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SUMMARY:Understanding genetic interaction networks - Florian Markowetz (Un
 iversity of Cambridge)
DTSTART:20160712T130000Z
DTEND:20160712T133000Z
UID:TALK66717@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Genes do not act in isolation\, but rather in tight interactio
 n networks. Maps  of genetic interactions between pairs of genes are a pow
 erful way to dissect  these relationships. I will discuss two statistical 
 approaches to better  understand the functional content of genetic interac
 tion networks and the  mechanism underlying them. <br> <br>First\, I will 
 present a method that adapt concepts of spatial statistics to  assess the 
 functional content of molecular networks. Based on the  guilt-by-associati
 on principle\, our approach (called SANTA) quantifies the  strength of ass
 ociation between a gene set and a network\, and functionally  annotates mo
 lecular networks like other enrichment methods annotate lists of  genes. <
 br> <br>Second\, I will describe a method to understand genetic interactio
 ns based on  high-dimensional phenotypes. I will present methodology we de
 veloped to test the  hypothesis that complex relationships between a gene 
 pair can be explained by  the action of a third gene that modulates the in
 teraction. Our approach to test  this hypothesis builds on Nested Effects 
 Models (NEMs)\, a probabilistic model  tailored to inferring networks from
  gene perturbation data. We have extended  NEMs with logical functions to 
 model gene interactions and show in simulations  and case studies that our
  approach can successfully infer modulators of genetic  interactions and t
 hus lead to a better understanding of an important feature of  cellular or
 ganisation. <br><br>Related Links <ul> <li><a target="_blank" rel="nofollo
 w">http://www.markowetzlab.org</a>  - Markowetz lab website&nbsp\;</li></u
 l>
LOCATION:Seminar Room 1\, Newton Institute
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