[talks] Smita Krishnaswamy talk TODAY

Mona Singh mona at CS.Princeton.EDU
Thu Mar 5 10:23:15 EST 2015


TALK TODAY STILL ON


Colloquium Speaker
Smita Krishnaswamy, from Columbia University
Thursday, March 5, 12:30pm
Computer Science 105

Unlocking Cellular Computation and Information Processing through 
Multidimensional Single-Cell Data

Cells are computational entities that process external signals through 
networks of interacting proteins and reconfigure their state via 
biochemical modifications of proteins and changes in gene expression. 
Despite progress in the understanding of signaling biology, graph 
diagrams typically used as depictions of signaling relationships only 
offer qualitative abstractions. New single-cell measurement technologies 
provide quantitatively precise measurements of dozens of cellular 
components representing important biochemical functions. However, a 
major challenge in deciphering single-cell signaling data is developing 
computational methods that can handle the complexity, noise and bias in 
the measurements. I will describe algorithms that quantify the flow of 
information through signaling interactions and mathematically 
characterize relationships between signaling molecules, using 
statistical techniques to detect dependencies while mitigating the 
effect of noise. I will show how these algorithms can be utilized to 
characterize signaling relationships in immune cells, detect subtle 
differences between cell types, and predict differential responses to 
perturbation. Next, I will analyze T cells from non-obese diabetic (NOD) 
mice and show that previously recognized defects in 
extracellular-signal-regulated kinase (ERK) signaling can be traced back 
to a small receptor-proximal defect that is amplified through 
reconvergence in the network. Then, I will show how multidimensional 
extensions of these techniques can be used to track dynamic changes in 
the relatively unknown network driving the epithelial-to-mesenchymal 
(EMT) transition that occurs during cancer metastasis, with the goal of 
predicting drugs to halt the process. Finally, I will discuss future 
directions involving integration of gene expression and other data types 
in order to gain a more complete picture of cellular computation.


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