Address: Department of Mathematics, University of Leicester, University
Road, Leicester LE1 7RH, United Kingdom
Institute of Computational Modeling,
E-mail:
Full Professor in
Research interests:
Dynamics of systems of
physical, chemical and biological kinetics;
Bioinformatics;
Human adaptation to hard
living conditions;
Architecture of neurocomputers and training algorithms for neural networks.
Education:
·
Doctor of Physics & Math (Biophysics), (Advanced
doctoral degree, Dr. Sc., analogue of Dr Habilit.),
1990,
·
PhD in Physics & Math (Differential Equations
& Math.Phys), 1980,
·
Diploma, 1973 (Master degree equivalent), Omsk
Pedagogical Institute (Physical Department and Mathematics Department). Thesis:
Sets of Removable Singularities in Banach Spaces and
Continuous Mappings;
·
·
Current Employment
Applied Mathematics Chair,
|
Name and
Address of Current Employe |
Job Title |
|
Dept. of Mathematics, |
Chair in Applied Mathematics (2004-present) Director of the Centre for Mathematical Modelling
(2006-present) |
Employment History:
·
Chief Scientist, 2008-present (on leave);
·
Deputy Director and Head of the Computer Sciences
Department, 1995 – 2005;
·
Head of the Nonequilibrium
Systems Laboratory, 1989 – 2008;
·
Senior researcher, 1983-1989;
·
Junior researcher, 1978-1983;
Institute of
·
Engineer, 1977-1978;
Institute of Theoretical & Applied
·
Engineer, 1978;
Tomsk Polytechnic Institute, Laboratory of Kinetics,
·
Junior researcher, 1977;
·
Junior researcher, 1976;
Omsk Railway Engineering Institute, Research Division,
·
Engineer, 1973-1976.
Part-time:
·
Head of Neurocomputers
Chair, 1993-2006; Professor, 1993-2006 (and now on leave);
Swiss Federal Institute of technology (ETH),
·
Senior Researcher, 2003-2004;
·
Professor, Department of Automatization
and Robots, 1993-2003;
·
Professor, Psychological Department, 1998-2001;
·
Associate professor, Higher Mathematics Chair,
1981-1989;
·
Associate professor, Psychological Department,
1989-1991;
·
Advisor of the
Visiting:
·
Clay Mathematics Institute (
·
Northeastern University (
·
Courant Mathematics Institute (
·
Institut des Hautes Etudes Scientiques (IHES, Paris, France), 10.2000-12.2000, 07.2001-08.2001,11.2002-12-2002, 09.2003;
·
Swiss Federal Institute of technology (ETH,
Expert positions:
·
Vice-Chairman of Scientific Council at
·
Head of Workgroup on Neurocomputing,
Ministry of Science and Technology
·
Vice-Chairman of Expert Council
·
Chairman of the Analytic Games Committee,
·
Member of Jury of USSR National competition in
mathematics for students of technical universities (1986-1990).
·
Full member of Russian Psychological Association
(1989);
·
Director of
·
Active member of
·
Member of Advisory Board of the Russian Neural
Networks Society (1990-present);
·
Associated Member of ASME (American Society of
Mechanical Engineers) (1997);
·
Member of Association CHAOS (Centre for Hyperincursion and Anticipation in Ordered Systems) (2000);
·
Member of Society for Mathematical Biology (2003).
Participant of 61
conferences, including 15 international, positions as a member of organizing
committee or a (co-)chairman at 22 conferences, including 7 international.
Organizer of:
·
International Research workshop: “Principal manifolds for data
cartography and dimension reduction” August 24-26, 2006,
·
International Workshop “Geometry of Genome: Unravelling of Structures Hidden in Genomic
Sequences,”
·
International Workshop “Model
Reduction and Coarse-Graining Approaches for Multiscale
Phenomena,”
·
International Workshop "Invariance and Model Reduction
for Multiscale Phenomena,"
·
USA-NIS Neurocomputing
Opportunities Workshop,
·
Russian annual National Conference “Neurionformatics” (1998-present);
·
Russian annual National Workshops “Neuroinformatics and Application,”
·
Russian annual National Workshops “Modeling of Nonequilibrium Systems,”
·
Russian National Conference “Problems of Regional Informatization”,
·
Soviet Union National competition in Neuroinformatics and Neurocomputers
for students and young scientists, 1991.
Grants and awards:
·
Elsevier
Most Cited in 2003-2006 Paper Award for the paper: Gorban, A.N.;Karlin,
I.V., Method of invariant manifold for
chemical kinetics, Chem.
·
Mathematical
Modelling of Adaptation and Decision-Making in
Neural Systems, The Royal
·
Modularity,
Abstraction and Robustness of Network Models in Molecular Biology,
·
EPSRC and LMS grants for the International Workshop “Model Reduction and Coarse-Graining
Approaches for Multiscale Phenomena,”
·
Prigogine Prize and Medal (2003,
·
Clay Scholar, (Clay Mathematics Institute,
·
Russian Federal Grant of the “Integration” program,
4 times (1998-2003);
·
Grant of Russian Federal subprogram “New Information
Processing Technology” (1999);
·
Soros Professor (grant of International Science
Foundation) (1998);
·
Russian Federal Fellowship for outstanding
scientists, twice (6 years);
·
Grant of Russian Foundation of Basic Research
(1996-1998);
·
Grants of Regional Scientific Foundation,
·
1994-1996 American Mathematical Society Fellowship.
Scientific advisor of 22 PhD thesis and 3 Dr. Habilit. (Dr.
Sc.), including:
·
E.M. Mirkes, The structure
and functioning of ideal neurocomputer (Dr. Habilt., Computer Science, 2002);
·
E.V. Smirnova, Measurement
and modeling of adaptation (Dr. Habilt., Modeling in
Biophysics, 2001);
·
D.A. Rossiev, Neural
networks based expert systems for medical
diagnostics (Dr. Habilt., Biophysics, 1997);
·
A.Yu. Zinovyev,
Method of Elastic Maps for Data Visualization: Algorithms, Software and
Applications in Bioinformatics (PhD, Computer Science, 2001);
·
V.G. Tzaregorodtzev,
Algorithms, technology and software for knowledge extraction using trainable
neural networks (Ph. D., Computer Science, 2000);
·
A.A. Pitenko, Neural
networks for geoinformatics (Ph. D., Computer
Science, 2000);
·
A.A. Rossiev, Neural
network modeling of data with gaps (Ph. D., Computer Science, 2000);
·
M.Yu. Senashova, Accuracy estimation for neural networks (Ph. D.,
Computer Science, 1999);
·
M.A.Dorrer, Psychological
intuition of neural networks (Ph. D., Computer Science, 1999);
·
I.V. Karlin, Method of invariant manifold in
physical kinetics, (PhD, Physics, 1991);
·
V.I.Verbitsky, Simultaneously
dissipative operators and global stability (PhD, Mathematical Analysis, 1989);
·
M.G. Sadovskii,
Optimization in space distributions of populations, (PhD, Biophysics, 1989);
·
V.A. Okhonin, Kinetic
equations for population dynamics (PhD, Biophysics, 1986).
Leader of 18 full-scale
Analytic Games, including:
"Project of a Free Economic Zone for the
"Problems of Russian Culture" (Krasnoyarsk, June 1991);
"Critical Situations in a Transfer to
Market" (Krasnoyarsk, December 1990).
Co-organizer of 15
Organizer of 2 Tobolsk Summer Schools for Talented Children.
Selected Publications
Monographs (in reverse
chronological order):
10. Kinetic
Models of Catalytic Reactions (Comprehensive
Chemical Kinetics, V.32, ed. by R.G. Compton), Elsevier,
Articles
(in
reverse chronological order):
1.
Ovidiu Radulescu, Alexander N Gorban, Andrei
Zinovyev, and Alain Lilienbaum Robust simplifications of multiscale biochemical networks, BMC Systems Biology 2008, 2:86 doi:10.1186/1752-0509-2-86.
2.
A.N. Gorban and O. Radulescu, Dynamic and Static Limitation
in Multiscale Reaction Networks, Revisited, Advances in Chemical Engineering 34 (2008), 103-173.
3.
A. N. Gorban, Selection Theorem for Systems with Inheritance, Math. Model. Nat. Phenom.,
Vol. 2, No. 4, 2007, pp. 1-45.
4.
R. A. Brownlee, A. N. Gorban, and J. Levesley, Nonequilibrium entropy limiters in lattice Boltzmann methods, Physica A: Statistical Mechanics and its Applications Volume 387, Issues 2-3, 15 January 2008, Pages 385-406
.
5.
A.N. Gorban and O.
Radulescu, Dynamical robustness of biological networks
with hierarchical distribution of time scales, IET Syst. Biol., 2007, 1, (4), pp. 238–246.
6.
R. A. Brownlee, A. N. Gorban, and J.
Levesley, Stability and stabilization of the lattice Boltzmann method, Phys. Rev. E 75, 036711 (2007) (17 pages)
7.
A.N. Gorban and A.Y. Zinovyev The Mystery of Two
Straight Lines in Bacterial Genome Statistics, Bulletin of Mathematical Biology (2007)
8. E. Chiavazzo, A.N. Gorban, and I.V. Karlin, Comparison
of Invariant Manifolds for Model Reduction in Chemical Kinetics, Commun. Comput. Phys. Vol. 2,
No. 5 (2007), pp. 964-992
9. A.N.
Gorban, N.R. Sumner, and A.Y. Zinovyev, Topological
grammars for data approximation, Applied Mathematics Letters Volume
20, Issue 4 (2007), 382-386
10. A.N.
Gorban, Order–disorder
separation: Geometric revision, Physica A Volume
374, Issue 1 , 15 January 2007, Pages 85-102
11. A.N. Gorban and O. Radulescu, Dynamical
robustness of biological networks with hierarchical distribution of time scales,
IET Syst. Biol., 2007, 1, (4), pp. 238–246
12. R.A.
Brownlee, A.N. Gorban, and J. Levesley, Stabilization of the lattice Boltzmann
method using the Ehrenfests' coarse-graining idea, Phys. Rev. E 74, 037703 (2006)
13. A. Gorban,
14. A.N.
Gorban, I.V. Karlin, Quasi-Equilibrium Closure Hierarchies for the Boltzmann
Equation, Physica A 360 (2006) 325–364
15. A.
Gorban, A. Zinovyev, Elastic Principal Graphs and Manifolds and their Practical
Applications, Computing 75, 359–379
(2005),
16. A.N.
Gorban, I.V. Karlin, Invariance
correction to Grad's equations: Where to go beyond approximations? Continuum Mechanics and Thermodynamics, 17(4) (2005), 311–335,
17. A.N.
Gorban, T.G.Popova, A.Yu. Zinovyev, Codon usage
trajectories and 7-cluster structure of 143 complete bacterial genomic
sequences •Physica
A: Statistical and Theoretical Physics, 353C (2005), 365-387.
18. A.N.
Gorban, T.G.Popova, A.Yu. Zinovyev, Four basic symmetry types in the universal
7-cluster structure of microbial genomic sequences, In Silico
Biology, 5 (2005), 0039.
19. A.N.
Gorban, P.A.Gorban, and
20. A.N.
Gorban, I.V. Karlin, A.Yu. Zinovyev, Constructive
methods of invariant manifolds for kinetic problems, Physics Reports, V. 396, N 4-6 (2004), p. 197-403.
21. A.N.
Gorban, I.V. Karlin, A.Yu. Zinovyev, Invariant grids
for reaction kinetics, Physica A, 333 (2004), 106--154.
22. A.N.
Gorban, I.V. Karlin, Uniqueness of thermodynamic projector and kinetic basis of
molecular individualism, Physica A, 336, 3-4 (2004), 391-432.
23. A.N.
Gorban, I.V. Karlin, Methods of nonlinear kinetics, in: Encyclopedia
of Life Support Systems, Encyclopedia of Mathematical Sciences, EOLSS Publishers,
24. A.N.
Gorban, T. G. Popova, and A. Yu. Zinovyev:
Self-organizing approach for automated gene identification. Open Sys. Information Dyn.
10 (2003) 1-13.
25. A.N. Gorban and
I. V. Karlin, Family of additive entropy functions out of thermodynamic limit, Phys. Rev. E. 2003, V.67, 016104,
E-print: http:, arXiv.org/abs/cond-mat/0205511
26. A.N. Gorban, I.
V. Karlin and H. C. Ottinger, The additive
generalization of the Boltzmann entropy. Phys.
Rev. E. (2003), V. 67. E-print: http:,
arXiv.org/abs/cond-mat/0209319.
27. A.N.
Gorban, I. V. Karlin, Method of invariant manifold for chemical kinetics. Chem.
28. I.V.
Karlin, L. L. Tatarinova, A. N. Gorban, and H. C. Öttinger,
Irreversibility in the short memory approximation, Physica A 327 (2003) 399-424.
29. A.
Gorban, A. Zinovyev, T. Popova. Seven clusters in
genomic triplet distributions. In Silico Biology. V.3
(2003), 471-482.
30. A.N. Gorban, T.G Popova, M.G Sadovsky,
Classification of nucleotide sequences over their frequency dictionaries
reveals a relation between the structure of sequences and taxonomy of their
bearers, Zh Obshch Biol 64 (1), 65-77. 2003
31. A. Gorban', Braverman M., Silantyev V.
Modified Kirchhoff flow with a partially penetrable obstacle and its
application to the efficiency of free flow turbines. Math. Comput. Modelling
35 (2002), No. 13, 1371-1375.
32. A. Gorban', Silantyev
V. Riabouchinsky Flow with Partially Penetrable
Obstacle. Math. Comput.
Modelling 35 (2002), no. 13, 1365-1370.
33. I.V. Karlin, M. Grmela, and A.N. Gorban: Duality in nonextensive
statistical mechanics, Phys. Rev. E
65 (2002) 036128.
34. A.N. Gorban and
I. V. Karlin, Reconstruction lemma and fluctuation-dissipation theorem, Revista Mexicana
de Fisica, 2002. V. 48 Suplemento
1, PP. 238-242.
35. A.N. Gorban and
I. V. Karlin, Geometry of irreversibility, in: Recent Developments in Mathematical and Experimental Physics,
Volume C: Hydrodynamics and Dynamical
Systems, Ed. F. Uribe (Kluwer,
36. A.N. Gorban and
I. V. Karlin, Macroscopic dynamics through coarse-graining: A solvable example,
Phys. Rev. E. V 65. 026116(1-5)
(2002).
37.
I.V. Karlin and A.N. Gorban, Hydrodynamics from
Grad's equations: What can we learn from exact solutions? Ann. Phys. (Leipzig) 10-11 (2002), pp. 783-833.
E-print: http:, arXiv.org/abs/cond-mat/0209560
38. A.N. Gorban, Zinov'ev A.Y., Pitenko A.A., Data vizualization. The method of
elastic maps, Neirocompjutery, 2002, 4, 19-30.
39. A.N. Gorban, A.A Rossiev, Iterative modeling of data with gaps via submanifolds of small dimension, Neirocompjutery, 2002, 4, 40-44.
40. A. Gorban, Rossiev A., Makarenko N., Kuandykov Y., Dergachev V.
Recovering data gaps through neural network methods. International Journal of Geomagnetism and Aeronomy,
2002, Vol. 3, No. 2, December 2002.
41. A.N. Gorban, V.T.
Manchuk, A.V.Perfil’eva, E.V.Smirnova, E.P. Cheusova, The
mechanism of increasing the correlation between physiological parameters for
high adaptation tension, Siberian
Ecological Journal, 2001, No 5, 651-655.
42. A.N. Gorban, Gorlov A.M., Silantyev V.M.
Limits of the turbin efficiency for free fluid flow, ASME Journal of Energy
Resourses Technology, Dec. 2001, V. 123, Iss.
4, pp. 311-317.
43. A.N. Gorban, Pitenko A.A., Zinov'ev A.Y.,
Wunsch D.C. Vizualization of any data uzing elastic map method ,
Smart Engineering System Design. 2001, V.11, p. 363-368.
44. A.N. Gorban, Popova T.G., Sadovsky M.G., Wunsch
D.C. Information content of the frequency dictionaries, reconstruction,
transformation and classification of
dictionaries and genetic texts. Smart
Engineering System Design, 2001, V.11, p. 657-663.
45. A.N.Gorban, I.V.Karlin, P.Ilg and H.C.Ottinger Corrections and enhancements of
quasi-equilibrium states, J.
Non-Newtonian Fluid Mech., 2001,
V.96(1-2), PP. 203-219.
46. A.N. Gorban,
Karlin I.V., Ottinger H.C., Tatarinova L.L. Ehrenfest's argument extended to a formalism of nonequilibrium thermodynaics, Phys. Rev. E. 2001, V. 63. 066124.
47. A.N. Gorban, Gorbunova K.O.,
48. A.N. Gorban,
Zinovyev A. Yu. Method of Elastic Maps and its Applications in Data
Visualization and Data Modeling. International
Journal of Computing Anticipatory Systems, CHAOS. 2001. V. 12. PP. 353-369.
49. V.A. Dergachev, Gorban A.N., Rossiev
A.A., Karimova L.M., Kuandykov
E., Makarenko N.G., Steier.
The filling of gaps in geophysical time series by artificial neural networks, Radiocarbon, 2001, V. 43, No. 2, PP.
343-348.
50. A.N.Gorban, V.P.Torchilin, M.V.Malyutov, M.
Lu Modeling polymer brushes protective action , Simulation
in Industry' 2000. Proceedings of 12-th European Simulation Symposium
ESS'2000. September 28-30, 2000,
51. A.N.Gorban, Neuroinformatics: What are us, where are we going, how to
measure our way? Informacionnye technologii,
2000, 4. - С. 10-14.
52. A.N. Gorban, K.
O. Gorbunova, Liquid Brain: Kinetic Model of Structureless Parallelism, Internation Journal of Computing Anticipatory Systems, CHAOS, V. 6, 2000,
P.117-126.
53. A.N. Gorban, I.V.
Karlin, V.B. Zmievskii and S.V. Dymova,
Reduced description in reaction kinetics,
Physica A, 2000. V. 275, No. 3-4, PP. 361-379.
54. A.N Gorban, The
generalized Stone approximation theorem for arbitrary algebras of continuous
functions, Dokl Akad Nauk, 365 (5), 586-588, 1999
55. A.N. Gorban, A.A Rossiev, Neural network iterative method of principal
curves for data with gaps, J Comput Sys Sc Int, 38 (5): 825-830, 1999.
56. A.N. Gorban, I.V.Karlin and V.B.Zmievskii,
Two-step approximation of space-independent relaxation, Transp.Theory Stat.Phys., 1999. V. 28(3), PP. 271-296.
57. A.N. Gorban,
Approximation of Continuous Functions of Several Variables by an Arbitrary
Nonlinear Continuous Function of One Variable, Linear Functions, and Their Superpositions. Appl.
Math. Lett.,
1998. V. 11, No. 3, pp. 45-49.
58. S.E. Gilev, A.N. Gorban, The completeness theorem for semigroups of continuous functions, Dokl Akad Nauk, 362
(6): 733-734, 1998
59. N.N.Bugaenko, A. N. Gorban, M.G.Sadovskii, Maximum entropy method in analysis of
genetic text and measurement of its information content , Open systems and information
dynamics. #5, 1998. - pp.265-278.
60. A.N. Gorban, Neuroinformatics and applications, Otkrytye sistemy (Open Systems), 1998, No. 4-5.
pp. 36-41.
61. A.N. Gorban, I.V.
Karlin, Sroedinger operator in a overfull set , Europhys. Lett., 1998, V. 42, No.2, pp. 113-117.
62. I.V. Karlin, A.
N. Gorban, S. Succi, V. Boffi, Maximum
Entropy Principle for Lattice Kinetic Equation , Physical
Review Letters, 1998, V. 81, No. 1, pp. 6-9.
63. A.N. Gorban, Yeugenii
M. Mirkes and Donald Wunsch, High Order Orthogonal
Tensor Networks: Information Capacity and Reliability, Proc. IEEE/INNS International Conference on Neural Networks,
64. A.N. Gorban, Masha Yu. Senashova and Donald
Wunsch, Back-Propagation of Accuracy, Proc.
IEEE/INNS International Conference on Neural Networks,
65. N.N. Bugaenko, A. N. Gorban, M.G.Sadovskii,
Information content of nucleotid sequences and their
fragments. Biofizika. 1997. V. 42, Iss.
5, pp. 1047-1053.
66. V.I. Bykov, A.N. Gorban, S.V. Dymova,
Method of invariant manifolds for the reduction of kinetic description, ACH-Models Chem 134
(1): 83-95 1997
67. A.N. Gorban, I.V.Karlin, Scattering rates versus moments: Alternative
Grad equations, Phys. Rev. E, 1996,
54(4), R3109.
68. A.N. Gorban, I.V.Karlin, Short-Wave Limit of Hydrodynamics: A Soluble
Example, Phys. Rev. Lett.,
1996, V. 77, N. 2, P. 282-285.
69. N.N. Bugaenko, A.N. Gorban, M.G. Sadovskii,
Information content in nucleotide sequences, Mol Biol, 30 (3): 313-320, 1996.
70. A.N. Gorban, T.G.
Popova, M.G. Sadovskii,
Human virus genes are less redundant than human genes, Genetika, 32 (2), 289-294, 1996.
71. A.N. Gorban, I.V.Karlin, V.B.Zmievskii, T.F.Nonnenmacher, Relaxational
trajectories: global approximations, Physica A, 1996, V.231, No.4, p.648-672.
72. A.N. Gorban, D.N.Golub, Multi-Particle Networks for Associative Memory, Proc. of the World Congress on Neural Networks,
Sept. 15-18, 1996, San Diego, CA, Lawrence
Erlbaum Associates, 1996, pp. 772-775.
73. S.E. Gilev, A. N. Gorban, On Completeness of the Class of
Functions Computable by Neural Networks, Proc.
of the World Congress on Neural Networks, Sept. 15-18, 1996, San Diego, CA, Lawrence Erlbaum Associates,
1996, pp. 984-991.
74. A.N. Gorban, D.A.
Rossiyev, E.V. Butakova,
S.E. Gilev, S.E. Golovenkin,
S.A. Dogadin, D.A. Kochenov,
E.V. Maslennikova, G.V. Matyushin,
Y.E. Mirkes, B.V. Nazarov,
Medical and Physiological Applications of MultiNeuron
Neural Simulator. Proceedings of the 1995
World Congress On Neural Networks, A Volume in the INNS Series of Texts,
Monographs, and Proceedings, Vol. 1, 1995.
75. M.G. Dorrer, A.N. Gorban, A.G. Kopytov,
V.I. Zenkin, Psychological Intuition of Neural
Networks. Proceedings of the 1995 World
Congress On Neural Networks, A Volume in the INNS Series of Texts,
Monographs, and Proceedings, Vol. 1, 1995.
76. A.N. Gorban, C.
Waxman, Neural Networks for Political Forecast. Proceedings of the 1995 World Congress On Neural Networks, A
Volume in the INNS Series of Texts, Monographs, and Proceedings, Vol. 1, 1995.
77. A.N. Gorban, T.G.
Popova, M.G. Sadovskii,
Redundancy of genetic texts, Mol Biol, 28 (2), 206-213, 1994.
78. A.N. Gorban, T.G.
Popova, M.G. Sadovskii,
Correlation approach to comparing nucleotide-sequences, Zh Obshch Biol,
55 (4-5), 420-430, 1994.
79. A.N. Gorban, I.V.
Karlin, General approach to constructing models of the Boltzmann equation, Physica A, 206 (1994), 401-420.
80. A.N. Gorban, I.V.
Karlin, Method of invariant manifolds and regularization of acoustic spectra, Transport Theory and Stat. Phys., 23,
559-632, 1994.
81. A.N. Gorban, E.M.
Mirkes, T.G. Popova, M.G. Sadovskii, A new approach to the investigations of
statistical properties of genetic texts, Biofizika 38 (5), 762-767, 1993.
82. A.N. Gorban, E.M.
Mirkes, T.G. Popova, M.G. Sadovskii, The comparative redundancy of genes of various
organisms and viruses, Genetika 29 (9), 1413-1419, 1993.
83. A.N. Gorban, I.V.Karlin, Structure and Approximations of the Chapman-Enskog Expansion for Linearized
Grad Equations, Transport Theory and Stat.Phys, V.21, No 1&2, P.101-117, 1992.
84. V.I. Verbitskii, A.N. Gorban, Jointly dissipative operators and
their applications, Siberian Math J,
33 (1), 19-23, 1992.
85. A.N. Gorban, E.M.
Mirkes, A.P. Svitin, Method
of multiplet covering and its application for the
prediction of atom and molecular-properties, Zh Fiz Khim, 66
(6): 1504-1510, 1992.
86. V.I. Bykov, V.I. Verbitskii, A.N.
Gorban, Evaluation of cauchy-problem solution with
inaccurately given initial data and the right part, Izv Vuz Mat, (12), 5-8, 1991.
87. A.N. Gorban, V.I.Verbitsky, Simultaneously Dissipative Operators and
Quasi-Thermodynamicity of the Chemical Reactions
Systems, Advances in Modelling
and Simulation, 1992, V.26, N1,
p.13-21.
88. N.N. Bugaenko, A. N. Gorban, I.V.Karlin Universal Expansion of the Triplet
Distribution Function, Teoreticheskaya i Matematicheskaya Fisica,
V.88, No.3, P.430-441(1991).
89. A.N. Gorban, I.V.Karlin, Approximations of the Chapman-Enskog Expansion, Zh.Exp.Teor.Fis., V.100, No.4(10), P.1153-1161(1991); Sov. Phys. JETP, V.73(4), P.637-641.(1991).
90. S.Ye. Gilev, A. N. Gorban and E.M. Mirkes,
Small Experts and Internal Conflicts in Learnable Neural Networks, Doklady Acad. Nauk SSSR, V.320, No.1, (1991) P.220-223.
91. A.N. Gorban, E.M.
Mirkes, A.N. Bocharov, V.I.
Bykov,
Thermodynamic consistency of kinetic data, Combust Explosion & Shock, 25 (5), 593-600, 1989.
92. V.I. Verbitskii, A.N. Gorban, G.S. Utiubaev,
Y.I. Shokin, Moores effect
in interval spaces, Dokl Akad Nauk SSSR, 304 (1), 17-21 1989.
93. A.N. Gorban, M.G.
Sadovskii, Optimal strategies of spatial-distribution
- Olli effect, Zh Obshch Biol 50 (1), 16-21, 1989.
94. A.N. Gorban, K.R.Sedov and E.V.Smirnova,
Correlation Adaptometry as a Method for Measuring the
Health, Vestnik Acad. Medic. Nauk
SSSR, No.5, P.69-75(1989).
95. V.I.Bykov, A. N. Gorban, A
Model of Autooscillations in Association Reactions, Chem.Eng.Sci., V.42, No.5,
P.1249-1251(1987).
96. A.N. Gorban, M.G.Sadovskii, Evolutionary Mechanisms of Creation of
Cellular Clusters in Flowrate Cultivators,
Biotechnology and Biotechnics, No.5, P.34-36(1987).
97. V.I.Bykov, A. N. Gorban, G.S.Yablonskii. Thermodynamic Function Analogue for
Reactions Proceeding Without Interactions of Various Substances, Chem.Eng.Sci., V.41, No.11,
P.2739-2745 (1986).
98. V.I. Bykov, S.E. Gilev, A.N. Gorban,
G.S. Yablonskii, Imitation modeling of the diffusion
on the surface of a catalyst, Dokl Akad Nauk SSSR, 283 (5):
1217-1220 1985.
99. V.I. Bykov, A.N. Gorban, Simplest model of self-oscillations in
association reactions, React Kinet Catal Lett,
27 (1): 153-155 1985
100.
V.I. Bykov, A.N. Gorban,
T.P. Pushkareva, Autooscillation
model in reactions of the association, Zh Fiz
Khim, 59 (2): 486-488, 1985.
101.
A.N. Gorban, V.I. Bykov,
G.S. Yablonskii, Description of non-isothermal
reactions using equations of nonideal
chemical-kinetics, Kinet Catal, 24
(5), 1055-1063, 1983.
102.
V.I. Bykov, A.N. Gorban,
L.P. Kamenshchikov, G.S. Yablonskii,
Inhomogeneous stationary states in reaction of carbon-monoxide oxidation on
platinum, Kinet
Catal, 24 (3), 520-524, 1983
103.
V.I. Bykov, A.N. Gorban, Quasithermodynamic characteristic of reactions without the
reaction of different substances, Zh Fiz
Khim, 57 (12), 2942-2948, 1983.
104.
V.I. Bykov, A.N. Gorban,
G.S. Yablonskii, Description of non-isothermal
reactions in terms of Marcelin-De-Donder
kinetics and its generalizations, React Kinet Catal Lett,
20 (3-4), 261-265, 1982.
105.
S.E. Gilev, A.N. Gorban,
V.I. Bykov, G.S. Yablonskii,
Simulative modeling of processes on a catalyst surface, Dokl Akad Nauk SSSR, 262
(6), 1413-1416, 1982.
106.
V.I. Elokhin, G.S. Yablonskii, A.N. Gorban, V.M. Ceresiz,
Dynamics of chemical-reactions and non-physical steady-states, React Kinet Catal Lett, 15 (2), 245-250,
1980.
107.
A.N. Gorban, G.S. Yablonskii,
On one unused possibility in the kinetic experiment
design, Dokl Akad Nauk SSSR, 250 (5):
1171-1174, 1980.
108.
A.N. Gorban, V.I. Bykov,
G.S. Yablonskii, The Path to
Equilibrium, Intern. Chem.
109.
A.N. Gorban, V.M.Ceresiz,
Slow Relaxations of Dynamical Systems and Bifurcations of Omega-Limit Sets, Soviet Math. Dokl.,
V.24, P.645-649(1981).
110.
A.N. Gorban, V.I. Bykov,
G.S. Yablonskii, Macroscopic Clusters Induced by
Diffusion in Catalytic Oxidation Reactions, Chem.
111.
A.N. Gorban, V.I.Bykov, V.I.Dimitrov. Marcelin-De Donder Kinetics Near Equilibrium, React. Kinet. Catal.
Lett.,
V.12, No.1, P.19-23(1979).
112.
A.N. Gorban, Priori evaluation of the region of
linearity for kinetic-equations, React Kinet Catal Lett,
10 (2), 149-152, 1979
113.
A.N. Gorban, Invariant Sets for Kinetic Equations, React. Kinet. Catal. Lett., 1979, V.10, P.187-190.
114.
A.N. Gorban, Sets of
Removable Singularities and Continuous Mappings, Siberian Math. Journ., V.19, P.1388-1391(1978).
115.
A.N. Gorban, V.B. Melamed,
Certain properties of Fredholm analytic sets in Banach-spaces, Siberian
Math J, 17 (3), 523-526, 1976.
Past Achievements and Future
Research
A collection of methods for construction of slow
invariant manifolds has been developed, in particular the analogue of Kolmogorov-Arnold-Moser methods for dissipative systems.
The nonperturbative deviation of physically
consistent hydrodynamics from the Boltzmann equation and from reversible
dynamics, for Knudsen numbers
near one, was obtained.
The theory of simultaneously dissipative operators and
tools for global stability analysis were developed. An explicitly solvable
mathematical model for estimating the maximum efficiency of turbines in a free
(non-ducted) fluid was obtained. This result can be used for hydropower
turbines where construction of dams is impossible or undesirable.
A family of fast training algorithms for neural networks
and generalized technology of extraction of explicit knowledge from data was
developed. These algorithms are now in use in medical expert systems and in
anti-terrorism security systems in
The geometric seven-cluster structure of the genome was
discovered.
The
Geometry of Irreversibility. A new general geometrical framework of nonequilibrium thermo-dynamics will be developed. Our
approach is based on constructive methods of invariant manifolds elaborated
during the past two decades. The new methods allow us to solve the problem of
macro-kinetics even when there are no autonomous equations of macro-kinetics.
These methods will be elaborated together with computational algorithms. Each
step of these algorithms should be physically consistent. The notion of the
invariant film of non-equilibrium states, and the
method of its approximate construction transform the problem of nonequilibrium kinetics into a series of problems of
equilibrium statistical physics. The main specific problem for application of
developed methods will be the problem of dynamic memory appearance in
macromolecular complexes. Such memory effects may be important for chromatin
dynamics and its role in functional nuclear organization. Spatio-temporal
organization of chromatin will be studied.
Results
and Projects (1971-2004)
1.
The beginning (1971-1975)
Two scientific contacts
determined my scientific work during 1971-1975: Prof. V.P. Mikheev
(technical sciences) and Prof. V.B. Melamed
(functional analysis). With Prof. Mikheev we created
models of contact net and contact devices and developed new stations for
technical diagnosis. Perhaps the main results of our collaboration are:
stations for technical diagnosis that were in use on the
Prof. Melamed
was from the
2.
Chemical kinetics and topological dynamics (1975-1980)
3.
Biological kinetics and functional analysis (1980-1990)
Does the
dynamics of distributed systems which models biological evolution always
lead to a discrete distribution? (In the biological context this question can
be reformulated as follows: is natural selection really effective if the
initial diversity is sufficiently rich?)
In order to answer this question, a theory of special dynamical systems
in the space of Radon measures on compact space was developed. These are systems with a specific
conservation law: the conservation of support of measures. There are
characterization theorems for omega-limit points, and different theorems about
efficiency of natural selection. The qualitative picture of these results was
summarized in the book: Demon of
This abstract theory has
found very practical application. My former PhD student, E. V. Smirnova (now Professor Smirnova)
discovered that the approximate dimension of the cloud of physiological data of
a group precisely characterizes the level of adaptation of this group to the
living conditions: when the group members exhaust their adaptation resource
then the dimension usually decreases. It
decreases usually, but not always.
Sometimes the dimension goes another way. We explained the effect, and,
on the other hand, predicted the exclusions. The results were confirmed by
thousands of experiments with different populations and groups: from human to
plants and fungi. Now the developed concept of correlation adaptometry is in use for
monitoring needs in
4.
Neural networks (1985-now)
In 1985 I stated the problem
of effective parallelism as a main problem for our group for the next decade.
In 1986 V. Okhonin (former PhD student) published a
new algorithm for training neural networks (for synchronized and
non-synchronized networks, for discrete and continuous time, for systems with
delays in time, and for many other cases).
The central idea was the flexible use of duality (it is a rather usual
step in optimization methods). (At the same time, Rumelhart D.E., Hinton G.E., Williams
R.J. published a particular case of this algorithm that became famous under the
name “back propagation of errors”.) For several years we tried to make the
training algorithms faster, and network skills more stable. During an interval
of fifteen years (1987-2002) we developed a generalized technology of
extraction of explicit knowledge from data.
This technology was implemented in a series of software libraries and
allowed us to create dozens of knowledge-based expert systems in medical and
technical diagnosis, ecology and other fields.
On the base of this approach, the
Russian Close Corporation "Applied Radiophysics
- Security Systems" developed neural network-based security systems (1997
– 2003). This Russian system "Voron" was
the laureate of the international exhibition "Frontier-2000" (see http://etic-m.narod.ru/company.htm, http://www.grand-prix.ru/catalogue/perimeter/voron/solution/ (in Russian).
The results were summarized in
several monographs, 16 PhD theses were submitted, and 3 scientists prepared
Doctor of Science degrees. The developed software is in widespread use in the
former
5.
Physical Kinetics and Invariant Manifolds (1977-present)
The concept of
the slow invariant manifold is recognized as the central idea underpinning a
transition from micro to macro and model reduction in kinetic theories. We developed
constructive methods of invariant manifolds for model reduction in physical and
chemical kinetics. The physical problem of a reduced description is studied in
the most general form as a problem of constructing the slow invariant manifold.
A collection of methods to derive analytically and to compute numerically the
slow invariant manifold is elaborated. Among them, iteration methods based on
incomplete linearization, relaxation methods and the method of invariant grids
have been developed. The systematic use of thermodynamic structures and of the
quasi-chemical representation allows us to construct approximations which are
consistent with physical restrictions at each step.
There are many
examples of applications: nonperturbative derivation
of physically consistent hydrodynamics from the Boltzmann equation and from
reversible dynamics, for Knudsen numbers Kn near one;
construction of the moment equations for nonequilibrium
media and their dynamical correction in order to gain more accuracy in the
description of highly nonequilibrium flows; the
kinetic theory of phonons; model reduction in chemical kinetics; derivation and
numerical implementation of constitutive equations for polymeric fluids. A review of this direction of work is now published
in Physics Reports.
A new approach to
the lattice Boltzmann method is developed. Beginning from thermodynamic
considerations, the LBM can be recognised as a
discrete dynamical system generated by entropic involution and free-flight and
the stability analysis is more natural. We solve the stability problem of the
LBM on the basis of this thermodynamic point of view. The main instability
mechanisms are identified. The simplest and most effective receipt for stabilisation adds no artificial dissipation, preserves
the second-order accuracy of the method, and prescribes coupled steps: to start
from a local equilibrium, then, after free-flight, perform the overrelaxation collision, and after a second free-flight
step go to new local equilibrium. Two other prescriptions (“salvation rules”) add some artificial
dissipation locally and prevent the system from loss of positivity and local
blow-up.
6.
Bioinformatics and Geometry of Genome (1990-now)
Is it possible to study the
genetic text on the same way as A. Kolmogorov
studied poetry? Is there a footprint of biological sense in statistical
features of the genome? This question needs to be carefully solved. The result
may be positive or negative.
Nevertheless, we should study this problem. We have investigated a numbe
of questions in this direction.
Some positive results have
been obtained and published during the past fourteen years. In particular, the
clear seven-cluster structure of genome was identified. We studied cluster
structure of several genomes in the space of olygomer
frequencies. The result: many complete genomic
sequences were analyzed, using visualization of tables of triplet counts in
a sliding window. The distribution of 64-dimensional vectors of triplet
frequencies displays a well-detectable
cluster structure. The structure was found to consist of seven
clusters, corresponding to protein-coding information in three possible
phases in one of the two complementary strands and in the non-coding regions.
Awareness of the existence of this structure allows development of methods for
the segmentation of sequences into regions with the same coding phase and
non-coding regions. This method
may be completely unsupervised.