Mikhail Kolev

Dr. Mikhail Kolev

1. Faculty of Mathematics and Computer Science, University of Warmia and Mazury, Słoneczna 54 Street, 10-710 Olsztyn, Poland
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Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 February 2012 in Nonlinear Analysis: Real World Applications
Verified
Journal Article
Closed access
CJC.L. Jorcyk
C.L. Jorcyk
MKMikhail Kolev
Mikhail Kolev
KTK. Tawara
K. Tawara
BZBarbara Zubik-Kowal
Barbara Zubik-Kowal

1 May 2005 in Mathematical and Computer Modelling
Verified
Journal Article
Closed access
PDF file
MKMikhail Kolev
Mikhail Kolev

1 January 2007 in Collection of Czechoslovak Chemical Communications
Verified
Journal Article
Closed access
PDF file
ZVZhivko A. Velkov
Zhivko A. Velkov
MKMikhail Kolev
Mikhail Kolev
ATAlia Tadjer
Alia Tadjer

31 October 2010 in Nonlinear Analysis: Real World Applications
Verified
Journal Article
Closed access
KDKamil Drucis
Kamil Drucis
MKMikhail Kolev
Mikhail Kolev
WMW. Majda
W. Majda
BZB. Zubik-Kowal
B. Zubik-Kowal

30 October 2019 in Mathematics
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Journal Article
Open access
PDF file
MKMikhail Kolev
Mikhail Kolev
A new mathematical model of a general autoimmune disease is presented. Basic information about autoimmune diseases is given and illustrated with examples. The model is developed by using ideas from the kinetic theory describing individuals expressing certain functions. The modeled problem is formulated by ordinary and partial equations involving a variable for a functional state. Numerical results are presented and discussed from a medical view point.

30 May 2008 in Computational and Mathematical Methods in Medicine
Verified
Journal Article
Open access
PDF file
ZJZdzislaw Jackiewicz
Zdzislaw Jackiewicz
CJC. L. Jorcyk
C. L. Jorcyk
MKMikhail Kolev
Mikhail Kolev
BZB. Zubik-Kowal
B. Zubik-Kowal
This work demonstrates that prostate tumour progression in vivo can be analysed by using solutions of a mathematical model supplemented by initial conditions chosen according to growth rates of cell lines in vitro. The mathematical model is investigated and solved numerically. Its numerical solutions are compared with experimental data from animal models. The numerical results confirm the experimental results with the growth rates in vivo.