CompMed Seminar
2022-11-17 14:00 - 15:00 (America/New_York)
A Computational Medicine and the Center for Environmental Health and Susceptibility (CEHS) collaboration
Presenter: Didong Li
Talk Title: Linear models for case-control data

CompMed Research in Progress
2022-11-18 10:00 - 11:00 | Mary Ellen Jones 3106, 116 Manning Drive, 3rd floor, Chapel Hill, NC, 27599, United States
Presenter: Carson Mosso
Talk Title: “Association Mining and Sensitivity Analysis for Single-cell RNA-sequencing Data“

CompMed Research in Progress
2022-12-02 10:00 - 11:00 | Mary Ellen Jones 3112, 116 Manning Drive, Chapel Hill, NC, 27514
Presenter: Sarah Van Alsten
Talk Title: “Genomic algorithms to distinguish recurrent and second primary breast tumors”

No Meeting - Research in Progress
2022-12-09 10:00 - 11:00
No Research in Progress today, have a safe Holiday and see you January 6, 2023

CompMed Seminar
2022-12-15 14:00 - 15:00 | Bioinformatics Building, Room 1131, 130 Mason Farm Rd, Chapel Hill, NC, 27514, United States
Presenter: Amy Brock PhD
Associate Professor
Raymond F. Dawson Centennial Fellow
The University of Texas at Austin | Biomedical Engineering, Institute for Cell and Molecular Biology
Talk title: Tracking population heterogeneity and the dynamics of chemoresistance

No Meeting - Research in Progress Winter Holiday
2022-12-16 10:00 - 11:00
No Meeting – Research in Progress Winter Holiday

Holiday
2022-12-27 - 2023-01-02

Faculty Candidate Seminar
2023-01-05 14:00 - 15:00 | Lineberger Pagano Conference Room, 450 West Drive, Chapel Hill, 27599, United States
Presenter: Arjun Bhattacharya, PhD
Department of Pathology and Laboratory Medicine
David Geffen School of Medicine
University of California, Los Angeles
Talk Title: The breadth and depth of transcriptomics to understand the genetic etiology of diseases

Arjun Bhattacharya, PhD is a Postdoctoral Fellow in the Department of Pathology and Laboratory Medicine and in Computational Medicine at the David Geffen School of Medicine at UCLA and a Fellow of the Institute for Quantitative and Computational Biosciences. He earned my PhD in Biostatistics at the University of North Carolina at Chapel Hill, where he focused on statistical genetics, computational genomics, and molecular epidemiology. He develops and applies novel computational methods that integrate genetic and functional genomic data to understand complex diseases, specifically cancer progression, childhood neurodevelopment, and other developmental traits.

CompMed Research in Progress
2023-01-06 10:00 - 11:00
Presenter: Timothy Qi
Talk Title: Apex predators in anti-tumor immunity

Faculty Candidate Seminar
2023-01-10 16:00 - 17:00 | Bioinformatics Building, Room 1131, 130 Mason Farm Rd, Chapel Hill, NC, 27514, United States
Presenter: Haibo Ni, PhD
Department of Pharmacology, School of Medicine
University of California, Davis
Talk Title: Quantitative systems physiology and pharmacology for cardiac arrhythmias

Dr. Haibo Ni is an Assistant Project Scientist at the Department of Pharmacology, University of California Davis. He obtained his Ph.D. degree in Biological Physics from the University of Manchester, U.K., in 2017, and completed postdoctoral training with Prof. Eleonora Grandi’s lab at Davis. Dr. Ni received a prestigious American Heart Association (AHA) Postdoctoral Fellowship and is a grant reviewer for AHA Fellowship programs. He has 28 peer-reviewed journal publications and one book chapter in press.
Dr. Ni’s research advances quantitative systems investigation of cardiac physiology, pathophysiology, and pharmacology by developing multiscale and multiphysics computational frameworks of the heart. Dr. Ni’s work focuses on applying these frameworks to dissect complex mechanisms of heart diseases and define and optimize new therapeutic strategies through in-silico drug screening and virtual clinical trials using personalized simulations, with an emphasis on heart rhythm disorders.

Faculty Candidate Seminar
2023-01-12 14:00 - 15:00 | Bioinformatics Building, Room 1131, 130 Mason Farm Rd, Chapel Hill, NC, 27514, United States
Presenter: Abigail Lind, PhD
Gladstone Institutes, UCSF, San Francisco, CA
Talk Title: From pathogens to commensals: human-associated microbial eukaryotes through the lens of genomics and evolution

Humans coexist with myriad microbes that live within and on us, impacting our health in beneficial and detrimental ways. These microbes come from all domains of life and include bacteria, archaea, and eukaryotes. Eukaryotic microbes, including protists and fungi, are emerging as key members of the microbiome that influence other microbiota and host health in multifaceted ways. The factors that differentiate negative and positive interactions with a human host, and mechanistically how eukaryotic microbes accomplish these impacts, are unknown.
I have developed methods to routinely and accurately identify eukaryotic microbes in microbiomes, and discovered that multiple commensal protists are common members of a healthy gut. I have found that Blastocystis, a diverse species complex of stramenopile protists, are the most prevalent commensal gut eukaryotes worldwide and can be found in the guts of animals from insects to humans. Interestingly, Blastocystis is closely associated with gut health, correlating with decreased inflammation and high bacterial diversity. However, we understand very little about the biology of this common organism, which in the past has even been viewed as a parasite. Using comparative and functional genomics approaches in combination with mechanistic experiments on defined anaerobic cultures I investigate the function of Blastocystis and other commensal gut protists in the microbiome. These approaches have identified key biological principles of Blastocystis and in the future will determine how these common commensal gut protists interact with bacterial gut microbiota and the human host to impact health.

No Meeting - Research in Progress
2023-01-13 10:00 - 11:00
In honor of Martin Luther King Jr. Day on Monday, no meeting today.

Faculty Candidate Seminar
2023-01-17 16:00 - 17:00
Presenter: Christopher Park
Simons Foundation, Flatiron Institute, New York
Center for Computational Biology
Talk Title: The impact of RNA-binding protein dysregulation on psychiatric disorder risk

Christopher Park is a Flatiron Research Scientist at the Flatiron Institute, a research division of the Simons Foundation. Christopher’s background is at the intersection of computational biology, human genetics and RNA neurobiology, focusing on elucidating the pathogenic mechanisms that connect genetic risk to psychiatric disorders. Christopher also holds a research interest in health conditions that intersect with the endocrine system.
Prior to joining the Simons Foundation, Christopher was a postdoctoral researcher in the laboratory of Dr. Robert Darnell at Rockefeller University and the New York Genome Center. He completed his Ph.D. training at Princeton University with Dr. Olga Troyanskaya. In addition to his Ph.D., Christopher holds a B.S. in Biochemistry and Computer Science from the University of Washington, Seattle, where he also worked with Dr. William Stafford Noble tackling problems related to proteomics.

Faculty Candidate Seminar
2023-01-19 14:00 - 15:00 | Bioinformatics Building, Room 1131, 130 Mason Farm Rd, Chapel Hill, NC, 27514, United States
Presenter: Peng He, PhD
European Bioinformatics Institute
Wellcome Sanger Institute
Talk Title: Deciphering human organogenesis principles with single-cell and spatial technologies

Dr. Peng He had his Bachelor’s in Statistics and Biochemistry at the University of Hong Kong, after which he earned his PhD in genetics at California Institute of Technology. He now holds a joint postdoctoral research position between European Bioinformatics Institute (EMBL-EBI) and Wellcome Trust Sanger Institute

CompMed Research in Progress
2023-01-20 10:00 - 11:00 | Mary Ellen Jones 3112, 116 Manning Drive, Chapel Hill, NC, 27514
Presenter: Xiaoqi Li (Yun Li Lab)
Talk Title: “VAE-PRS: A deep learning based approach to compute polygenic risk score”

Faculty Candidate Seminar
2023-01-24 16:00 - 17:00 | Bioinformatics Building, Room 1131, 130 Mason Farm Rd, Chapel Hill, NC, 27514, United States
Presenter Christian Cuba-Samaniego, PhD
University of California Los Angeles
Talk Title: Adapting feedback control and pattern recognition paradigms for biotechnological applications
Engineering synthetic networks with desired behavior for robust adaptation or complex decision-making is challenging. Current approaches rely on different negative regulation techniques or logic-based operators, which suffer from suboptimal performance. To address this limitation, we introduce two design principles: (1) ultrasensitive input-output behavior and (2) tunable thresholds. Here, we engineer ultrasensitive-based networks to both achieve adaptive behavior through feedback control and build synthetic programs for molecular pattern recognition by implementing neural computing networks in living cells.

Faculty Candidate Seminar
2023-01-26 14:00 - 15:00 | Bioinformatics Building, Room 1131, 130 Mason Farm Rd, Chapel Hill, NC, 27514, United States
Presenter: Irene Kaplow, PhD
Carnegie Mellon University
Talk Title: Relating enhancer genetic variation across mammals to complex phenotypes using machine learning
Lecture abstract: Advances in the genome sequencing have provided a comprehensive view of cross-species conservation across small segments of nucleotides. These conservation measures have proven invaluable for associating phenotypic variation, both within and across species, to variation in genotype at protein-coding genes or highly conserved enhancers. However, these approaches cannot be applied to the vast majority of enhancers, where the conservation levels of individual nucleotides are often low even when enhancer function is conserved and where activity is tissue- or cell type-specific. To overcome these limitations, we developed the Tissue-Aware Conservation Inference Toolkit (TACIT), in which convolutional neural network models learn the regulatory code connecting genome sequence to open chromatin in a tissue of interest, allowing us to accurately predict cases where differences in genotype are associated with differences in open chromatin in that tissue at candidate enhancer regions. We established a new set of evaluation criteria for machine learning models developed for this task and used these criteria to compare our models to models trained using different negative sets and to conservation scores. We then developed a framework for connecting these predictions to phenotypes in a way that accounts for the phylogenetic tree. When applying our framework to motor cortex, we identified dozens of new candidate enhancers associated with the evolution of brain size and vocal learning.
Bio.: Irene Kaplow received her B.S. in Mathematics with a minor in Biology from the Massachusetts Institute of Technology in 2010. There, she began her career as a computational biologist while doing research with Bonnie Berger. She then went to graduate school at Stanford University, where she received her Ph.D. in Computer Science in 2017. At Stanford, she worked in the Hunter Fraser and Anshul Kundaje’s labs to develop methods to analyze novel high-throughput sequencing datasets to better understand the roles of DNA methylation and Cys2-His2 zinc finger transcription factor binding in gene expression regulation. Irene is now a Lane Postdoctoral Fellow in Andreas Pfenning’s lab in the Computational Biology Department at Carnegie Mellon University, where she is developing methods to identify enhancers involved in the evolution of neurological characteristics that have evolved through gene expression.

Faculty Candidate Seminar
2023-02-02 14:00 - 15:00 | Bioinformatics Building, Room 1131, 130 Mason Farm Rd, Chapel Hill, NC, 27514, United States
Talk Title: “Interpretable deep learning for cancer personalized medicine”
Dr. María Rodrίguez Martίnez is the Technical Leader of Systems Biology at IBM Research Europe (Switzerland) and an associated member of the Department of Biology at ETH since 2014. A theoretical physicist by training, she became interested in the development of computational and statistical approaches to unravel cancer molecular mechanisms using high-throughput multi-omics datasets and single-cell molecular data. In recent years, her team has specialized in the development of AI approaches for personalized drug modeling. More recently, she is building multi-scale models of the immune system through a combination of deep learning and mechanistic models. Through this effort, her team has developed deep learning models to predict the specificity of T cell receptors and stochastic mechanistic models to recapitulate B cell development.
She is also quite active in the area of interpretable deep learning. Deep learning has achieved astounding performances in a broad range of disciplines, but breakthrough performances have often come at the price of a lack of information about the rules that govern a model’s decision. Interpretable deep learning aims to develop models that can not only make a prediction with high accuracy, but can also provide insight into the reasons underlying the prediction. On this area, her team has contributed several novel methods for different applications in computational biology, ranging from AI-driven protein modeling to the integration of image and RNA-Seq data modalities.

CompMed Research in Progress
2023-02-03 10:00 - 11:00 | Mary Ellen Jones 3112, 116 Manning Drive, Chapel Hill, NC, 27514
Presenter Peyton Kuhlers (Hoadley Lab)
Talk Title: “Repeatability of Gene Expression between Patient Matched Tissue and Tissue Models”

Faculty Candidate Seminar
2023-02-07 16:00 - 17:00 | Bioinformatics Building, Room 1131, 130 Mason Farm Rd, Chapel Hill, NC, 27514, United States
Talk Title: “Accelerated Molecular Simulations and Drug Discovery”
Remarkable advances of supercomputing and artificial intelligence (AI) are transforming computational chemistry, biology and medicine in studies of molecules to cells. However, large gaps remain between the time scales of supercomputer simulations (typically microseconds) and those of biological processes (milliseconds or even longer). It has proven challenging to achieve sufficient sampling and compute thermodynamics and kinetics of biological systems, hindering effective drug design. I will present our efforts to address these challenges and make use of simulations for drug discovery. First, we have developed novel theoretical and computational algorithms and AI techniques. They have enabled unprecedented simulations on repetitive dissociation and binding of small molecules, peptides and proteins, thereby allowing for highly efficient and accurate calculations of their binding free energies and kinetics. These parameters are critical for therapeutic design of drugs, peptides and antibodies. Furthermore, we have combined complementary accelerated molecular simulations and cutting-edge experimental techniques to uncover functional mechanisms of important biomolecules and design novel drug molecules through successful collaborations with leading experimental groups. Our studied systems include G-protein-coupled receptors (GPCRs) that serve as primary targets of ~1/3 of currently marketed drugs, γ-secretase (a key membrane-embedded protease implicated in Alzheimer’s disease), RNA-binding proteins and RNA. Future outlooks will be provided for AI-driven drug discovery and multiscale modeling of cellular signaling pathways.
Brief Biography: Dr. Yinglong Miao is an Associate Professor in the Department of Molecular Biosciences and Center for Computational Biology at the University of Kansas. Yinglong obtained Ph.D. in Computational Chemistry in the Peter Ortoleva lab at Indiana University. He then received training in Biophysics and Pharmacology through postdoctoral studies, first with Jeremy Smith and Jerome Baudry at Oak Ridge National Laboratory/University of Tennessee, and then with Andy McCammon at the Howard Hughes Medical Institute/the University of California San Diego. Yinglong develops novel accelerated simulation methods and applies these methods in advanced simulations of biomolecules and drug discovery. His lab currently focuses on simulations and drug discovery of G-protein-coupled receptors (GPCRs), membrane-embedded proteases, RNA-binding proteins, and RNA. Yinglong received the Scientist Development Award from American Heart Association in 2017 and OpenEye Outstanding Junior Faculty Award from ACS Computational Chemistry in 2021. He has been productive in research with >80 published papers and 37 H-index so far. He has received funding from American Heart Association, NIH and NSF.

Canceled - CompMed Research in Progress
2023-02-10 10:00 - 11:00

Faculty Candidate Seminar
2023-02-14 16:00 - 17:00 | Bioinformatics Building, Room 1131, 130 Mason Farm Rd, Chapel Hill, NC, 27514, United States
Talk Title: Machine Learning the Rules od Antibody-Virus Interactions
Tal did his PhD at Caltech with Rob Phillips, whose lab specializes in developing models that don’t just fit data, but provide deep insights into the underlying mechanisms. In his postdoc, Tal shifted lanes into immunology, joining Jesse Bloom’s lab at the Fred Hutch Cancer Center which studies the antibody response against viruses such as influenza, HIV, and SARS-CoV-2. Tal is a Damon Runyon Quantitative Biology Fellow, and today we will hear about one of his multidisciplinary research projects that combines concepts from physics, math, biology, and computer science to help us understand and augment our antibody response against viruses.
Abstract for advertising talk: Immunology is undergoing a paradigm shift where the objective has expanded from creating a stopgap vaccine against a currently-circulating virus to developing a universal vaccine that confers lifelong protection. My research uses biophysical modeling and machine learning to probe how the antibody response changes with each viral exposure, with the ultimate goals of making the antibody response programmable and guiding it to a maximally-protective configuration. My lab will initially build off my expertise with influenza, but future efforts will generalize these methods to other viruses such as HIV-1 and SARS-CoV-2 that are of interest to public health.

Canceled - CompMed Research in Progress
2023-02-17 10:00 - 11:00
Holiday weekend and Monday is Mental Health Day.
Enjoy your weekend

CompMed Seminar
2023-02-28 14:00 - 15:00 | Bioinformatics Building, Room 1131, 130 Mason Farm Rd, Chapel Hill, NC, 27514, United States
Presenter: Trachette Jackson, PhD
University of Michigan
Date February 28, 2023
Talk Title “Multiscale Models for Understanding Tumor-Immune Dynamics and Optimizing Immune and Targeted Therapy Schedules”
Trachette Jackson is a professor in the Department of Mathematics in the College of Literature, Science, and the Arts and Assistant Vice President for Research – DEI Initiatives at the University of Michigan. Motivated by addressing critical challenges associated with cancer therapeutics, developing multiscale mathematical models is the aim of much of Dr. Jackson’s research. She designs these models to optimize the use of anticancer agents that specifically target active molecular pathways that cancer cells use to promote their growth and survival. Jackson is an award-winning educator and scholar who has received honors for her accomplishments in both areas. In 2003, she became the second African American woman to receive the prestigious Alfred P. Sloan Research Award in Mathematics; in 2005, she received the James S. McDonnell 21st Century Scientist Award; in 2008 Diverse Magazine honored her as one of the year’s Emerging Scholars. In 2010 she received the Blackwell-Tapia Prize, which biannually recognizes a mathematician for both their research achievements and for their contributions to addressing diversity in mathematics and in 2012 she was elected to the inaugural class of Simon’s Foundation Fellows, an honor featured in the NY Times. More recently, Dr. Jackson was voted into the inaugural class of Association for Women in Mathematics (AWM) Fellows and the 2021 class of the Society of Industrial and Applied Mathematics (SIAM) Fellows, becoming the first African American to have this honor.

CompMed Research in Progress
2023-03-03 10:00 - 11:00 | Mary Ellen Jones 3112, 116 Manning Drive, Chapel Hill, NC, 27514
Presenter: Assistant Professor Susana Garcia Recio
Talk Title: Multiomics analysis of matched primary and metastatic breast tumors from the AURIRA US Network

Research in Progress
2023-03-10 10:00 - 11:00 | Mary Ellen Jones 3112, 116 Manning Drive, Chapel Hill, NC, 27514
Presenter: Caitlin Rose Lahue
Talk Title: Differential Methylation in Isoproterenol Induced Heart Failure

No CompMed Seminar - Spring Break
2023-03-16 14:00 - 15:00

No Meeting - Research in Progress
2023-03-17 10:00 - 11:00
Enjoy Spring Break

BRC Spring Seminar - Dr. Karl Desch
2023-03-17 11:00 - 12:00 | Mary Ellen Jones 3116, 116 Manning Drive, Chapel Hill, NC, 27599, United States
Together with Dr. Erica Sparkenbaugh in the Blood Research Center, Karin Leiderman, PhD is hosting a seminar speaker for the BRC Spring Seminar series. They invited Dr. Karl Desch from the University of Michigan on March 17th, at 11:00 am. His talk is titled: “Using human genetic variation to explore mechanisms of hemostasis and thrombosis.”

Mini-Symposium - Precision Nutrition: Connections Between Food, Environment, & Health
2023-03-22 08:00 - 16:00
Join the UNC Program for Precision Medicine in Health Care (PPMH) for Precision Nutrition: Connections Between Food, Environment, & Health, a free virtual mini-symposium from 2:00-4:00pm on Wednesday March 22, 2023. Precision nutrition is an emerging personalized approach to nutrition that takes into account an individual’s unique dietary needs, lifestyle factors, and genetic makeup. This approach recognizes the intricate relationship between diet, environment, and health, acknowledging that what we eat and how we live can significantly impact our wellbeing.

Presentations:
Blending Precision Nutrition and Precision Public Health Approaches: “Neighborhood-omics”
Alice Ammerman, DrPH
Mildred Kaufman Distinguished Professor, Department of Nutrition, School of Public Health
Director, Center for Health Promotion & Disease Prevention, School of Medicine

Metabolic Individuality and Nutrition for Precision Health
Susan Sumner, PhD
Professor, Department of Nutrition, School of Public Health

How to Use Precision Nutrition in Current Clinical Practice
Martin Kohlmeier, MD, PhD
Professor, Department of Nutrition, School of Public Health

Click here for more information.
Click here to register.
Contact precisionmedicine@med.unc.edu with any questions.
