E
Evgeny M. Mirkes
Researcher at University of Leicester
Publications - 81
Citations - 1171
Evgeny M. Mirkes is an academic researcher from University of Leicester. The author has contributed to research in topics: Computer science & Cluster analysis. The author has an hindex of 13, co-authored 72 publications receiving 760 citations. Previous affiliations of Evgeny M. Mirkes include Leicester General Hospital & Siberian Federal University.
Papers
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Journal ArticleDOI
A random six-phase switch regulates pneumococcal virulence via global epigenetic changes
Ana Sousa Manso,Melissa H. Chai,John M. Atack,Leonardo Furi,Megan De Ste Croix,Richard D. Haigh,Claudia Trappetti,Abiodun D. Ogunniyi,Lucy K. Shewell,Matthew Boitano,Tyson A. Clark,Jonas Korlach,Matthew Blades,Evgeny M. Mirkes,Alexander N. Gorban,James C. Paton,Michael P. Jennings,Marco R. Oggioni +17 more
TL;DR: This work demonstrates distinct virulence in experimental infection and in vivo selection for switching between SpnD39III variants, which is ubiquitous in pneumococci, indicating an essential role in its biology.
Journal ArticleDOI
Accelerometer-assessed Physical Activity in Epidemiology: Are Monitors Equivalent?
Alex V. Rowlands,Evgeny M. Mirkes,Thomas Yates,Stacy A. Clemes,Melanie J. Davies,Kamlesh Khunti,Charlotte L. Edwardson +6 more
TL;DR: If GENEActiv or Axivity is compared with the ActiGraph, time spent within intensity cut points has good agreement, which can be used to inform selection of appropriate outcomes if outputs from these accelerometer brands are compared.
Book ChapterDOI
The Five Factor Model of personality and evaluation of drug consumption risk
TL;DR: In this paper, an online survey methodology was employed to collect data including personality traits (NEO-FFI-R), impulsivity (BIS-11), sensation seeking (ImpSS), and demographic information.
Journal ArticleDOI
SOM: Stochastic initialization versus principal components
TL;DR: This work demonstrates on learning of one-dimensional SOM (models of principal curves) that for the quasilinear datasets the principal component initialization of the self-organizing maps is systematically better than the random initialization, whereas for the essentially nonlinear datasets the Random initialization may perform better.
Journal ArticleDOI
Automatic short answer grading and feedback using text mining methods
TL;DR: A model to predict marks based on the similarities between the student answers and the model answer is designed, and it is demonstrated that clusters indicate the groups of students who are awarded the same or the similar scores.