N a previous study [45]. In particular, we identified a large number of graph components, between which no exchange of atoms is possible. This observation warrants a further study to find out whether the disconnectivity stems from errors in KEGG database, a biological phenomena, or both. The availability and quality of atom mappings is of great importance to the method. Currently, methods for obtaining high-quality atom mappings are actively being investigated by many groups, including ours. Fortunately for applications demonstrated in this paper, we are mostly able to ignore the problem of deciding between alternative mappings stemming from apparently isomorphic fragments.Authors’ contributionsEP designed, analyzed and implemented the algorithm, performed the experiments and wrote the manuscript. PJ and JR contributed to the development of the method and writing the manuscript. PJ and EP analyzed the results of the glucose-IMP experiment. All authors have read and approved the final version of the manuscript.Additional material Additional fileReTrace user guide and implementation notes. ReTrace implementation details and user guide. A self-contained web site: unpack archive and open index.html in a web browser. Click here for file [http://www.biomedcentral.com/content/supplementary/17520509-3-103-S1.zip]Additional fileReTrace results from experiments. Summary data and html output from ReTrace runs performed for the queries discussed in the section Results. A self-contained web site: unpack archive and open index.html in a web browser. Click here for file [http://www.biomedcentral.com/content/supplementary/17520509-3-103-S2.zip]AcknowledgementsWe would like to thank Ari Rantanen and Esko Ukkonen for their critical comments, and Mikko Arvas for discussion and support with the T. reesei genome. This work was supported by Academy of Finland grants 118653 (ALGODAN) and 118573 (White Biotechnology – Green Chemistry 20082013), and in part by the IST Programme of the European Community under PASCAL2 Network of Excellence, IST-2007-216886. This publication only reflects the authors’ views.
Coulon et al. BMC Systems Biology 2010, 4:2 http://www.biomedcentral.com/1752-0509/4/RESEARCH ARTICLEOpen AccessOn the spontaneous stochastic dynamics of a single gene: complexity of the molecular LurbinectedinMedChemExpress Lurbinectedin interplay at the promoterAntoine Coulon1,2,3*, Olivier Gandrillon1,3, Guillaume Beslon2,AbstractBackground: Gene promoters can be in various epigenetic states and undergo interactions with many molecules in a highly transient, probabilistic and combinatorial way, resulting in a complex global dynamics as observed experimentally. However, models of stochastic gene expression commonly consider promoter activity as a twostate on/off system. We consider here a model of single-gene stochastic expression that can represent arbitrary prokaryotic or eukaryotic promoters, PubMed ID:http://www.ncbi.nlm.nih.gov/pubmed/27735993 based on the combinatorial interplay between molecules and epigenetic factors, including energy-dependent remodeling and enzymatic activities. Results: We show that, considering the mere molecular interplay at the promoter, a single-gene can demonstrate an elaborate spontaneous stochastic activity (eg. multi-periodic multi-relaxation dynamics), similar to what is known to occur at the gene-network level. Characterizing this generic model with indicators of dynamic and steady-state properties (including power spectra and distributions), we reveal the potential activity of any promoter and its influence on gen.
