K
Konstantinos Tsekouras
Researcher at Arizona State University
Publications - 23
Citations - 640
Konstantinos Tsekouras is an academic researcher from Arizona State University. The author has contributed to research in topics: Medicine & Asymmetric simple exclusion process. The author has an hindex of 10, co-authored 16 publications receiving 541 citations. Previous affiliations of Konstantinos Tsekouras include Indiana University & Indiana University – Purdue University Indianapolis.
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Journal ArticleDOI
The heat released during catalytic turnover enhances the diffusion of an enzyme
Clement Riedel,Ronen Gabizon,Christian A. M. Wilson,Kambiz M. Hamadani,Kambiz M. Hamadani,Konstantinos Tsekouras,Susan Marqusee,Steve Pressé,Carlos Bustamante +8 more
TL;DR: It is proposed that the heat released during catalysis generates an asymmetric pressure wave that results in a differential stress at the protein–solvent interface that transiently displaces the centre-of-mass of the enzyme (chemoacoustic effect).
The heat released during catalytic turnover enhances the diffusion of an enzyme
Clement Riedel,Ronen Gabizon,Christian A. M. Wilson,Kambiz M. Hamadani,Kambiz M. Hamadani,Konstantinos Tsekouras,Susan Marqusee,Steve Pressé,Carlos Bustamante +8 more
TL;DR: In this article, the authors used single-molecule fluorescence correlation spectroscopy to show that for enzymes that catalyse chemical reactions with large reaction enthalpies, the heat released at the protein's active site during catalysis transiently displaces the protein center-of-mass, essentially giving rise to a recoil effect that propels the enzyme.
Journal ArticleDOI
Unraveling the Thousand Word Picture: An Introduction to Super-Resolution Data Analysis
Antony Lee,Konstantinos Tsekouras,Konstantinos Tsekouras,Christopher P. Calderon,Carlos Bustamante,Steve Pressé +5 more
TL;DR: A survey of data analysis methods starting from an overview of basic statistical techniques underlying the analysis of super-resolution and, more broadly, imaging data is provided.
Journal ArticleDOI
A novel method to accurately locate and count large numbers of steps by photobleaching.
TL;DR: A new Bayesian photobleaching trace analysis method that is computationally inexpensive can be used to treat blinking, reactivation, and overlapping events and reliably detect up to 50 fluorophores even for low signal-to-noise ratios.
A novel method to accurately locate and count large numbers of steps by photobleaching
TL;DR: A Bayesian photobleaching trace analysis method that is computationally inexpensive can be used to treat blinking, reactivation, and overlapping events and reliably detect up to 50 fluorophores as mentioned in this paper.