×
  • Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
 

Using Network Information With Gene Expression Data - Jean Yee Hwa Yang

by on Dec 11, 2013

  • 312 views

Large-scale molecular interaction networks are dynamic in nature and changes in these networks, rather than changes in individual genes/proteins, are often drivers of complex diseases such as cancer. ...

Large-scale molecular interaction networks are dynamic in nature and changes in these networks, rather than changes in individual genes/proteins, are often drivers of complex diseases such as cancer. In this talk, I use data from stage III melanoma patients provided by Prof. Mann lab that comprise of clinical, mRNA and miRNA data to discuss how network information can be utilise in the analysis of gene expression analysis to aid in biological interpretation. I will also present an R software package, Variability Analysis in Networks (VAN), that enables an integrative analysis of protein-protein or microRNA-gene networks and expression data to identify hubs (i.e. highly connected proteins/microRNAs in a network) that are dysregulated, in terms of expression correlation with their interaction partners.

Statistics

Views

Total Views
312
Views on SlideShare
312
Embed Views
0

Actions

Likes
0
Downloads
11
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via SlideShare as Adobe PDF

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
Post Comment
Edit your comment

Using Network Information With Gene Expression Data - Jean Yee Hwa Yang Using Network Information With Gene Expression Data - Jean Yee Hwa Yang Presentation Transcript