Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Barcena Menendez, Diego, Senthivel, Vivek Raj, Isalan, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2015
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
_version_ 1782357928948269056
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