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Merged biocompute and grns
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@@ -38,35 +38,35 @@ <h2>quantitative biology + synthetic biology + systems biology</h2>
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<div class="container">
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<!--- PROJECT - cartoons ----->
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<section>
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<span class="feature-icon"><a href="#cancer_popup" class="icon solid fa-dna"></a></span>
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<header>
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<h3>Mutational processes</h3>
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</section>
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<span class="feature-icon"><a href="#microbiome_popup" class="icon solid fa-microscope"></a></span>
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<h3>Microbiome engineering</h3>
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<div class="col-3 col-12-narrow">
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<!-- <div class="col-3 col-12-narrow">
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<span class="feature-icon"><a href="#grn_popup" class="icon solid fa-share-alt"></a></span>
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<h3>Gene regulatory networks</h3>
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<span class="feature-icon"><a href="#biocomp_popup" class="icon solid fa-microchip"></a></span>
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<h3>Biological computing</h3>
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<h3>Biological computation</h3>
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<a href="#x" class="overlay" id="biocomp_popup"></a>
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<div class="popup">
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<h2>Biological computing</h2>
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<h2>Biological computation</h2>
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<p>Biological organisms comprise complex information processing systems and computation is present at
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every level, from protein and DNA nanomachines, through cellular gene and signalling networks to
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tissues, brains and ecosystems. Thus, computation can be seen to be a fundamental and unifying
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</header>
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<section id="research_grn" class="main">
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<section id="research_biocomp" class="main">
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<header>
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<div class="container">
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<h2>Gene regulatory networks</h2>
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<h2>Biological computation</h2>
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<figure>
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<img width="50%" src="images/science/fig10-toggle-osc-v2.jpg" alt="" />
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<figcaption>Fig: Post-translational coupling of an oscillator and a bistable switch</figcaption>
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<img width="50%" src="images/science/logic_gate_sim.jpg" alt="" />
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<figcaption>Fig: Patterning as a spatial computation. Each panel represents a different interpretation
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of a morphogen gradient produced from two sources A and B</figcaption>
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</figure>
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<p> Otero-Muras, I., Perez-Carrasco, R., Banga, J.R., Barnes, C.P. (2023). Automated design of gene circuits with optimal mushroom-bifurcation behavior. iScience, 26 (6), doi:10.1016/j.isci.2023.106836</p>
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<p>Perez-Carrasco, R., Barnes, C.P., Schaerli, Y., Isalan, M., Briscoe, J., Page, K.M. (2018).
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<p> AJH Fedorec, NJ Treloar, KY Wen, L Dekker, QH Ong, G Jurkeviciute, ... (2023)
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Emergent digital bio-computation through spatial diffusion and engineered bacteria
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bioRxiv, 2023.07. 07.548081 </p>
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<p> Otero-Muras, I., Perez-Carrasco, R., Banga, J.R., Barnes, C.P. (2023).
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Automated design of gene circuits with optimal mushroom-bifurcation behavior.
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iScience, 26 (6), doi:10.1016/j.isci.2023.106836</p>
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<p> Treloar, N.J., Braniff, N., Ingalls, B., Barnes, C.P. (2022).
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Deep reinforcement learning for optimal experimental design in biology.
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PLoS Computational Biology, 18 (11), doi:10.1371/journal.pcbi.1010695 </p>
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<p>Treloar, N., Wen, K.Y., Fedorec, A., Barnes, C. (2021).
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SynBioBrain: building biological computers from bacterial populations.
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The Project Repository Journal, doi:<a href=https://doi.org/10.54050/PRJ1117751>doi.org/10.54050/PRJ1117751</a> </p>
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<p> Karkaria, B.D., Treloar, N.J., Barnes, C.P., Fedorec, A.J.H. (2020).
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From microbial communities to distributed computing systems
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Frontiers in Bioengineering and Biotechnology 8, 834, doi:<a href=https://doi.org/10.3389/fbioe.2020.00834>doi.org/10.3389/fbioe.2020.00834</a>
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</p>
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<p>Dalchau, N., Szép, G., Hernansaiz-Ballesteros, R., Barnes, C.P., Cardelli, L., Phillips, A., Csikász-Nagy, A. (2018).
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Computing with biological switches and clocks.
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Natural Computing, 1-19. doi:<a href=https://doi.org/10.1007/s11047-018-9686-x>10.1007/s11047-018-9686-x</a>
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</p>
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<p>Perez-Carrasco, R., Barnes, C.P., Schaerli, Y., Isalan, M., Briscoe, J., Page, K.M. (2018).
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Combining a Toggle Switch and a Repressilator within the AC-DC Circuit Generates Distinct Dynamical Behaviors.
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Cell Systems. doi:<a href=https://doi.org/10.1016/j.cels.2018.02.008>10.1016/j.cels.2018.02.008</a>
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</p>
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<p>
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Boeing, P., Leon, M., Nesbeth, D.N., Finkelstein, A., Barnes, C. (2018).
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Towards an Aspect-Oriented Design and Modelling Framework for Synthetic Biology.
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Processes, 6 (9), doi:<a href=https://doi.org/10.3390/pr6090167>10.3390/pr6090167</a>
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</p>
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<p>
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Leon, M., Woods, M.L., Fedorec, A.J.H., & Barnes, C.P. (2016)
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A computational method for the investigation of multistable systems and its application to genetic switches.
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A framework for parameter estimation and model selection from experimental data in systems biology using approximate Bayesian computation.
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Nature Protocols, 9(2), 439-456. doi:<a href=https://doi.org/10.1038/nprot.2014.025>10.1038/nprot.2014.025</a>
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</p>
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<section id="research_biocomp" class="main">
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<div class="container">
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<h2>Biological computing</h2>
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<figure>
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<img width="50%" src="images/science/logic_gate_sim.jpg" alt="" />
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<figcaption>Fig: Patterning as a spatial computation. Each panel represents a different interpretation
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of a morphogen gradient produced from two sources A and B</figcaption>
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</figure>
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<p> AJH Fedorec, NJ Treloar, KY Wen, L Dekker, QH Ong, G Jurkeviciute, ...
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Emergent digital bio-computation through spatial diffusion and engineered bacteria
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bioRxiv, 2023.07. 07.548081 </p>
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<p> Treloar, N.J., Braniff, N., Ingalls, B.,
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Barnes, C.P. (2022). Deep reinforcement learning for optimal
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experimental design in biology. PLoS Computational Biology, 18
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(11), doi:10.1371/journal.pcbi.1010695 </p>
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<p>Treloar, N., Wen, K.Y., Fedorec, A., Barnes, C. (2021). SynBioBrain: building biological computers from bacterial populations. The Project Repository Journal, doi:<a href=https://doi.org/10.54050/PRJ1117751>doi.org/10.54050/PRJ1117751</a> </p>
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<p> Karkaria, B.D., Treloar, N.J., Barnes, C.P., Fedorec, A.J.H. (2020).
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From microbial communities to distributed computing systems
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Frontiers in Bioengineering and Biotechnology 8, 834, doi:<a href=https://doi.org/10.3389/fbioe.2020.00834>doi.org/10.3389/fbioe.2020.00834</a>
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</p>
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<p>Dalchau, N., Szép, G., Hernansaiz-Ballesteros, R., Barnes, C.P., Cardelli, L., Phillips, A., Csikász-Nagy, A. (2018).
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Computing with biological switches and clocks.
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Natural Computing, 1-19. doi:<a href=https://doi.org/10.1007/s11047-018-9686-x>10.1007/s11047-018-9686-x</a>
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</p>
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