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Basel Computational Biology Seminar Grégory Paul Computer Vision Lab, ETH Zürich Towards imagederived quantitative models in biology: lessons learned from astral microtubule dynamics in yeastDeriving quantitative models from images as a primary source of data has become prominent in modern biology, and yet, such a task remains challenging. The common way to tackle such a problem relies on a two step process based on an ad hoc image processing pipeline. It extracts secondary data, that are used to assess the quantitative models of interest. The main drawback of such an approach is that classical image processing pipelines are inherently digital, and assume implicitly that objects live in pixel space, whereas most of the spatiotemporal models of biological processes are formulated in physical space. In our group we followed a different route and started a research program aiming at establishing a sound mathematical and computational framework for modelbased image processing. Using examples from astral microtubule dynamics in yeast will show our preliminary results in this direction, with an emphasis on the open problems and challenges. Date: Monday, December 14 th , 2015 Time: 16:00 Room: Lounge (13th floor), Klingelbergstrasse 61 Contact: Thomas Julou ([email protected])

Grégory’Paul’ - Biozentrum University of Basel...2015/12/14  · Basel!Computational!Biology!Seminar! Grégory’Paul’ Computer)Vision)Lab,ETHZürich)! “Towards’image4derivedquantitativemodels’inbiology:’

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Page 1: Grégory’Paul’ - Biozentrum University of Basel...2015/12/14  · Basel!Computational!Biology!Seminar! Grégory’Paul’ Computer)Vision)Lab,ETHZürich)! “Towards’image4derivedquantitativemodels’inbiology:’

     

   

 

Basel  Computational  Biology  Seminar    

Grégory  Paul  Computer  Vision  Lab,  ETH  Zürich  

 

“Towards  image-­‐derived  quantitative  models  in  biology:  

lessons  learned  from  astral  microtubule  dynamics  in  yeast”      

Deriving   quantitative   models   from   images   as   a   primary   source   of   data   has   become  prominent  in  modern  biology,  and  yet,  such  a  task  remains  challenging.  

The  common  way  to  tackle  such  a  problem  relies  on  a  two  step  process  based  on  an  ad  hoc  image   processing   pipeline.   It   extracts   secondary   data,   that   are   used   to   assess   the  quantitative  models  of  interest.  

The   main   drawback   of   such   an   approach   is   that   classical   image   processing   pipelines   are  inherently  digital,  and  assume  implicitly  that  objects  live  in  pixel  space,  whereas  most  of  the  spatio-­‐temporal  models  of  biological  processes  are  formulated  in  physical  space.  

In   our   group   we   followed   a   different   route   and   started   a   research   program   aiming   at  establishing   a   sound  mathematical   and   computational   framework   for  model-­‐based   image  processing.   Using   examples   from   astral   microtubule   dynamics   in   yeast   will   show   our  preliminary  results  in  this  direction,  with  an  emphasis  on  the  open  problems  and  challenges.  

 

 

 

Date:   Monday,  December  14th,  2015  

Time:   16:00  

Room:   Lounge  (13th  floor),  Klingelbergstrasse  61  

Contact:     Thomas  Julou  ([email protected])