Literature DB >> 12075018

Modelling biological processes using workflow and Petri Net models.

Mor Peleg1, Iwei Yeh, Russ B Altman.   

Abstract

MOTIVATION: Biological processes can be considered at many levels of detail, ranging from atomic mechanism to general processes such as cell division, cell adhesion or cell invasion. The experimental study of protein function and gene regulation typically provides information at many levels. The representation of hierarchical process knowledge in biology is therefore a major challenge for bioinformatics. To represent high-level processes in the context of their component functions, we have developed a graphical knowledge model for biological processes that supports methods for qualitative reasoning.
RESULTS: We assessed eleven diverse models that were developed in the fields of software engineering, business, and biology, to evaluate their suitability for representing and simulating biological processes. Based on this assessment, we combined the best aspects of two models: Workflow/Petri Net and a biological concept model. The Workflow model can represent nesting and ordering of processes, the structural components that participate in the processes, and the roles that they play. It also maps to Petri Nets, which allow verification of formal properties and qualitative simulation. The biological concept model, TAMBIS, provides a framework for describing biological entities that can be mapped to the workflow model. We tested our model by representing malaria parasites invading host erythrocytes, and composed queries, in five general classes, to discover relationships among processes and structural components. We used reachability analysis to answer queries about the dynamic aspects of the model. AVAILABILITY: The model is available at http://smi.stanford.edu/projects/helix/pubs/process-model/.

Entities:  

Mesh:

Year:  2002        PMID: 12075018     DOI: 10.1093/bioinformatics/18.6.825

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  13 in total

1.  Data analysis and data mining: current issues in biomedical informatics.

Authors:  R Bellazzi; M Diomidous; I N Sarkar; K Takabayashi; A Ziegler; A T McCray
Journal:  Methods Inf Med       Date:  2011       Impact factor: 2.176

2.  Using Petri Net tools to study properties and dynamics of biological systems.

Authors:  Mor Peleg; Daniel Rubin; Russ B Altman
Journal:  J Am Med Inform Assoc       Date:  2004-11-23       Impact factor: 4.497

3.  Automated QSPR through Competitive Workflow.

Authors:  J Cartmell; S Enoch; D Krstajic; D E Leahy
Journal:  J Comput Aided Mol Des       Date:  2006-01-17       Impact factor: 3.686

4.  Simulation of a Petri net-based model of the terpenoid biosynthesis pathway.

Authors:  Aliah Hazmah Hawari; Zeti-Azura Mohamed-Hussein
Journal:  BMC Bioinformatics       Date:  2010-02-09       Impact factor: 3.169

5.  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

6.  Ontology-based instance data validation for high-quality curated biological pathways.

Authors:  Euna Jeong; Masao Nagasaki; Kazuko Ueno; Satoru Miyano
Journal:  BMC Bioinformatics       Date:  2011-02-15       Impact factor: 3.169

7.  A rigorous approach to facilitate and guarantee the correctness of the genetic testing management in human genome information systems.

Authors:  Luciano V Araújo; Simon Malkowski; Kelly R Braghetto; Maria R Passos-Bueno; Mayana Zatz; Calton Pu; João E Ferreira
Journal:  BMC Genomics       Date:  2011-12-22       Impact factor: 3.969

Review 8.  From pathways databases to network models of switching behavior.

Authors:  Baltazar D Aguda; Andrew B Goryachev
Journal:  PLoS Comput Biol       Date:  2007-09       Impact factor: 4.475

9.  Putative cold acclimation pathways in Arabidopsis thaliana identified by a combined analysis of mRNA co-expression patterns, promoter motifs and transcription factors.

Authors:  Aakash Chawade; Marcus Bräutigam; Angelica Lindlöf; Olof Olsson; Björn Olsson
Journal:  BMC Genomics       Date:  2007-09-02       Impact factor: 3.969

10.  On deducing causality in metabolic networks.

Authors:  Chiara Bodei; Andrea Bracciali; Davide Chiarugi
Journal:  BMC Bioinformatics       Date:  2008-04-25       Impact factor: 3.169

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