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SUMMARY:Machine Learning Reveals the Genetic Code Controlling Splicing - B
 rendan Frey - Microsoft Research
DTSTART:20090714T140000Z
DTEND:20090714T150000Z
UID:TALK18840@talks.cam.ac.uk
CONTACT:Microsoft Research Cambridge Talks Admins
DESCRIPTION:*Abstract:* Thirty years after the proposal of DNA\, Roberts a
 nd Sharp discovered that DNA does not directly encode messenger RNA\, but 
 that a process called splicing assembles each mRNA based on carefully sele
 cted DNA subsequences. Because of this\, a gene can encode many different 
 mRNAs and which mRNAs are generated can depend on tissue type\, age and di
 sease. There are 22\,000 human genes\, but there are over 1\,000\,000 diff
 erent mRNAs produced by splicing. One gene encodes 38\,000 mRNAs that are 
 involved in wiring together neurons. Another gene encodes two mRNAs that d
 etermine the organism`s sexual preference. Roberts and Sharp received the 
 Nobel Prize for their work in 1993\, but the genetic information responsib
 le for controlling splicing has mostly remained a mystery. In the past 3 y
 ears it became possible to detect mRNAs with sufficient resolution that re
 searchers can attempt to infer for the first time such a `splicing code`. 
 In this talk\, I`ll describe a machine learning technique that we used to 
 infer a splicing code that is explanatory as well as predictive. Its inter
 pretation is consistent with known mechanisms\, but suggests new ones. The
  code achieves 93% prediction accuracy and was verified using different ge
 nes\, different species and different experimental assays. Mutation of the
  identified genetic information leads to corresponding changes in splicing
 . In addition to describing these results\, I`ll talk about how the object
 ive was formulated as a machine learning problem\, how the need for human 
 interpretability shaped the approach and what was done to isolate causatio
 n from correlation. 
LOCATION:Small public lecture room\, Microsoft Research Ltd\, 7 J J Thomso
 n Avenue (Off Madingley Road)\, Cambridge
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