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Evgeni Selkov

dblp:05/244 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 1999
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 74% Computational science and engineering · 26%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational science and engineering › numerical simulation
dynamic simulation
0.011999
Mathematical simulation and analysis of cellular metabolism and regulation · Bioinform. 1999
Bioinformatics and computational biology › systems biology
metabolic modeling
0.011999
Mathematical simulation and analysis of cellular metabolism and regulation · Bioinform. 1999
Bioinformatics and computational biology
systems biology
0.011999
Mathematical simulation and analysis of cellular metabolism and regulation · Bioinform. 1999
Bioinformatics and computational biology › systems biology
metabolic network reconstruction
0.021999
Reconstruction of Metabolic Networks Using Incomplete Information · ISMB 1995
Mathematical simulation and analysis of cellular metabolism and regulation · Bioinform. 1999

Methods — techniques the papers use, named apart from their topics

parameter fitting · 0.0ordinary differential equations · 0.0nonlinear algebraic equations · 0.0constrained optimization · 0.0bifurcation analysis · 0.0
YearPublicationVenuePosition
1999 Mathematical simulation and analysis of cellular metabolism and regulation
abstract
MOTIVATION: A better understanding of the biological phenomena observed in cells requires the creation and analysis of mathematical models of cellular metabolism and physiology. The formulation and study of such models must also be simplified as far as possible to cope with the increasing complexity demanded and exponential accumulation of the metabolic reconstructions computed from sequenced genomes. RESULTS: A mathematical simulation workbench, DBsolve, has been developed to simplify the derivation and analysis of mathematical models. It combines: (i) derivation of large-scale mathematical models from metabolic reconstructions and other data sources; (ii) solving and parameter continuation of non-linear algebraic equations (NAEs), including metabolic control analysis; (iii) solving the non-linear stiff systems of ordinary differential equations (ODEs); (iv) bifurcation analysis of ODEs; (v) parameter fitting to experimental data or functional criteria based on constrained optimization. The workbench has been successfully used for dynamic metabolic modeling of some typical biochemical networks (Dolgacheva et al., Biochemistry (Moscow), 6, 1063-1068, 1996; Goldstein and Goryanin, Mol. Biol. (Moscow), 30, 976-983, 1996), including microbial glycolytic pathways, signal transduction pathways and receptor-ligand interactions. AVAILABILITY: DBsolve 5. 00 is freely available from http://websites.ntl.com/ approximately igor.goryanin. CONTACT: [email protected]
Igor Goryanin, Charlie Hodgman, Evgeni Selkov
Bioinform.3
1995 Reconstruction of Metabolic Networks Using Incomplete Information
Terry Gaasterland, Evgeni Selkov
ISMB2