Caroline Buckee, Department of Biostatistics Harvard TH Chan School of Public Health How do we predict the pandemic? Michael Mina, Department of Epidemiology Harvard TH Chan School of Public Health The importance and challenges of testing for COVID-19 Natalie Dean, Department of Biostatistics, University of Florida How we evaluate the efficacy of potential therapies and […]
Frontiers in Biostatistics Seminar Noah Simon, Ph.D. Associate Professor Department of Biostatistics University of Washington To build inferential or predictive survival models, it is common to assume proportionality of hazards and fit a model by maximizing the partial likelihood. This has been combined with non-parametric and high dimensional techniques, eg. spline expansions and penalties, to flexibly build […]
Frontiers in Biostatistics Webinar Marianne Menictas Postdoctoral Fellow, Department of Statistics Harvard University Mobile health (mHealth) technologies are increasingly being employed to deliver interventions to users in their natural environments. With the advent of increasingly sophisticated sensing devices (e.g., GPS) and phone-based EMA, it is becoming possible to deliver interventions at moments when they can […]
A conversation with Jeff Leek, PhD, Johns Hopkins University. Moderator: Rafael Irizarry. Registration required. https://dfci.zoom.us/webinar/register/WN_XscX-d21RqylhDCXzvP2-Q A recording of the talk is available on our YouTube channel.
Frontiers in Biostatistics Seminar Tuesday September 15, 2020 at 1:00PM Eastern Time Peter F. Thall, PhD Department of Biostatistics University of Texas M.D. Anderson Cancer Center Abstract: Conventional evaluation of a new drug, 𝐴, is done in three phases. Phase I relies on toxicity to determine a “maximum tolerable dose” (MTD) of 𝐴, in phase […]
Data Science Seminar September 22, 2020 2:00PM ET Ignaty Leshchiner, PhD Postdoctoral Fellow, Harvard Medical School/Brigham and Women's Hospital Zoom link: http://bit.ly/DSSept22 Abstract: Real-time study of tumor emergence and progression in patients will help predict and ultimately change the course of the patient's disease. This could be achieved by inferring genotypes of heterogeneous cell populations within […]
Data Science Seminar September 29, 2020 1:00PM ET Martin Aryee, PhD Assistant Professor of Pathology, Harvard Medical School Assistant Molecular Pathologist, Massachusetts General Hospital Zoom link: https://dfci.zoom.us/j/95524743149?pwd=SzN4cjJZUnhsNVl3dXNmZjZ1N3F4QT09 Abstract: The spatial organization of biological systems can impart additional functionality beyond that of the individual components. This is true at a range of scales – from cells […]
Frontiers in Biostatistics Seminar October 13, 2020 1:00PM Lu Tian, PhD Associate Professor of Biomedical Data Science in the School of Medicine Stanford University It is appealing to compared survival distributions based on restricted mean survival time (RMST), since it generates a clinically interpretable summary of the treatment effect, which can be estimated nonparametrically without […]
Data Science Seminar October 15, 2020 1:00PM ET Dominik Glodzik, PhD Repare Therapeutics Zoom link: https://bit.ly/DSOct15 Abstract: Whole genome sequences contain within them signatures of mutational processes. In particular, some of the mutation signatures relate to impaired DNA-repair in cancer cells. Accurate measurement of mutation signatures reveals the role of DNA-repair deficiencies in etiology and […]
Monday, December 14, 3:00-4:30 PM ET RSVP https://bit.ly/CDSBioDec14 Speakers: Aedin Culhane, Senior Research Scientist, Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health Isabella Grabski, PhD Student in Biostatistics, Harvard University Probabilistic gene barcodes identify cell-types in single-cell RNA-sequencing data Shannan Ho Sui, Senior Research Scientist, Harvard T.H. Chan School of Public Health […]
Frontiers in Biostatistics Seminar January 12, 2021 1:00PM Jing Ning, PhD Associate Professor. Department of Biostatistics Division of Quantitative Sciences The University of Texas M.D. Anderson Cancer Center Register at: https://bit.ly/FIBJan12 Abstract: Bias sampling mechanisms are commonly encountered in applications where the subjects in a target population are not given an equal chance to be selected, […]
