NextGen Star; 2018 Orange County Engineering Council Outstanding Young Engineer; Elected Fellow of the American Institute for Medical and Biological Engineering (2021)

Hosted by: Alan Boyle, PhD

https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

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Livestream / Virtual Wed, 20 Oct 2021 09:54:50 -0400 2021-11-03T16:00:00-04:00 2021-11-03T17:00:00-04:00 Off Campus Location DCMB Seminar Series Livestream / Virtual Stacey D. Finley, Ph.D. (USC)
Department of Computational Medicine & Bioinformatics Weekly Seminar (November 10, 2021 4:00pm) https://events.umich.edu/event/88540 88540-21654960@events.umich.edu Event Begins: Wednesday, November 10, 2021 4:00pm
Location: Off Campus Location
Organized By: DCMB Seminar Series

Abstract:

Subspace classifiers have been around for a long time, beginning with feature selection, which in essence was a subspace selection technique. This talk will discuss the kind of subspace classifiers that Bledsoe and Browning presented in their 1959 paper and from which there have been a variety of extensions which we will discuss.

The Bledsoe and Browning subspace classifier quantizes measurement space. Each quantized observation tuple corresponds to a cell in measurement space. A collection of subspaces are selected at random. In the original form the subspaces were mutually exclusive. For each class, each cell of a subspace contained a number dependent on the number of observations of the training data that fell into that cell. For each class those numbers were combined in ways not dissimilar to random forests. For a given observation tuple, the class with the highest vote count was selected as the assigned class.

We will discuss a variety of principled extensions of the technique and make some comparisons with Neural Networks.

Research Interests:

High-dimensional space clustering, pattern recognition, knowledge discovery and artificial intelligence

Professor Haralick began his work as one of the principal investigators of the NASA ERTS satellite data doing remote sensing image analysis.

He has made a series of contributions in the field of computer vision. In the high-level vision area, he has worked on inferring 3D geometry from one or more perspective projection views.] He has also identified a variety of vision problems which are special cases of the consistent labeling problem. His papers on consistent labeling, arrangements, relation homomorphism, matching, and tree search translate some specific computer vision problems to the more general combinatorial consistent labeling problem and then discuss the theory of the look-ahead operators that speed up the tree search. The most basic of these is called Forward Checking. This gives a framework for the control structure required in high-level vision problems. He has also extended the forward-checking tree search technique to propositional logic.

Zoom: https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

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Livestream / Virtual Fri, 22 Oct 2021 09:28:27 -0400 2021-11-10T16:00:00-05:00 2021-11-10T17:00:00-05:00 Off Campus Location DCMB Seminar Series Livestream / Virtual Robert M. Haralick, PhD (City University of New York)
DCMB / CCMB Weekly Seminar Series (November 17, 2021 4:00pm) https://events.umich.edu/event/89137 89137-21660643@events.umich.edu Event Begins: Wednesday, November 17, 2021 4:00pm
Location: Palmer Commons
Organized By: DCMB Seminar Series

Talk title: Clinical Trajectory analysis to determine risk-factors of Copd: A COPDGene Study

Abstract:

Background

Chronic obstructive pulmonary disease (COPD) presents significant clinical heterogeneity and a wide variety of progression trajectories [1]. Clinical trajectory analysis (ClinTrajAn) is a powerful tool based on elastic principal graphs for the calculation of trajectories from large cross-sectional clinical data sets [2].

Aims and objectives

Our objective was to determine potential risk-factors by evaluate progression trajectories in COPD using ClinTrajAn on the COPDGene Phase I (baseline visit) dataset.

Methods

7883 participants, current and former smokers with GOLD 0 thru 4 COPD, from Phase I of the COPDGene study, were utilized for this work. 55 features were obtained for each subject, including demographics, spirometry, smoking history and computed tomography (CT), which included Parametric Response Mapping (PRM). Developed by our group, PRM is capable of simultaneously measuring small airways disease and emphysema which are the main contributors of airflow limitations in COPD. The resulting data matrix was analyzed with ClinTrajAn.

Results

A principal tree, with 13 branch segments and 8 termini, was generated (Figure 1). There was a clearly recognized trajectory from healthier subjects through decreasing lung function and increasing age (Figure 1 A), increasing in GOLD (Figure 1 B), to an emphysema high terminus (Figure 1 C). Notably this method illustrated numerous branching points along this trajectory.

Conclusions

In this study we used ClinTrajAn to obtain a map of disease progression trajectories in COPD including clinically recognized pathogenesis. Our next steps will be to further validate this approach using longitudinal data from the COPDGene follow-up visits.

References

1. Han MK, Agusti A, Calverley PM, Celli BR, Criner G, Curtis JL, Fabbri LM, Goldin JG, Jones PW, MacNee W, Make BJ. Chronic obstructive pulmonary disease phenotypes: the future of COPD. American journal of respiratory and critical care medicine. 2010 Sep 1;182(5):598-604.

2. Golovenkin SE, Bac J, Chervov A, Mirkes EM, Orlova YV, Barillot E, Gorban AN, Zinovyev A. Trajectories, bifurcations, and pseudo-time in large clinical datasets: applications to myocardial infarction and diabetes data. GigaScience. 2020 Nov;9(11):giaa128.

Zoom link: https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

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Lecture / Discussion Wed, 10 Nov 2021 09:47:40 -0500 2021-11-17T16:00:00-05:00 2021-11-17T17:00:00-05:00 Palmer Commons DCMB Seminar Series Lecture / Discussion
Department of Computational Medicine & Bioinformatics Weekly Seminar (December 1, 2021 4:00pm) https://events.umich.edu/event/88514 88514-21654664@events.umich.edu Event Begins: Wednesday, December 1, 2021 4:00pm
Location: Palmer Commons
Organized By: DCMB Seminar Series

Abstract:

Epigenetic control of gene expression is highly cell-type- and context-specific. Yet, despite its complexity, gene regulatory logic can be broken down into modular components consisting of a transcription factor (TF) activating or repressing the expression of a target gene through its binding to a cis-regulatory region. Recent advances in joint profiling of transcription and chromatin accessibility with single-cell resolution offer unprecedented opportunities to interrogate such regulatory logic. Here, we propose a nonparametric approach, TRIPOD, to detect and characterize three-way relationships between a TF, its target gene, and the accessibility of the TF’s binding site, using single-cell RNA and ATAC multiomic data. We apply TRIPOD to interrogate cell-type-specific regulatory logic in peripheral blood mononuclear cells and contrast our results to detections from enhancer databases, cis-eQTL studies, ChIP-seq experiments, and TF knockdown/knockout studies. We then apply TRIPOD to mouse embryonic brain data during neurogenesis and gliogenesis and identified known and novel putative regulatory relationships, validated by ChIP-seq and PLAC-seq. Finally, we demonstrate TRIPOD on SHARE-seq data of differentiating mouse hair follicle cells and identify lineage-specific regulation supported by histone marks for gene activation and super-enhancer annotations.

Hosted by: Joshua Welch, PhD

Speaker will be in-person and the seminar will be live-streamed via Zoom.

Zoom: https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

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Lecture / Discussion Thu, 21 Oct 2021 14:55:35 -0400 2021-12-01T16:00:00-05:00 2021-12-01T17:00:00-05:00 Palmer Commons DCMB Seminar Series Lecture / Discussion Yuchao Jiang (Assistant Professor in the Departments of Biostatistics and Genetics at UNC)
Weekly Seminar for DCMB / CCMB (February 23, 2022 4:00pm) https://events.umich.edu/event/92060 92060-21686457@events.umich.edu Event Begins: Wednesday, February 23, 2022 4:00pm
Location: Off Campus Location
Organized By: DCMB Seminar Series

Abstract:

In the Peixoto lab we use genomic approaches to understand gene expression and its epigenetic regulation in response to learning and sleep deprivation, and its alteration in autism spectrum disorders. This requires combining behavioral paradigms in mice, molecular biology and the analysis of high-throughput data in the brain in vivo. It also requires using the right data analysis tools to be able to capture the effect of learning or sleep in the context of an ever-active brain. In this talk we will discuss the effects of learning on chromatin accessibility and the effects of sleep loss in gene expression, with an emphasis on how data analysis influences our ability to detect novel and reproducible biology.

Short bio:

Lucia Peixoto received her bachelor’s degree in Biochemistry from the Universidad de la Republica in her native Uruguay in 2002. She subsequently earned her Ph.D. at The University of Pennsylvania under the mentorship of Dr. David S. Roos, using genomic and computational biology approaches to understand host-pathogen interactions. She completed her postdoctoral training in Neuroscience with Dr. Ted Abel at The University of Pennsylvania in 2015. During her fellowship, she was also a trainee at the Training Program in Neurodevelopmental disabilities at the Children’s Hospital of Philadelphia. As a trainee at CHOP, she completed a clinical internship at the Center for Autism Research under the supervision of Dr. Robert Schultz. She became an Assistant Professor at Washington State University in 2015 and has since been recognized with a K01 Early Career Faculty award from NIH/NINDS and a pilot award from the Simons Foundation Autism Research Initiative. She is also a member of the board of directors of the International Society of computational biology (ISCB) and cochair the Equity, Diversity and Inclusion committee of ISCB. Her lab uses behavior, electrophysiology, molecular biology and genomic approaches to understand how sleep and learning modulate transcription and how this may be altered in Autism Spectrum Disorders.

Zoom livestream link: https://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09

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Workshop / Seminar Mon, 07 Feb 2022 14:54:44 -0500 2022-02-23T16:00:00-05:00 2022-02-23T17:00:00-05:00 Off Campus Location DCMB Seminar Series Workshop / Seminar