Literature DB >> 15922580

The Silicon Cell initiative: working towards a detailed kinetic description at the cellular level.

Jacky L Snoep1.   

Abstract

The Silicon Cell initiative aims to understand cellular systems on the basis of the characteristics of their components. As a tool to achieve this, detailed kinetic models at the network reaction level are being constructed. Such detailed kinetic models are extremely useful for medical and biotechnological applications and form strong tools for fundamental studies. Several recently constructed detailed kinetic models on metabolism (glycolysis), signal transduction (EGF receptor), and the eukaryotic cell cycle (Saccharomyces cerevisiae) have been used to exemplify the Silicon Cell project. These models are stored and made accessible via the JWS Online Cellular Systems Modeling project, a web-based repository of kinetic models. Using a web-browser the models can be interrogated via a user-friendly graphical interface. The goal of the two projects is to combine models on parts of cellular systems and ultimately to construct detailed kinetic models at the cellular level.

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Year:  2005        PMID: 15922580     DOI: 10.1016/j.copbio.2005.05.003

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  7 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2007-07-18       Impact factor: 11.205

2.  "Reproducible" Research in Mathematical Sciences Requires Changes in our Peer Review Culture and Modernization of our Current Publication Approach.

Authors:  Santiago Schnell
Journal:  Bull Math Biol       Date:  2018-09-19       Impact factor: 1.758

3.  Computational modeling with forward and reverse engineering links signaling network and genomic regulatory responses: NF-kappaB signaling-induced gene expression responses in inflammation.

Authors:  Shih Chi Peng; David Shan Hill Wong; Kai Che Tung; Yan Yu Chen; Chun Cheih Chao; Chien Hua Peng; Yung Jen Chuang; Chuan Yi Tang
Journal:  BMC Bioinformatics       Date:  2010-06-08       Impact factor: 3.169

4.  A probabilistic approach to identify putative drug targets in biochemical networks.

Authors:  Ettore Murabito; Kieran Smallbone; Jonathan Swinton; Hans V Westerhoff; Ralf Steuer
Journal:  J R Soc Interface       Date:  2010-12-01       Impact factor: 4.118

Review 5.  Metabolic flux analysis: a comprehensive review on sample preparation, analytical techniques, data analysis, computational modelling, and main application areas.

Authors:  Bruna de Falco; Francesco Giannino; Fabrizio Carteni; Stefano Mazzoleni; Dong-Hyun Kim
Journal:  RSC Adv       Date:  2022-09-07       Impact factor: 4.036

6.  Extended kalman filter for estimation of parameters in nonlinear state-space models of biochemical networks.

Authors:  Xiaodian Sun; Li Jin; Momiao Xiong
Journal:  PLoS One       Date:  2008-11-19       Impact factor: 3.240

7.  Investigating differential dynamics of the MAPK signaling cascade using a multi-parametric global sensitivity analysis.

Authors:  Jeongah Yoon; Thomas S Deisboeck
Journal:  PLoS One       Date:  2009-02-23       Impact factor: 3.240

  7 in total

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