Literature DB >> 17636859

Generalized hill function method for modeling molecular processes.

Vitali Likhoshvai1, Alexander Ratushny.   

Abstract

Development of an in silico cell is an urgent task of systems biology. The core of this cell should consist of mathematical models of intracellular events, including enzymatic reactions and control of gene expression. For example, the minimal model of the E. coli cell should include description of about one thousand enzymatic reactions and regulation of expression of approximately the same number of genes. In many cases detailed mechanisms of molecular processes are not known. In this study, we propose a generalized Hill function method for modeling molecular events. The proposed approach is a method of kinetic data approximation in view of additional data on structure functional features of molecular genetic systems and actually does not demand knowledge of their detailed mechanisms. Generalized Hill function models of an enzymatic reaction catalyzed by the tryptophan-sensitive 3-deoxy-d-arabino-heptulosonate-7-phosphate synthase and the cydAB operon expression regulation are presented.

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Year:  2007        PMID: 17636859     DOI: 10.1142/s0219720007002837

Source DB:  PubMed          Journal:  J Bioinform Comput Biol        ISSN: 0219-7200            Impact factor:   1.122


  11 in total

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2.  An evolutionarily conserved RNase-based mechanism for repression of transcriptional positive autoregulation.

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3.  Pluripotency gene network dynamics: System views from parametric analysis.

Authors:  Ilya R Akberdin; Nadezda A Omelyanchuk; Stanislav I Fadeev; Natalya E Leskova; Evgeniya A Oschepkova; Fedor V Kazantsev; Yury G Matushkin; Dmitry A Afonnikov; Nikolay A Kolchanov
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4.  Mathematical modeling of biomolecular network dynamics.

Authors:  Alexander V Ratushny; Stephen A Ramsey; John D Aitchison
Journal:  Methods Mol Biol       Date:  2011

5.  A plausible mechanism for auxin patterning along the developing root.

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6.  The rates of protein synthesis and degradation account for the differential response of neurons to spaced and massed training protocols.

Authors:  Faisal Naqib; Carole A Farah; Christopher C Pack; Wayne S Sossin
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Review 7.  Systems cell biology.

Authors:  Fred D Mast; Alexander V Ratushny; John D Aitchison
Journal:  J Cell Biol       Date:  2014-09-15       Impact factor: 10.539

8.  Dynamic landscape of the local translation at activated synapses.

Authors:  T M Khlebodarova; V V Kogai; E A Trifonova; V A Likhoshvai
Journal:  Mol Psychiatry       Date:  2017-12-05       Impact factor: 15.992

9.  Metallochaperones regulate intracellular copper levels.

Authors:  W Lee Pang; Amardeep Kaur; Alexander V Ratushny; Aleksandar Cvetkovic; Sunil Kumar; Min Pan; Adam P Arkin; John D Aitchison; Michael W W Adams; Nitin S Baliga
Journal:  PLoS Comput Biol       Date:  2013-01-17       Impact factor: 4.475

10.  On the control mechanisms of the nitrite level in Escherichia coli cells: the mathematical model.

Authors:  Tamara M Khlebodarova; Nataly A Ree; Vitaly A Likhoshvai
Journal:  BMC Microbiol       Date:  2016-01-27       Impact factor: 3.605

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