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SUMMARY:Cross-contamination rate estimation for digital PCR in lab-on-a-ch
 ip microfluidic devices - Bence Mélykúti (Albert-Ludwigs-Universität Fr
 eiburg)
DTSTART:20160616T100000Z
DTEND:20160616T110000Z
UID:TALK66582@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:<span>In the bond percolation model on a lattice\, we colour v
 ertices with n_c colours independently at random according to Bernoulli di
 stributions. A vertex can receive multiple colours and each of these colou
 rs is individually observable. The colours colour the entire component int
 o which they fall. Our goal is to estimate the n_c +1<br> parameters of th
 e model: the probabilities of colouring of single vertices and the probabi
 lity with which an edge is open. The input data is the configuration of co
 lours once the complete components have been coloured\, without the inform
 ation which vertices were originally coloured or which edges are open.<br>
  <br> We use a Monte Carlo method\, the method of simulated moments to ach
 ieve this goal. We prove that this method is a strongly consistent estimat
 or by proving a strong law of large numbers for the vertices&#39\; weakly 
 dependent colour values. We evaluate the method in computer tests. The mot
 ivating application is cross-contamination rate estimation for digital PCR
  in lab-on-a-chip microfluidic devices.</span>
LOCATION:Seminar Room 2\, Newton Institute
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