1. From Data to Therapies Research in Xinghua Lu’s Lab
Research Themes
Cancer Pathway Discovery
Decision support system for personalized medicine
Machine learning
Deep learning
Text mining and knowledge representation
Grant support as PI:
R01 LM ,
R01 LM
R01 LM012011
Collaborative funding
U54HG  
R01 GM100387
1U01HL112707

2. Integrative analysis of cancer genomic data to discover cancer pathways
Combine genomic alteration and transcriptomic data to reveal driving pathways
Pathway discovery leads to novel treatment strategy

3. Decision support system for personalized precision medicine
Cancer is a genomic disease; each patient has unique genomic alteration and cellular signal perturbation
Cancer can benefit from personalized precision medicine
We are developing computational methods to support the above task at the individual patient level.
Methods for identify driver genomic alterations in a given tumor
Identify the pathways perturbed in the tumor
Predict the sensitivity of a given tumor to existing drug therapy

4. Deep learning in biology
Cellular signaling system is organized in hierarchy.
Deep hierarchical models are a interesting framework to learn systems
Identifying TF-binding motifs using deep convolutional neural networks.
gene 7
gene 9
gene 5
gene 3
gene 2
gene 4
gene 6
gene 8
gene 10
gene 1
AACTGT
CACTGT
CACTCT
Learning to predict human cell response based on rat cells’ responses