S
Stefan Hohmann
Researcher at Chalmers University of Technology
Publications - 205
Citations - 16932
Stefan Hohmann is an academic researcher from Chalmers University of Technology. The author has contributed to research in topics: Saccharomyces cerevisiae & Osmotic shock. The author has an hindex of 62, co-authored 204 publications receiving 15988 citations. Previous affiliations of Stefan Hohmann include University of the Free State & Technische Universität Darmstadt.
Papers
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Journal ArticleDOI
Comparison of the nucleotide sequences of a yeast gene family. II. Analysis of spontaneous deletions and insertions.
Daniel Gozalbo,Stefan Hohmann +1 more
TL;DR: It is concluded that small repeated sequences or monotonous sequences are prone to deletion or insertion mutations.
Book ChapterDOI
Chapter 8 Integrative analysis of yeast osmoregulation
TL;DR: A comprehensive mathematical model of yeast osmoregulation is generated and mechanisms of feedback control of the HOG pathway are analysed, illustrating how a signalling pathway combines rigorous feedback control with maintenance of signalling competence, as required for a system controlling cell homeostasis.
Book ChapterDOI
Aquaporin Water Channels in Saccharomyces Cerevisiae
TL;DR: Forming the largest subgroup in the MIP family, aquaporins (AQPs) are water-selective channels facilitating rapid water flow across cellular membranes, and have been identified in mammals, plants, invertebrates, amphibia, prokaryotes and recently in the baker’s yeast.
Posted ContentDOI
Correlating single-molecule characteristics of the yeast aquaglyceroporin Fps1 with environmental perturbations directly in living cells
TL;DR: This work employed super-resolved millisecond fluorescence microscopy with a single-molecule sensitivity, to track labelled molecules of interest in real time and shed new light on aspects of architecture and dynamics of glycerol-permeable plasma membrane channels.
Book ChapterDOI
Applying Microfluidic Systems to Study Effects of Glucose at Single-Cell Level
TL;DR: A guide to how to use microfluidic systems in single-cell studies and how the large amount of data can be analyzed in a "semi-automatic" manner using custom-made software is provided.