{"id":166924,"date":"2014-07-01T00:00:00","date_gmt":"2014-07-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/computational-design-of-nucleic-acid-feedback-control-circuits\/"},"modified":"2018-10-16T20:26:26","modified_gmt":"2018-10-17T03:26:26","slug":"computational-design-of-nucleic-acid-feedback-control-circuits","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/computational-design-of-nucleic-acid-feedback-control-circuits\/","title":{"rendered":"Computational design of nucleic acid feedback control circuits"},"content":{"rendered":"<div class=\"asset-content\">\n<p>The design of synthetic circuits for controlling molecular-scale processes is an important goal of synthetic biology, with potential applications in future in vitro and in vivo biotechnology. In this paper, we present a computational approach for designing feedback control circuits constructed from nucleic acids. Our approach relies on an existing methodology for expressing signal processing and control circuits as biomolecular reactions. We first extend the methodology so that circuits can be expressed using just two classes of reactions: catalysis and annihilation. We then propose implementations of these reactions in three distinct classes of nucleic acid circuits, which rely on DNA strand displacement, DNA enzyme and RNA enzyme mechanisms, respectively. We use these implementations to design a Proportional Integral controller, capable of regulating the output of a system according to a given reference signal, and discuss the trade-offs between the different approaches. As a proof of principle, we implement our methodology as an extension to a DNA strand displacement software tool, thus allowing a broad range of nucleic acid circuits to be designed and analyzed within a common modeling framework.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The design of synthetic circuits for controlling molecular-scale processes is an important goal of synthetic biology, with potential applications in future in vitro and in vivo biotechnology. In this paper, we present a computational approach for designing feedback control circuits constructed from nucleic acids. Our approach relies on an existing methodology for expressing signal processing [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"American Chemical Society","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"8","msr_edition":"ACS Synthetic Biology","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"ACS Synthetic Biology","msr_number":"","msr_organization":"","msr_pages_string":"600-616","msr_page_range_start":"600","msr_page_range_end":"616","msr_series":"","msr_volume":"3","msr_copyright":"","msr_conference_name":"","msr_doi":"10.1021\/sb400169s","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"Jongmin Kim, Rasmus L. Petersen, Angelina Shudy, Vishwesh V. 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We continue to actively explore the exciting intersection of computing and life sciences, with other projects located on\u00a0www.microsoft.com\/research. Building a platform for programming biology The ability to program biology could enable fundamental breakthroughs across a broad range of industries, including medicine, agriculture, food, construction, textiles, materials and chemicals. It could also help lay the foundation for a future bioeconomy based on sustainable technology. 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