scholarly journals Computational Modeling of Genetic and Biochemical Networks. * Edited by James M. Bower and Hamid Bolouri * Computational Molecular Biology, A Bradford Book, The MIT Press, Cambridge, Massachusetts; 2004; * ISBN: 0 262 52423 6; Paperback; 390pp.; *  22.95/$35.00.

2006 ◽  
Vol 7 (2) ◽  
pp. 204-206
Author(s):  
S. Schnell
Keyword(s):  
Molecular Biology ◽  
Computational Modeling ◽  
Biochemical Networks ◽  
Computational Molecular Biology

Progress in computational molecular biology

1999 ◽  
Vol 19 (3) ◽  
pp. 9-12 ◽  
Author(s):  
Lawrence Hunter
Keyword(s):  
Molecular Biology ◽  
Computational Molecular Biology

scholarly journals Computational molecular biology approaches to ligand‐target interactions

HFSP Journal ◽  
2009 ◽  
Vol 3 (4) ◽  
pp. 228-239 ◽  
Author(s):  
Paola Lupieri ◽  
Chuong Ha Hung Nguyen ◽  
Zhaleh Ghaemi Bafghi ◽  
Alejandro Giorgetti ◽  
Paolo Carloni
Keyword(s):  
Molecular Biology ◽  
Computational Molecular Biology

Some open problems in computational molecular biology

1999 ◽  
Vol 30 (3) ◽  
pp. 43-49 ◽  
Author(s):  
Tao Jiang ◽  
Paul Kearney ◽  
Ming Li
Keyword(s):  
Molecular Biology ◽  
Open Problems ◽  
Computational Molecular Biology

Systems Biology and Infectious Diseases

2009 ◽  
pp. 377-402 ◽  
Author(s):  
Alia Benkahla ◽  
Lamia Guizani-Tabbane ◽  
Ines Abdeljaoued-Tej ◽  
Slimane Ben Miled ◽  
Koussay Dellagi
Keyword(s):  
Immune Response ◽  
Systems Biology ◽  
Molecular Biology ◽  
Infected Cell ◽  
Regulatory Networks ◽  
Interdisciplinary Approach ◽  
Biochemical Networks ◽  
Mathematical Methods ◽  
Meaningful Information ◽  
Models And Modelling

This chapter reports a variety of molecular biology informatics and mathematical methods that model the cell response to pathogens. The authors first outline the main steps of the immune response, then list the high throughput biotechnologies, generating a wealth of information on the infected cell and some of the immune-related databases; and finally explain how to extract meaningful information from these sources. The modelling aspect is divided into modelling molecular interaction and regulatory networks, through dynamic Boolean and Bayesian models, and modelling biochemical networks and regulatory networks, through Differential/Difference Equations. The interdisciplinary approach explains how to construct a model that mimics the cell’s dynamics and can predict the evolution and the outcome of infection.

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