Quantitative and Probabilistic Modeling in Pathway Logic

Author

Abate, Alessandro ; Bai, Yu ; Sznajder, Nathalie ; Talcott, Carolyn ; Tiwari, Ashish

Author_Institution

Univ. of California at Berkeley, Berkeley

fYear

2007

fDate

14-17 Oct. 2007

Firstpage

922

Lastpage

929

Abstract

This paper presents a study of possible extensions of pathway logic to represent and reason about semiquantitative and probabilistic aspects of biological processes. The underlying theme is the annotation of reaction rules with affinity information that can be used in different simulation strategies. Several such strategies were implemented, and experiments carried out to test feasibility, and to compare results of different approaches. Dimerization in the ErbB signalling network, important in cancer biology, was used as a test case.

Keywords

association; biochemistry; cancer; enzymes; medical computing; molecular biophysics; physiological models; probability; ErbB signalling network; annotation; biological processes; cancer biology; dimerization; pathway logic; probabilistic modeling; quantitative modeling; reaction rules; Biological processes; Biological system modeling; Biophysics; Cancer; Mathematical model; Probabilistic logic; Proteins; Stochastic systems; Testing; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Bioengineering, 2007. BIBE 2007. Proceedings of the 7th IEEE International Conference on

Conference_Location

Boston, MA

Print_ISBN

978-1-4244-1509-0

Type

conf

DOI

10.1109/BIBE.2007.4375669

Filename

4375669