Bioinformatics

Bioinformatics

Date:
15 December 2015 15:00 hrs. - 18:00 hrs.
Location:
Figdor Lecture Theatre, 8th floor RIMLS Building, Geert Grooteplein 26-28, route 289
Title:
RIMLS Technical Forum Bioinformatics for PhD students
Speaker(s):

Prof. Dr. Rob Russell, Prof. Dr. Patrick Aloy, Prof. Dr. Martijn Huynen

15-12-2015 15:00:0015-12-2015 18:00:00Europe/AmsterdamRIMLS Technical Forum Bioinformatics for PhD students Figdor Lecture Theatre, 8th floor RIMLS Building, Geert Grooteplein 26-28, route 289Rimlsrimls@radboudumc.nl

Remarks / more information:

 

 

Registration

 

  

 

Speakers:
  

 

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 Prof. Dr. Rob Russell
Bridging the gap between genetics & molecular biology: methods to discern mechanism from mutation
The ability to sequence whole genomes rapidly has produced a flood of data that are an ongoing challenge to those interested in the molecular basis of disease.  Fortunately, the wealth of data already in existence related to protein structure, function and biomolecular interactions can often be used to rapidly discern which variations, from hundreds or thousands of candidates, might have the greatest impact on function.   We have developed several techniques over the past decade to help understand and predict biomolecular interactions, and in this presentation I will discuss how these can be applied to large datasets of human variants from cancer and genetic diseases to reveal novel insights into the molecular biology of disease. 

 

 

 

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Prof. Dr. Patrick Aloy
A Network Biology Approach to Therapeutics
Network and systems biology offer a novel way of approaching therapeutics by developing models that consider the global physiological environment of protein targets, and the effects of modifying them, without losing the key molecular details. In this talk, I will discuss two recent projects developed in the lab that exploit global properties of complex systems. In particular, I will present a computational network biology strategy, based on the quantification of pathway crosstalk inhibition in therapeutic networks, to discover synergistic drug combinations for breast cancer treatment. In addition, I will show how taking a chemo-centric view of human health, which does not require detailed mechanistic information, we can build networks of human conditions able to predict disease comorbidities, as well as identifying potential drug side effects and opportunities for drug repositioning.

 

 

 

undefinedProf. Dr. Martijn Huynen
Bayesian data integration to predict proteins of a molecular system 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  



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