Biostatistics Events

Biostatistics Departmental Calendar

Event Category
Thu 9/12/2019 3:30PM - 4:30PM
Mingyao Li, University of Pennsylvania Biostatistics Seminar Series
Mingyao Li, University of Pennsylvania
Thu 9/12/2019 3:30PM - 4:30PM
Public Health Lecture Hall (A115)

Mingyao Li, PhD, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania.


Public Health Lecture Hall (A115)
Biostatistics
Seminar Series
Thu 9/19/2019 3:30PM - 4:30PM
Novartis Information Session Biostatistics Seminar Series
Novartis Information Session
Thu 9/19/2019 3:30PM - 4:30PM
Public Health Lecture Hall (A115)


Public Health Lecture Hall (A115)
Biostatistics
Seminar Series
Thu 10/10/2019 3:30PM - 4:30PM
Peter Mueller, University of Texas at Austin Biostatistics Seminar Series
Peter Mueller, University of Texas at Austin
Thu 10/10/2019 3:30PM - 4:30PM
Public Health Lecture Hall (A115)

Peter Mueller, PhD, Department of Mathematics, Department of Statistics and Data Sciences, University of Texas at Austin


Public Health Lecture Hall (A115)
Biostatistics
Seminar Series
Thu 10/24/2019 3:30PM - 4:30PM
Lu Mao, University of Wisconsin-Madison Biostatistics Seminar Series
Lu Mao, University of Wisconsin-Madison
Thu 10/24/2019 3:30PM - 4:30PM
Public Health Lecture Hall (A115)

Lu Mao, PhD, Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison


Public Health Lecture Hall (A115)
Biostatistics
Seminar Series
Thu 11/7/2019 3:30PM - 4:30PM
Snehalata Huzurbazar, West Virginia University Biostatistics Seminar Series
Snehalata Huzurbazar, West Virginia University
Thu 11/7/2019 3:30PM - 4:30PM
Public Health Lecture Hall (A115)

Snehalata Huzurbazar, PhD, Department of Biostatistics, West Virginia University


Public Health Lecture Hall (A115)
Biostatistics
Seminar Series
Sun 3/22/2020 to Wed 3/25/2020
ENAR 2020 Spring Meeting of the International Biometric Society -- JW Marriott Nashville Biostatistics Conference
ENAR 2020 Spring Meeting of the International Biometric Society -- JW Marriott Nashville
Sun 3/22/2020 to Wed 3/25/2020


Meetings of the Eastern North American Region of the International Biometric Society (a.k.a. "ENAR meetings") are held in late March or early April each year and reflect the broad interests of the Society, including both quantitative techniques and application areas. Faculty and student presenters from the Department of Biostatistics regularly participate giving invited talks, contributed talks, and poster presentations.


Biostatistics
Conference
Sat 8/1/2020 to Thu 8/6/2020
Joint Statistical Meetings - - JSM 2020, Philadelphia, PA Biostatistics Conference
Joint Statistical Meetings - - JSM 2020, Philadelphia, PA
Sat 8/1/2020 to Thu 8/6/2020


The Joint Statistical Meetings, known simply as "JSM", is the largest gathering of statisticians held annually in North American. Faculty and student presenters from the  Department of Biostatistics regularly participate giving invited talks, contributed talks, and poster presentations. Our students often receive top awards and participate in the affiliated career marketplace at the event.


Biostatistics
Conference
Sun 3/14/2021 to Wed 3/17/2021
ENAR 2021 Spring Meeting of the International Biometric Society -- Baltimore Biostatistics Conference
ENAR 2021 Spring Meeting of the International Biometric Society -- Baltimore
Sun 3/14/2021 to Wed 3/17/2021


Meetings of the Eastern North American Region of the International Biometric Society (a.k.a. "ENAR meetings") are held in late March or early April each year and reflect the broad interests of the Society, including both quantitative techniques and application areas. Faculty and student presenters from the Department of Biostatistics regularly participate giving invited talks, contributed talks, and poster presentations.


Biostatistics
Conference
Sat 8/7/2021 to Thu 8/12/2021
Joint Statistical Meetings - - JSM 2021, Seattle, WA Biostatistics Conference
Joint Statistical Meetings - - JSM 2021, Seattle, WA
Sat 8/7/2021 to Thu 8/12/2021


The Joint Statistical Meetings, known simply as "JSM", is the largest gathering of statisticians held annually in North American. Faculty and student presenters from the  Department of Biostatistics regularly participate giving invited talks, contributed talks, and poster presentations. Our students often receive top awards and participate in the affiliated career marketplace at the event.


Biostatistics
Conference
Sun 3/27/2022 to Wed 3/30/2022
ENAR 2022 Spring Meeting of the International Biometric Society -- Houston Biostatistics Conference
ENAR 2022 Spring Meeting of the International Biometric Society -- Houston
Sun 3/27/2022 to Wed 3/30/2022


Meetings of the Eastern North American Region of the International Biometric Society (a.k.a. "ENAR meetings") are held in late March or early April each year and reflect the broad interests of the Society, including both quantitative techniques and application areas. Faculty and student presenters from the Department of Biostatistics regularly participate giving invited talks, contributed talks, and poster presentations.


Biostatistics
Conference
Sat 8/6/2022 to Thu 8/11/2022
Joint Statistical Meetings - - JSM 2022, Washington, DC Biostatistics Conference
Joint Statistical Meetings - - JSM 2022, Washington, DC
Sat 8/6/2022 to Thu 8/11/2022


The Joint Statistical Meetings, known simply as "JSM", is the largest gathering of statisticians held annually in North American. Faculty and student presenters from the  Department of Biostatistics regularly participate giving invited talks, contributed talks, and poster presentations. Our students often receive top awards and participate in the affiliated career marketplace at the event.


Biostatistics
Conference

Recent Events

Biostatistics Dissertation Defense

Li Zhu - Bayesian variable selection model and differential co-expression network analysis for...

Tuesday 4/9 12:00PM - 2:00PM
A216 Public Health

Li Zhu of the Department of Biostatistics defends her dissertation on "Bayesian variable selection model and differential co-expression network analysis for multi-omics data integration".

Committee Chairperson: George C. Tseng, ScD, Department of Biostatistics

Committee Members: 
Robert Krafty, PhD, Department of Biostatistics
Lu Tang, PhD, Department of Biostatistics
Daniel E. Weeks, PhD, Department of Human Genetics 
Wei Chen, Department of Pediatrics 
 

Graduate faculty of the University and all other interested parties are invited to attend


ABSTRACT:

Due to the large accumulation of omics data sets in public repository, innumerable studies have been designed to analyze omics data for various purposes. However, the analysis of single data set often suffers from limited sample size, small power, and lack of reproducibility across studies, and thus data integration is gaining more and more attention nowadays. This dissertation focuses on developing methods for variable selection in regression and clustering for multi-omics data integration, and identification of differential co-expression network in the transcriptomic meta-analysis setting.

In the first paper, we propose a Bayesian indicator variable selection model to incorporate multi-layer overlapping group structure (MOG) in the regression setting, motivated by the structure commonly encountered in multi-omics applications, in which a biological pathway contains tens to hundreds of genes and a gene can contain multiple experimentally measured features (such as its mRNA expression, copy number variation and methylation levels of possibly multiple sites). We evaluated the model in simulations and two breast cancer examples, and demonstrated that the result not only enhances prediction accuracy but also improves variable selection and model interpretation that lead to deeper biological insight of the disease. In the second paper, we extended MOG to Gaussian mixture models for clustering, aiming to identify disease subtypes and detect subtype-relevant omics features.

In the third paper, we present a meta-analytic framework for detecting differential co-expression networks (MetaDCN). Differential co-expression (DC) analysis, different from conventional differential expression (DE) analysis, helps detect alterations of gene-gene correlations in case/control comparison, which is likely to be missed in DE analysis.

Public health significance: Methods proposed in paper 1 and 2 not only can predict disease outcome or identify disease subtypes, but also determine relevant biomarkers, which can potentially facilitate the design of a test assay to monitor disease progression, predict disease subtypes, and guide treatment decision. Methods developed in paper 3 provides a novel framework to identify differentially co-expressed genes to help us better understand how gene-gene interactions are altered in disease mechanism and provide potential new molecular targets for drug development.

Last Updated On Tuesday, March 19, 2019 by Valenti, Renee Nerozzi
Created On Tuesday, March 19, 2019

JulAugust 2019Sep
SunMonTueWedThuFriSat
28293031123
45678910
11121314151617
18192021222324
25262728293031
1234567

Submit events and news

Enter upcoming calendar events or share your school news and announcements at publichealth.pitt.edu/submit.