Computation of probabilities in an enzyme reaction network

Xueying Zhang; Katrien De Cock; Mónica F. Bugallo; Petar M. Djurić

Computation of probabilities in an enzyme reaction network

Xueying Zhang
, Katrien De Cock
, Mónica F. Bugallo
, Petar M. Djurić

Stony Brook University

Stony Brook University

Research output: Contribution to journal › Conference article › peer-review

Abstract

The study of the stochastic properties of enzyme reactions are extremely valuable for understanding life processes. In this paper, we present a new approach for the computation of probability distributions in enzyme reaction networks. By employing system theory and block diagrams, the new approach offers a visible and convenient way to decompose a complicated network into simpler sub-networks and vice versa. An enzyme catalyst reaction is analyzed and the results for both the transient and steady states of the reaction are obtained.

Original language	English
Pages (from-to)	1646-1650
Number of pages	5
Journal	Conference Record of the Asilomar Conference on Signals, Systems and Computers
Volume	2
State	Published - 2004
Event	Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States Duration: Nov 7 2004 → Nov 10 2004

Cite this

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title = "Computation of probabilities in an enzyme reaction network",

abstract = "The study of the stochastic properties of enzyme reactions are extremely valuable for understanding life processes. In this paper, we present a new approach for the computation of probability distributions in enzyme reaction networks. By employing system theory and block diagrams, the new approach offers a visible and convenient way to decompose a complicated network into simpler sub-networks and vice versa. An enzyme catalyst reaction is analyzed and the results for both the transient and steady states of the reaction are obtained.",

author = "Xueying Zhang and \{De Cock\}, Katrien and Bugallo, \{M{\'o}nica F.\} and Djuri{\'c}, \{Petar M.\}",

year = "2004",

language = "English",

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journal = "Conference Record of the Asilomar Conference on Signals, Systems and Computers",

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note = "Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers ; Conference date: 07-11-2004 Through 10-11-2004",

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TY - JOUR

T1 - Computation of probabilities in an enzyme reaction network

AU - Zhang, Xueying

AU - De Cock, Katrien

AU - Bugallo, Mónica F.

AU - Djurić, Petar M.

PY - 2004

Y1 - 2004

N2 - The study of the stochastic properties of enzyme reactions are extremely valuable for understanding life processes. In this paper, we present a new approach for the computation of probability distributions in enzyme reaction networks. By employing system theory and block diagrams, the new approach offers a visible and convenient way to decompose a complicated network into simpler sub-networks and vice versa. An enzyme catalyst reaction is analyzed and the results for both the transient and steady states of the reaction are obtained.

AB - The study of the stochastic properties of enzyme reactions are extremely valuable for understanding life processes. In this paper, we present a new approach for the computation of probability distributions in enzyme reaction networks. By employing system theory and block diagrams, the new approach offers a visible and convenient way to decompose a complicated network into simpler sub-networks and vice versa. An enzyme catalyst reaction is analyzed and the results for both the transient and steady states of the reaction are obtained.

UR - https://www.scopus.com/pages/publications/21644441803

M3 - Conference article

SN - 1058-6393

VL - 2

SP - 1646

EP - 1650

JO - Conference Record of the Asilomar Conference on Signals, Systems and Computers

JF - Conference Record of the Asilomar Conference on Signals, Systems and Computers

T2 - Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers

Y2 - 7 November 2004 through 10 November 2004

ER -

Computation of probabilities in an enzyme reaction network

Abstract

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