Difference between revisions of "User:Tim"

 
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<newstitle> The proton pump plays a crucial role in the phototropic response of Arabidopsis</newstitle>   
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Plants such as Arabidopsis Thaliana orient towards the light, thus optimizing the source of energy. This so-called phototropic response is mediated by the formation of a gradient of the plant growth hormone auxin. Using computational models validated by biological experiments, we showed in collaboration with the group of Christian Fankhauser from the CIG at UNIL, that the proton pump plays a crucial role in the establishment of this gradient and that this pump is regulated by the plants photoreceptors. The paper has just been published and is available in <a href="http://msb.embopress.org/content/10/9/751.long"> Molecular Systems Biology</a>
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<date>1 Oct 2014</date>
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</teaser>
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[[File:timCBG.jpg|200px|thumb|right|Tim Hohm, Postdoc]]  
 
[[File:timCBG.jpg|200px|thumb|right|Tim Hohm, Postdoc]]  
  

Latest revision as of 16:28, 1 October 2014



Tim Hohm, Postdoc

Tim Hohm is a postdoc at the Computational Biology Group in the Department of Medical Genetics at the University of Lausanne. He received his PhD from ETH Zurich in 2009, developing techniques for parameter estimation on gene regulative networks for multi-cell systems. He is now involved in the Plant Growth project from SystemsX.ch, investigating gene regulative networks responsible for phototropism in Arabidopsis thaliana.


Contact Details

  • address: Rue du Bugnon 27 - BU 01 116 - CH-1005 Lausanne - Switzerland
  • email: tim.hohm at unil.ch
  • phone: +41 - 21 - 692 - 53 78

Publications

2013

<biblio>

  1. phbf2013 pmid=24076239
  2. hpf2012 pmid=23152332

</biblio>

2010

<biblio>

  1. hzs2010a pmid=20169148
  2. wbhb2010a Woehrle M, Brockhoff D, Hohm T, and Bleuler S. Investigating Coverage and Connectivity Trade-offs in Wireless Sensor Networks: The Benefits of MOEAs. In Ehrgott M et al., editors, Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems (MCDM 2008), volume 634 of LNEMS, pages 211–221, Heidelberg, Germany, 2010. Springer. doi
  3. baha2010a Brockhoff D, Auger A, Arnold DV, and Hohm T. Mirrored Sampling and Sequential Selection for Evolution Strategies . In Schaefer R et al., editors, Parallel Problem Solving from Nature (PPSN XI), volume 6238 of LNCS, pages 11–21, Heidelberg, Germany, 2010. Springer. doi
  4. hz2010a pmid=20851739

</biblio>

2009

<biblio>

  1. hz2009b Hohm T and Zitzler E. A Multiobjective Evolutionary Algorithm for Numerical Parameter Space Characterization of Reaction Diffusion Systems. In Kadirkamanathan V et al., editors, International Conference on Pattern Recognition in Bioinformatics (PRIB 2009), volume 5780 of LNBI, pages 162–174, Heidelberg, Germany, 2009. Springer. doi
  2. hz2009c pmid=19622425
  3. hz2009a Hohm T and Zitzler E. Multiobjectivization for parameter estimation: a case-study on the segment polarity network of drosophila. In Rothlauf F et al., editors, GECCO '09: Genetic and Evolutionary Computation Conference (GECCO 2009), pages 209–216, New York, NY, USA, 2009. ACM. doi

</biblio>

2008

<biblio>

  1. hegb2008a Hohm T, Egli M, Gaehwiler S, Bleuler S, Feller J, Frick D, Huber R, Karlsson M, Lingenhag R, Ruetimann T, Sasse T, Steiner T, Stocker J, and Zitzler E. An Evolutionary Algorithm for the Block Stacking Problem. In Monmarché N et al., editors, Evolution Artificielle 2007, volume 4926 of LNCS, pages 111–122, Berlin, Germany, 2008. Springer. doi
  2. ghh2008a pmid=18284690

</biblio>

2007

<biblio>

  1. hz2007a Hohm T and Zitzler E. Modeling the Shoot Apical Meristem in A. thaliana: Parameter Estimation for Spatial Pattern Formation. In Marchiori E et al., editors, Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics (evoBIO 2007), volume 4447 of LNCS, pages 102–113. Springer, 2007. doi

</biblio>

2006

<biblio>

  1. hlh2006a pmid=16472025

</biblio>

2005

<biblio>

  1. hh2005a Hohm T and Hoffmann D. A multi-objective evolutionary approach to peptide structure redesign and stabilization. In Beyer H-G and O'Reilly U-M, editors, Genetic and Evolutionary Computation Conference (GECCO 2005), pages 423–429, New York, NY, USA, 2005. ACM Press. doi

</biblio>