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Sender–receiver systems and applying information theory for quantitative synthetic biology
Sender–receiver (S–R) systems abound in biology, with communication systems sending information in various forms. Information theory provides a quantitative basis for analysing these processes and is being applied to study natural genetic, enzymatic and neural networks. Recent advances in synthetic...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4332572/ https://www.ncbi.nlm.nih.gov/pubmed/25282688 http://dx.doi.org/10.1016/j.copbio.2014.08.005 |
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author | Barcena Menendez, Diego Senthivel, Vivek Raj Isalan, Mark |
author_facet | Barcena Menendez, Diego Senthivel, Vivek Raj Isalan, Mark |
author_sort | Barcena Menendez, Diego |
collection | PubMed |
description | Sender–receiver (S–R) systems abound in biology, with communication systems sending information in various forms. Information theory provides a quantitative basis for analysing these processes and is being applied to study natural genetic, enzymatic and neural networks. Recent advances in synthetic biology are providing us with a wealth of artificial S–R systems, giving us quantitative control over networks with a finite number of well-characterised components. Combining the two approaches can help to predict how to maximise signalling robustness, and will allow us to make increasingly complex biological computers. Ultimately, pushing the boundaries of synthetic biology will require moving beyond engineering the flow of information and towards building more sophisticated circuits that interpret biological meaning. |
format | Online Article Text |
id | pubmed-4332572 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-43325722015-03-03 Sender–receiver systems and applying information theory for quantitative synthetic biology Barcena Menendez, Diego Senthivel, Vivek Raj Isalan, Mark Curr Opin Biotechnol Article Sender–receiver (S–R) systems abound in biology, with communication systems sending information in various forms. Information theory provides a quantitative basis for analysing these processes and is being applied to study natural genetic, enzymatic and neural networks. Recent advances in synthetic biology are providing us with a wealth of artificial S–R systems, giving us quantitative control over networks with a finite number of well-characterised components. Combining the two approaches can help to predict how to maximise signalling robustness, and will allow us to make increasingly complex biological computers. Ultimately, pushing the boundaries of synthetic biology will require moving beyond engineering the flow of information and towards building more sophisticated circuits that interpret biological meaning. Elsevier 2015-02 /pmc/articles/PMC4332572/ /pubmed/25282688 http://dx.doi.org/10.1016/j.copbio.2014.08.005 Text en © The Authors. Published by Elsevier Ltd. http://creativecommons.org/licenses/by/3.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Barcena Menendez, Diego Senthivel, Vivek Raj Isalan, Mark Sender–receiver systems and applying information theory for quantitative synthetic biology |
title | Sender–receiver systems and applying information theory for quantitative synthetic biology |
title_full | Sender–receiver systems and applying information theory for quantitative synthetic biology |
title_fullStr | Sender–receiver systems and applying information theory for quantitative synthetic biology |
title_full_unstemmed | Sender–receiver systems and applying information theory for quantitative synthetic biology |
title_short | Sender–receiver systems and applying information theory for quantitative synthetic biology |
title_sort | sender–receiver systems and applying information theory for quantitative synthetic biology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4332572/ https://www.ncbi.nlm.nih.gov/pubmed/25282688 http://dx.doi.org/10.1016/j.copbio.2014.08.005 |
work_keys_str_mv | AT barcenamenendezdiego senderreceiversystemsandapplyinginformationtheoryforquantitativesyntheticbiology AT senthivelvivekraj senderreceiversystemsandapplyinginformationtheoryforquantitativesyntheticbiology AT isalanmark senderreceiversystemsandapplyinginformationtheoryforquantitativesyntheticbiology |