ArticleNucleic acids research2003
CADLIVE for constructing a large-scale biochemical network based on a simulation-directed notation and its application to yeast cell cycle.
Article in Nucleic acids research, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- Sustainable software development in science - insights from 20 years of Vanted.Journal of integrative bioinformatics · 2025Article
- Transcriptome-based network analysis of cell cycle-related genes in response to blue and red light in maize.AoB PLANTS · 2023Article
- Automatic Generation of SBML Kinetic Models from Natural Language Texts Using GPT.International journal of molecular sciences · 2023Article
- Virtual metabolic human dynamic model for pathological analysis and therapy design for diabetes.iScience · 2021Article
- Computer-Aided Rational Design of Efficient NADPH Production System byFrontiers in bioengineering and biotechnology · 2020Article
- Improvement of the memory function of a mutual repression network in a stochastic environment by negative autoregulation.BMC bioinformatics · 2019Article
- Self-replenishment cycles generate a threshold response.Scientific reports · 2019Article
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- Ranking network mechanisms by how they fit diverse experiments and deciding onNPJ systems biology and applications · 2019Article
- Modeling and simulation of the redox regulation of the metabolism inBiotechnology for biofuels · 2017Article
- Graphical Modeling Meets Systems Pharmacology.Gene regulation and systems biology · 2017Article
- Development of an accurate kinetic model for the central carbon metabolism of Escherichia coli.Microbial cell factories · 2016Article
- CADLIVE optimizer: web-based parameter estimation for dynamic models.Source code for biology and medicine · 2012Article
- Application of approximate pattern matching in two dimensional spaces to grid layout for biochemical network maps.PloS one · 2012Article
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- Article
- SynBioSS designer: a web-based tool for the automated generation of kinetic models for synthetic biological constructs.Briefings in bioinformatics · 2010Article
- An efficient biological pathway layout algorithm combining grid-layout and spring embedder for complicated cellular location information.BMC bioinformatics · 2010Article
- LucidDraw: efficiently visualizing complex biochemical networks within MATLAB.BMC bioinformatics · 2010Article
- Web-based applications for building, managing and analysing kinetic models of biological systems.Briefings in bioinformatics · 2009Article
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3 authors.
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Abstract
The further understanding of the mechanisms of gene regulatory networks requires comprehensive tools for both the representation of complicated signal transduction pathways and the in silico identification of genomic signals that govern the regulation of gene expression. Consequently, sophisticated notation must be developed to represent the signal transduction pathways in a form that can be readily processed by both computers and humans. We propose the regulator-reaction equations combined with detailed attributes including the associated cellular component, molecular function, and biological process and present the simulation-directed graphical notation that is derived from modification of Kohn's method. We have developed the software suite, CADLIVE (Computer-Aided Design of LIVing systEms), which features a graphical user interface (GUI) to edit large-scale maps of complicated signal transduction pathways using a conventional XML-based representation. The regulator-reaction equations represent not only mechanistic reactions, but also semantic models containing ambiguous and incomplete processes. In order to demonstrate the feasibility of CADLIVE, we constructed a detailed map of the budding yeast cell cycle, which consists of 184 molecules and 152 reactions, in a really compact space. CADLIVE enables one to look at the whole view of a large-scale map, to integrate postgenomic data into the map, and to computationally simulate the signal transduction pathways, which greatly facilitates exploring novel or unexpected interactions.
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