MAY 12, 2016 12:00 PM PDT

Learning Biology from Networks and their Structure

Speaker
  • Instructor, Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School
    BIOGRAPHY

Abstract

Network models are an invaluable tool for integrating multiple data types and for modeling interactions between biological elements. One common question that arises, however, is what to do with such a network beyond making a pretty picture. In this talk, I will describe two applications in which we have used network structure to explain features of biological systems. In the first, we construct bipartite eQTL networks from genotype and gene expression data collected by the GTEx consortium. In the second, we explore the response of gene regulatory networks in Mycobacterium tuberculosis to a targeted drug treatment. In both cases, we find that the network structural properties reflect constraints operating on each biological system, and that each network has its own unique, informative feature set. For example, in the eQTL networks, we find the global hubs are not very informative but degree is very useful in interpreting the tuberculosis regulatory network. I will also discuss statistical testing and validation of these networks using functional annotation and wet lab experiments.


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MAY 12, 2016 12:00 PM PDT

Learning Biology from Networks and their Structure


Specialty

Gene Expression

Research And Development

Dna

Big Data

Cancer Research

Tumor

Biomarkers

Cancer

Oncology

Earth Science

Gene Sequencing

University

Drug Discovery

Mass Cytometry

Cell Culture

Geography

Asia50%

Europe50%

Registration Source

Website Visitors100%

Job Title

Student50%

Medical Laboratory Technician50%

Organization

Manufacturer - Other50%

Academic Institution50%


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