Department of Medical Statistics, University Goettingen

Dr. John Wiedenhöft


Research Associate
Core Facility for Medical Biometry and Statistical Bioinformatics
Phone:
0551-39-5969
Telefax:
0551-39-4995
E-Mail:
John.wiedenhoeft@med.uni-goettingen.de
Office room:
Humboldtallee 32, GF 164
ORCID iD:
 orcid.org/0000-0002-6935-1517
Short biography

[Since 2019] Research Associate at the Core Facility
"Medical Biometry and Statistical Bioinformatics"
[2017 - 2018] Postdoctoral Researcher in the Department of Computer Science and Engineering at Chalmers University of Technology (Gothenburg)
[2011 - 2016] Ph.D. in Computer Science in the Department of Computer Science at Rutgers University
[2010 - 2011] Research assistant at Max Planck Institute for Molecular Genetics (Berlin) at the Department of Computational Molecular Biology, working on phylogeny of multidomain proteins, biclustering of gene expression data
[2010] Visiting scholar at Iowa State University
[2009-2011] M.Sc. in Bioinformatics (Free University of Berlin and Charité)
[2009-2010] Research assistant in zebra finch RNA-seq project at Max Planck Institute for Molecular Genetics in Berlin
[2008-2010] Research assistant at Free University of Berlin, Department of Animal Behaviour in the project: "Do birds tango? Biological origins of rhythm as a carrier of emotions" (Cluster of Excellence "Languages of Emotion")
[2008] Research assistant at the Max Planck Institute for Evolutionary Anthropology: Algorithms for human genomic diversity in population genetics and phylogenetic approaches towards the evolution of Bantu languages.
[2007 - 2009] B.Sc. in Bioinformatics (Free University of Berlin and Charité)
[2004] Ethnomusicological field research with the Newar in Bhaktapur in the Kathmandu Valley (Nepal): The role of the dhimay in ritual and processional music during the biskah jatra
[2003-2006] Magister studies, in musicology (Humboldt-University Berlin), ethnomusicology and Indian philology (Free University of Berlin) as well as communication research (Technical University Berlin)

Theses section

  1. PhD Thesis:
    ‘Dynamically compressed Bayesian Hidden Markov Models using Haar wavelets’
  2. Master’s Thesis: ’Biclustering and Related Methods’
  3. Bachelor’s Thesis: ’ Phylogenetic Reconstruction of Ancestral Multidomain Proteins’