Events Calendar

PQG Working Group

In Person

Kaia Mattioli Postdoctoral Research Fellow Brigham and Women’s Hospital Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms Transcription factors (TFs) control gene expression by interacting with DNA and cofactors to regulate transcription. Human TF genes produce multiple protein isoforms with altered DNA binding domains, effector domains, and other protein regions. The … Continue reading "PQG Working Group"

Quantitative Issues in Cancer Research Working Group Seminar

In Person

Daniel Schwartz Postdoctoral Research Fellow, Department of Biostatistics, Harvard T.H. Chan School of Public Health Treatment Effect Estimation in Multisite Trials with Endogenous Design: Old Estimators, New Results Abstract: In large-scale multisite randomized trials, key design features such as the sample size at each site often arise from an unpredictable social process. As a result, … Continue reading "Quantitative Issues in Cancer Research Working Group Seminar"

Quantitative Issues in Cancer Research Working Seminar

In Person

Elizabeth Graff PhD Student, Department of Biostatistics, Harvard T.H. Chan School of Public Health Discussion of "Shift-aware Human Mobility Recovery with Graph Neural Network" (Sun et al. 2021) Abstract: Human mobility recovery is of great importance for a wide range of location-based services. However, recovering human mobility is not trivial because of three challenges: 1) … Continue reading "Quantitative Issues in Cancer Research Working Seminar"

PQG Seminar

In Person

Xiang Zhou Professor of Biostatistics University of Michigan Statistical methods for fine-mapping analysis in genome-wide association studies Genome-wide association studies (GWAS) have identified many SNPs associated with common diseases and disease-relevant complex traits. However, the precise underlying causal signals and molecular mechanisms underlying these associations remain largely unknown. Here, I will discuss a few statistical … Continue reading "PQG Seminar"

Quantitative Issues in Cancer Research Working Seminar

In Person

Jodeci Wheaden PhD Student, Department of Biostatistics, Harvard T.H. Chan School of Public Health Lifestyle factors and impact on colon cancer risk Abstract: In my exploration titled "Lifestyle Factors and Impact on Colon Cancer Risk," I initially set out to understand the relationship between lifestyle choices and colon cancer risk. However, a pivot was necessary … Continue reading "Quantitative Issues in Cancer Research Working Seminar"

Quantitative Issues in Cancer Research Working Seminar

In Person

Giovanni Parmigiani Professor, Department of Data Science, Dana Farber Cancer Institute and Department of Biostatistics, T.H. Chan School of Public Health Digressions on Simpson’s Paradox

HIV Working Group

In Person

Daniela van Santen Postdoctoral Research Fellow, Harvard T.H. Chan School of Public Health, Department of Biostatistics The effect of direct-acting antivirals on the risk of hepatocellular carcinoma in people with HIV and HCV co-infection using a target trial emulation approach

Quantitative Issues in Cancer Research Working Group Seminar

In Person

Raphael Kim, PhD Student, Department of Biostatistics, Harvard T.H. Chan School of Public Health Title: Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling Abstract: There is a growing interest in using reinforcement learning (RL) to personalize sequences of treatments in digital health to support users in adopting healthier behaviors. Such … Continue reading "Quantitative Issues in Cancer Research Working Group Seminar"

PQG Student and Postdoc Seminar

In Person

Kodi Taraszka Research Fellow in Medicine Dana-Farber Cancer Institute COX proportional hazards Mixed Model (COXMM) accurately estimates the heritability of time-to-event traits With large biobanks connecting electronic health records with genetic sequencing, our understanding of the genetic architecture of time-to-event (TTE) traits such as age-of-onset, treatment response, and disease progression has grown. As a result, … Continue reading "PQG Student and Postdoc Seminar"