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dc.contributor.authorWeiss, Ron
dc.date.accessioned2020-07-07T14:53:06Z
dc.date.available2020-07-07T14:53:06Z
dc.date.issued2018-05
dc.identifier.issn2473-2877
dc.identifier.urihttps://hdl.handle.net/1721.1/126062
dc.description.abstractSignificant progress has been made towards engineering both single-cell and multi-cellular systems through a combination of synthetic and systems biology,nanobiotechnology, pharmaceutical science, and computational approaches.However, our ability to engineer systems that begin to approach the complexity ofnatural pathways is severely limited by important challenges, e.g. due to noise, orthe fluctuations in gene expression and molecular species at multiple scales (e.g.both intra- and inter-cellular fluctuations). This barrier to engineering requires thatbiological noise be recognized as a design element with fundamentals that can beactively controlled. Here we highlight studies of an emerging discipline that collectively strives to engineer noise towards predictive stochastic design using interdisciplinary approaches at multiple-scales in diverse living systems.en_US
dc.description.sponsorshipNational Science Foundation (U.S.) Science Technology Center. Emergent Behaviors of Integrated Cellular Systems (Grant CBET-0939511)en_US
dc.language.isoen
dc.publisherAIP Publishingen_US
dc.relation.isversionof10.1063/1.5025033en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceAmerican Institute of Physics (AIP)en_US
dc.titlePerspective: Engineering noise in biological systems towards predictive stochastic designen_US
dc.typeArticleen_US
dc.identifier.citationDar, Roy D. and Ron Weiss. “Perspective: Engineering noise in biological systems towards predictive stochastic design.” APL Bioengineering, vol. 2, no. 2, 2018, 020901 © 2018 The Author(s)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.relation.journalAPL Bioengineeringen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2020-03-18T16:47:47Z
dspace.date.submission2020-03-18T16:47:50Z
mit.journal.volume2en_US
mit.journal.issue2en_US
mit.licensePUBLISHER_CC
mit.metadata.statusComplete


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