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- Bros Selling Roses9:00 am
- IS&T RCS Tutorial - Scientific Visualization Using MATLAB10:00 am
- Paul Emmanuel: Remnants11:00 am
- Qualities of Stillness: Paintings by Joseph Ablow11:00 am
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- Stacey Piwinski: It's not you, it's me12:00 pm
- Oobleck12:00 pm
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- Lynne Harlow: Sweetheart of the Rodeo12:00 pm
- Free Stretch and Breathe Class for BU Employees12:15 pm
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- Faculty Workshop: Presentation by Jay Wexler, "Our Non-Christian Nation: How Wiccans, Atheists, Satanists, and Other Non-Christians are Demanding Their Rightful Place in American Public Life" 12:45 pm
- IS&T RCS Tutorial - R Code Optimization1:00 pm
- Legal Research Skills for Practice Program: Transactional Law1:00 pm
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- BU Around the World: International Student Forum3:00 pm
- Panel Discussion: Boston Public Schools' Assignment Plan4:00 pm
- Clark Lau LLC: Careers in Immigration Q&A Panel Discussion- Cambridge, MA4:00 pm
- Panel Discussion: Defining and Understanding Community4:00 pm
- Defining and Understanding Community4:00 pm
- Across Boundaries: Research on Migration Across Disciplines4:00 pm
- Information Session: Trunk Club4:00 pm
- Blue Cross Blue Shield Recruiting 4:00 pm
- Statistical approaches for making sense of high-throughput biological data (Christine B. Peterson -- Stanford University)4:00 pm
- Funded Internship Programs 101 (hosted with Pardee School of Global Studies)5:00 pm
- Robins Kaplan LLP: 1L Diversity Internship Program Reception- Boston, MA5:00 pm
- BU Study Group - Using Jupyter5:00 pm
- Mocktail Night6:00 pm
- Condom Fairy Packing Party6:00 pm
- Melinda Lopez' BACK THE NIGHT6:30 pm
- Melinda Lopez's BACK THE NIGHT6:30 pm
- Faculty Recital: Gabriel Langfur, trombone and Shiela Kibbe, piano8:00 pm
Statistical approaches for making sense of high-throughput biological data (Christine B. Peterson -- Stanford University)
Abstract: In this talk, I will discuss statistical approaches I have developed to gain insight into the complex networks of regulation and interaction that govern biological systems. Understanding these networks and how they are disrupted by disease is an important step in identifying potential targets for the treatment of disease. Firstly, I will describe my work on the inference of biological networks such as metabolic or protein interaction networks from high-throughput data. In particular, I will address graphical modeling methods I have proposed in the Bayesian framework for inferring such networks based on limited sample sizes, and illustrate the application of these approaches to highlight mechanisms underlying cancer progression. Secondly, I will address the problem of establishing the genetic basis of multivariate traits such as gene expression or other molecular profiling data. Here I propose a multi-stage multiple testing procedure which controls important error rates regarding the discovery of regulatory variants and the association of these variants to traits.
When | 4:00 pm to 5:00 pm on Thursday, February 4, 2016 |
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Location | MCS 148 |