Literature DB >> 12634134

BioMOL: a computer-assisted biological modeling tool for complex chemical mixtures and biological processes at the molecular level.

Michael T Klein1, Gang Hou, Richard J Quann, Wei Wei, Kai H Liao, Raymond S H Yang, Julie A Campain, Monica A Mazurek, Linda J Broadbelt.   

Abstract

A chemical engineering approach for the rigorous construction, solution, and optimization of detailed kinetic models for biological processes is described. This modeling capability addresses the required technical components of detailed kinetic modeling, namely, the modeling of reactant structure and composition, the building of the reaction network, the organization of model parameters, the solution of the kinetic model, and the optimization of the model. Even though this modeling approach has enjoyed successful application in the petroleum industry, its application to biomedical research has just begun. We propose to expand the horizons on classic pharmacokinetics and physiologically based pharmacokinetics (PBPK), where human or animal bodies were often described by a few compartments, by integrating PBPK with reaction network modeling described in this article. If one draws a parallel between an oil refinery, where the application of this modeling approach has been very successful, and a human body, the individual processing units in the oil refinery may be considered equivalent to the vital organs of the human body. Even though the cell or organ may be much more complicated, the complex biochemical reaction networks in each organ may be similarly modeled and linked in much the same way as the modeling of the entire oil refinery through linkage of the individual processing units. The integrated chemical engineering software package described in this article, BioMOL, denotes the biological application of molecular-oriented lumping. BioMOL can build a detailed model in 1-1,000 CPU sec using standard desktop hardware. The models solve and optimize using standard and widely available hardware and software and can be presented in the context of a user-friendly interface. We believe this is an engineering tool with great promise in its application to complex biological reaction networks.

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Year:  2002        PMID: 12634134      PMCID: PMC1241287          DOI: 10.1289/ehp.02110s61025

Source DB:  PubMed          Journal:  Environ Health Perspect        ISSN: 0091-6765            Impact factor:   9.031


  4 in total

1.  Computing 2010: from black holes to biology.

Authors:  D Butler
Journal:  Nature       Date:  1999-12-02       Impact factor: 49.962

Review 2.  Network dynamics and cell physiology.

Authors:  J J Tyson; K Chen; B Novak
Journal:  Nat Rev Mol Cell Biol       Date:  2001-12       Impact factor: 94.444

3.  Optimization by simulated annealing.

Authors:  S Kirkpatrick; C D Gelatt; M P Vecchi
Journal:  Science       Date:  1983-05-13       Impact factor: 47.728

Review 4.  Application of biologically based computer modeling to simple or complex mixtures.

Authors:  Kai H Liao; Ivan D Dobrev; James E Dennison; Melvin E Andersen; Brad Reisfeld; Kenneth F Reardon; Julie A Campain; Wei Wei; Michael T Klein; Richard J Quann; Raymond S H Yang
Journal:  Environ Health Perspect       Date:  2002-12       Impact factor: 9.031

  4 in total
  6 in total

Review 1.  CANDO and the infinite drug discovery frontier.

Authors:  Mark Minie; Gaurav Chopra; Geetika Sethi; Jeremy Horst; George White; Ambrish Roy; Kaushik Hatti; Ram Samudrala
Journal:  Drug Discov Today       Date:  2014-06-26       Impact factor: 7.851

2.  Computational evaluation of factors governing catalytic 2-keto acid decarboxylation.

Authors:  Di Wu; Dajun Yue; Fengqi You; Linda J Broadbelt
Journal:  J Mol Model       Date:  2014-06-10       Impact factor: 1.810

Review 3.  Application of biologically based computer modeling to simple or complex mixtures.

Authors:  Kai H Liao; Ivan D Dobrev; James E Dennison; Melvin E Andersen; Brad Reisfeld; Kenneth F Reardon; Julie A Campain; Wei Wei; Michael T Klein; Richard J Quann; Raymond S H Yang
Journal:  Environ Health Perspect       Date:  2002-12       Impact factor: 9.031

4.  Chemical mixtures research: significance and future perspectives.

Authors:  William A Suk; Kenneth Olden; Raymond S H Yang
Journal:  Environ Health Perspect       Date:  2002-12       Impact factor: 9.031

5.  Cumulative risk assessment toolbox: methods and approaches for the practitioner.

Authors:  Margaret M Macdonell; Lynne A Haroun; Linda K Teuschler; Glenn E Rice; Richard C Hertzberg; James P Butler; Young-Soo Chang; Shanna L Clark; Alan P Johns; Camarie S Perry; Shannon S Garcia; John H Jacobi; Marcienne A Scofield
Journal:  J Toxicol       Date:  2013-05-09

6.  The Promise and Challenge of Digital Biology.

Authors:  Mark E Minie; Ram Samudrala
Journal:  J Bioeng Biomed Sci       Date:  2013-12-04
  6 in total

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