{"id":1629,"date":"2017-03-01T10:01:37","date_gmt":"2017-03-01T10:01:37","guid":{"rendered":"http:\/\/blogs.kent.ac.uk\/biosciences\/?p=1629"},"modified":"2018-09-19T12:56:05","modified_gmt":"2018-09-19T11:56:05","slug":"research-seminar-advancing-the-engineering-science-of-synthetic-biology-model-predictive-design-and-optimization-of-cellular-sensors-circuits-and-pathways","status":"publish","type":"post","link":"https:\/\/blogs.kent.ac.uk\/biosciences\/2017\/03\/01\/research-seminar-advancing-the-engineering-science-of-synthetic-biology-model-predictive-design-and-optimization-of-cellular-sensors-circuits-and-pathways\/","title":{"rendered":"Research Seminar: Advancing the engineering science of synthetic biology: model-predictive design and optimization of cellular sensors, circuits, and pathways."},"content":{"rendered":"

Professor Howard <\/b>Salis,<\/b> Department of Agricultural and Biological Engineering, Pennsylvania State University, USA<\/strong><\/p>\n

Tuesday 7th March, 1.00 p.m., Stacey Lecture Theatre 1<\/b><\/p>\n

 <\/p>\n

DNA is Nature’s programming language and its sequence determines how organisms sense their environment, perform decision-making, and produce valuable chemical products. The Salis lab engineers cellular sensors, genetic circuits, and metabolic pathways by developing and applying sequence-to-function biophysical models and optimization algorithms, capable of predicting the sequences of high-performance genetic systems before they are constructed.\u200b \u200b<\/p>\n

We illustrate our design approach with several examples, including RNA-based sensors that detect 2,4-dinitrotoluene, genetic circuits that amplify signals, and metabolic pathways that over-produced desired chemicals. Using a web-based design platform, our algorithms have been used by researchers world-wide to engineer over 100,000 genetic systems for their own biotech applications.<\/p>\n