Literature DB >> 7584354

Petri net representations in metabolic pathways.

V N Reddy1, M L Mavrovouniotis, M N Liebman.   

Abstract

The present methods for representing metabolic pathways are limited in their ability to handle complex systems, incorporate new information, and to provide for drawing qualitative conclusions from the structure of pathways. The theory of Petri nets is introduced as a tool for computer-implementable representation of pathways. Petri nets have the potential to overcome the present limitations, and through a multitude of properties, enable the preliminary qualitative analysis of pathways.

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Year:  1993        PMID: 7584354

Source DB:  PubMed          Journal:  Proc Int Conf Intell Syst Mol Biol        ISSN: 1553-0833


  16 in total

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2.  Modelling and simulation of signal transductions in an apoptosis pathway by using timed Petri nets.

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3.  Graph-theoretic characterizations of monotonicity of chemical networks in reaction coordinates.

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4.  A graphical and computational modeling platform for biological pathways.

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5.  Some aspects of the anemia of chronic disorders modeled and analyzed by petri net based approach.

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Review 6.  The best models of metabolism.

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Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2017-05-19

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Authors:  Eduardo D Sontag
Journal:  Syst Synth Biol       Date:  2007-07-04

8.  Conceptual Model-based Systems Biology: mapping knowledge and discovering gaps in the mRNA transcription cycle.

Authors:  Judith Somekh; Mordechai Choder; Dov Dori
Journal:  PLoS One       Date:  2012-12-20       Impact factor: 3.240

9.  Computational systems biology in cancer: modeling methods and applications.

Authors:  Wayne Materi; David S Wishart
Journal:  Gene Regul Syst Bio       Date:  2007-09-17

10.  Multi-level model for the investigation of oncoantigen-driven vaccination effect.

Authors:  Francesca Cordero; Marco Beccuti; Chiara Fornari; Stefania Lanzardo; Laura Conti; Federica Cavallo; Gianfranco Balbo; Raffaele Calogero
Journal:  BMC Bioinformatics       Date:  2013-04-17       Impact factor: 3.169

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