Team:ULB-Brussels/Modelling

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<!-- /**  Design for https://2014.igem.org/Team:ULB-Brussels
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    Université Libre de Bruxelles  **/                -->
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<td width="50%"><section style="text-align: right">
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<a href="https://2014.igem.org/Team:ULB-Brussels/Modelling/Population-Dynamics"><b> Pop Dyn ></b></a>
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<a href="https://2014.igem.org/Team:ULB-Brussels/Modelling/TA-System"><b> TA Sys ></b></a>
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<a href="https://2014.igem.org/Team:ULB-Brussels/Modelling/2A-Peptid"><b> 2A Pep ></b></a>
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<p class="title"><font color="#002B9B">
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<font color="#CCD6EA">'Now begins an</font> $Overview$ <font color="#CCD6EA">about Modelling'</font>
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<h3>$\hspace{0.12cm}$Bibliography</h3>
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<ul>
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<li>[13]  A.V. Hill, (1910). <i>The possible effects of the Aggregation of the molecules of hemoglobin on its Dissociation curves</i>, J. Physiol, No.40, iv-vii. </li>
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<!-- Intro on Hill functions with hemoglobin-->
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<li>[14] T. Ogura, S. Hiraga, (1983). <i>Mini-F plasmids genes that couple Host cell division to Plasmid proliferation</i>, Proc. Natl. Acad. Sci. USA, 80, 4784-4788. </li>
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<!--
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(Abstract): Stable Maintenance plasmids, ccd region dissected into ccdB (cell division) and ccdA (inhibition), plasmid proloferation.
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(p4785): oriC plasmids, EcoR1, replication
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(p4787): Dissection of the cdd region + culture, kinetics and growing conditions.
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(p4788): Mutants of F plasmid
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<li>[15]  M. Santillán, (2008). <i>On the use of the Hill functions in Mathematical models od Gene regulatory networks</i>, Math. Model. Nat. Phenom., Vol.3, No.2, 85-97. </li>
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<!--
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(p86): Cooperative binding sequences: The Hill coefficient is appropriately described as an interaction coefficient reflecting cooperativity.
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(p94): If P is an activator(/repressor), the regulatory function R([P]) comes out to be monotocally increasing(/decreasing). Transcription rate, probability of gene copy.
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(p95): Interestingly, the most extensively studied gene regulatory systems (cf lactose operon of E.coli) make use of cooperativity to increase the sigmoidicity of the regulatory functions.
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(p96): Significance of the parameters by modelling.
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<li>[16] P. Wang, R.E. Dalbey, (2010). <i>In Vitro and in Vivo approaches to studying the Bacterial signal Peptide processing</i>, Springer Protocols, A. Economou ed. Humana Press, Protein Secretion, Methods in Molecular Biology 619,  21-37. </li>
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<!-- Signal peptide cleavage, membranes, cell biology, in vitro assays. -->
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<li>[17]  L. Gelens, L. Hill, A. Vandervelde, J. Danckaert, R. Loris, (2013). <i>A general model for Toxin-antitoxin module dynamics can explain Persister cell formation in E.coli</i>, PLOS Computational Biology, Vol.9, Iss.8, e1003190. </li>
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<!--
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(p1): Among the elements involved in bacterial stress response are the type TT toxine-antitoxin modules. CcdB and ParE family mambers inhibit gyrase, although via different molecular mechanisms.
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(p2): Persisters are subpopulations of bacteria wich are tolerant to biological stresses such antibiotics because they are in a dormant, non-dividing state.
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(p11): Fig @ simulations: Large toxin spikes -> route to persister cell formation through growth rate suppression.
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(p14): Kinds of TA, TAT Decay complexes.
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<li>[18] N. Goeders, L. Van Melderen, (2014). <i>Toxin-antitoxin systems as Multilevel interaction systems</i>, Toxins, 6, 304-324, ISSN 2072-6651. </li>
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<!--
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(p305): Fig: ccdA-ccdB
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(p306): Evolution of TA systems + bioinfo approaches.
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(p313): Effect on DNA-gyrase.
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<li>[19] D.A. Malyshev, K. Dhami, T. Lavergne, T. Chen, N. Dai, J.M. Foster, I.R. Corrêa Jr & F.E. Romesberg, (2014).
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<i>A semi-synthetic organism with an expanded genetic alphabet</i>, Research Letter, Nature 13314, 1-17. </li>
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<!-- E.Coli, experimental results using IPTG and KPI, iGEM 2013 team -->
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<li>[20] A. Provata, C. Nicolis & G. Nicolis, (2014). <i>DNA viewed as an out-of-equilibrium structure</i>, Phys. Rev. E 89, 052105. </li>
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<!-- Stochasticity and Markov processes, mammal chromosomes, MC rejection method algorithm, short-ranged intermolecular interactions. -->
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<section style="text-align: right">
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<a href="https://2014.igem.org/Team:ULB-Brussels/Modelling/Population-Dynamics"><b> Population Dynamics > </b></a>
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Revision as of 22:42, 17 October 2014

Pop Dyn > TA Sys > 2A Pep >

'Now begins an $Overview$ about Modelling'


$\hspace{0.12cm}$Bibliography

  • [13] A.V. Hill, (1910). The possible effects of the Aggregation of the molecules of hemoglobin on its Dissociation curves, J. Physiol, No.40, iv-vii.
  • [14] T. Ogura, S. Hiraga, (1983). Mini-F plasmids genes that couple Host cell division to Plasmid proliferation, Proc. Natl. Acad. Sci. USA, 80, 4784-4788.
  • [15] M. Santillán, (2008). On the use of the Hill functions in Mathematical models od Gene regulatory networks, Math. Model. Nat. Phenom., Vol.3, No.2, 85-97.
  • [16] P. Wang, R.E. Dalbey, (2010). In Vitro and in Vivo approaches to studying the Bacterial signal Peptide processing, Springer Protocols, A. Economou ed. Humana Press, Protein Secretion, Methods in Molecular Biology 619, 21-37.
  • [17] L. Gelens, L. Hill, A. Vandervelde, J. Danckaert, R. Loris, (2013). A general model for Toxin-antitoxin module dynamics can explain Persister cell formation in E.coli, PLOS Computational Biology, Vol.9, Iss.8, e1003190.
  • [18] N. Goeders, L. Van Melderen, (2014). Toxin-antitoxin systems as Multilevel interaction systems, Toxins, 6, 304-324, ISSN 2072-6651.
  • [19] D.A. Malyshev, K. Dhami, T. Lavergne, T. Chen, N. Dai, J.M. Foster, I.R. Corrêa Jr & F.E. Romesberg, (2014). A semi-synthetic organism with an expanded genetic alphabet, Research Letter, Nature 13314, 1-17.
  • [20] A. Provata, C. Nicolis & G. Nicolis, (2014). DNA viewed as an out-of-equilibrium structure, Phys. Rev. E 89, 052105.

Population Dynamics >


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