Dr. John Wiedenhöft

Research Associate, Scientific Core Facility Medical Biometry and Statistical Bioinformatics


telephone: +49 (0 ) 551 39-63371

fax: +49 (0) 551 39-4995

e-mail address: john.wiedenhoeft(at)med.uni-goettingen.de

location: Humboldtallee 32, EG 153

ORCID iDorcid.org/0000-0002-6935-1517

Short biography

[Since 2019]

Research Associate at the Scientific 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 - 2018]

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’

Publications

Follow us