Fall 2019 Seminars
SEPTEMBER 26 | PATENGE ROOM C102 FEE HALL 3:30 pm
Raina Fichorova, MD, PhD
Distinguished Chair in Obstetrics,
Gynecology, Brigham and Women's Hospital
Professor of Obstetrics, Gynecology and Reproductive Biology
Harvard Medical School Research Division Director
"From maternal immunobiome to child health outcomes – lessons from the ELGAN study"
Rapidly decreasing costs of molecular measurement technologies not only enable profiling of disease sample molecular features (e.g., transcriptome, proteome, metabolome) at different levels (e.g., tissues, single cells), but also enable measuring of molecular signatures of individual drugs in clinically relevant models. Exploring methods to relate diseases to potentially efficacious drugs through various molecular features is critically important in the discovery of new therapeutics. We propose to employ a systems-based approach that identifies drugs that reverse the molecular state of a disease. There is a plethora of relevant datasets and analysis modules that are publicly available, yet are isolated in distinct silos, making it tedious, if not possible, to implement this approach in translational research for many labs. In this talk, I will present how these resources and analysis modules can be orchestrated in translational research and how advanced AI methods including deep learning can improve the performance. I will also introduce the hundreds of terabytes of data my lab is working on as well as computational changes we are facing.
OCTOBER 10 | E4 FEE HALL 3:30pm
Bin Chen, PhD | View Seminar
Assistant Professor
Department of Pediatrics and Human Development
Michigan State University
"Big Data in Translational Research"
Rapidly decreasing costs of molecular measurement technologies not only enable profiling of disease sample molecular features (e.g., transcriptome, proteome, metabolome) at different levels (e.g., tissues, single cells), but also enable measuring of molecular signatures of individual drugs in clinically relevant models. Exploring methods to relate diseases to potentially efficacious drugs through various molecular features is critically important in the discovery of new therapeutics. We propose to employ a systems-based approach that identifies drugs that reverse the molecular state of a disease. There is a plethora of relevant datasets and analysis modules that are publicly available, yet are isolated in distinct silos, making it tedious, if not possible, to implement this approach in translational research for many labs. In this talk, I will present how these resources and analysis modules can be orchestrated in translational research and how advanced AI methods including deep learning can improve the performance. I will also introduce the hundreds of terabytes of data my lab is working on as well as computational changes we are facing.
OCTOBER 24 | E4 FEE HALL 3:30 pm
Guilherme Rosa, PhD | View Seminar
Professor
Department of Animal Sciences
University of Wisconsin-Madison
“Using Graphical Models in Quantitative Genetics and Genomics Studies.”
Quite often in genetics and genomic studies interest relies on multiple correlated phenotypic traits. It is well known that the joint analysis of correlated traits using multivariate data analysis techniques might improve results in terms of statistical power and precision of parameters estimation compared to independent analyses for each trait. More importantly, a joint analysis provides additional insight regarding relationships between traits such as shared genetic and environmental factors across traits. Traditional multiple trait analyses however explore only symmetric relationships between traits, such as covariances and correlations, and do not consider the existence of recursive and feedback mechanisms. In contrast, graphical modeling techniques such as Bayesian networks and structural equation models explore functional links between variables in a phenotype network, in which one trait can be considered as a predictor of another trait. In this talk we will discuss some basic concepts and applications of graphical models in genetic studies, and illustrate how genomic information can aid network inferences, e.g. using instrumental variable techniques. Specific examples to be discussed will include applications in traditional quantitative genetic analyses of complex traits, as well as genome-wide association studies and whole-genome prediction.
NOVEMBER 14 | E4 FEE HALL 3:30 pm
Amelia K. Boehme, PhD, MSPH | View Seminar
Assistant Professor of Epidemiology (in Neurology
and in the Sergievsky Center)
Columbia University
“Infections and Inflammation: Stroke Risk Factors or Triggers?”
Stroke is the number one cause of severe long-term adult disability in the US and the fifth leading cause of death. The incidence and prevalence of stroke among the young is increasing in the US, with approximately 10%-14% of incident or new strokes occurring in people age 18-45. Health disparities in stroke incidence are increasing as well, with racial minorities, geographic location, and socioeconomic status increasing the risk of stroke in the young. It is estimated that poorly controlled risk factors account for nearly 90% of strokes, with younger adults having some of the lowest risk factor control, even among those who seek care. The overall goal of this talk will be to discuss novel risk factors for stroke, and how this plays a role in the changing demographics of stroke.
NOVEMBER 21 | E4 FEE HALL 3:30 pm
David Morgan, PhD | View Seminar
Professor of Translational Neuroscience
Michigan State University
"Michigan Aging Research Recruitment Consortium (MARRC) and Preventing Alzheimer's with Cognitive Training (PACT). The Alzheimer's Alliance in Grand Rapids"
The seminar will highlight the growth and development of a clinical research program on Alzheimer’s disease in Grand Rapids. The program is based upon some prior experience of Dr Morgan while in Tampa Florida. In that location he oversaw development of a Community Based Memory Screening Program serving 55 and older communities in west central Florida. In this program local volunteers, typically retirees with health care experience, were trained to administer the Montreal Cognitive Assessment to other members of their community. Health history and interest in clinical research were entered into a registry along with the MoCA score. A similar program is being developed in Grand Rapids and plans are being made to possibly extend this to other parts of Michigan. Another project initiated in Florida and now being conducted in Grand Rapids is the PACT study, a clinical trial examining Cognitive Training as a possible means to reduce risk of medically diagnosed cognitive decline. Four locations have been established in Tampa and are accruing participants, and two have been recently established in Grand Rapids. Rationale and study designs will be discussed.