Team:MIT/ResultsOverview

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In addition to our experimental results, we programmed computational models to inform our design decisions. We used Visual DSD to design a strand displacement <a href = "https://2012.igem.org/Team:MIT/ResultsProcessing#model">NOT gate</a>, and we used Visual GEC to design the <a href = "https://2012.igem.org/Team:MIT/ResultsSensing#sensing2bio">mRNA sensor</a> and an <a href = "https://2012.igem.org/Team:MIT/ResultsSensing#sensing2bio">inverted mRNA sensor</a>. Check it out!
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<img src = "https://static.igem.org/mediawiki/2012/e/e5/MIT-2012-computationalmodelling.png" width = "300"></img>In addition to our experimental results, we programmed computational models to inform our design decisions. We used Visual DSD to design a strand displacement <a href = "https://2012.igem.org/Team:MIT/ResultsProcessing#model">NOT gate</a>, and we used Visual GEC to design the <a href = "https://2012.igem.org/Team:MIT/ResultsSensing#sensing2bio">mRNA sensor</a> and an <a href = "https://2012.igem.org/Team:MIT/ResultsSensing#sensing2bio">inverted mRNA sensor</a>. Check it out!
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Revision as of 03:33, 4 October 2012

DEPRECATED. DO NOT USE OR EDIT. If a page uses this template, relink with MIT-results2.

The MIT iGEM team sought to unify aspects from the fields of DNA computing and synthetic biology in one project. We built upon an existing in vitro method of nucleic acid computation, designing new components and extending strand displacement to in vivo applications.

Over the past few months we have:
  • established the viability of RNA as an alternative processing medium to DNA
  • demonstrated RNA strand displacement in vivo and in vitro
  • successfully delivered DNA and RNA into mammalian cells
  • designed, modeled, and tested a DNA-based NOT gate, compatible with strand displacement circuits
  • designed, modeled, and tested a modular mRNA sensor along with an inverting sensor, both compatible with strand displacement circuits
  • designed, modeled, and tested various forms of regulating gene expression at the RNA level, compatible with strand displacement circuits, using:
    • miRNA-induced RNAi knockdown
    • Decoy & TuD mediated double-repression systems
    • self-cleaving Hammerhead ribozymes
  • characterized various new MammoBlock parts for transcribing short pieces of RNA in mammalian cells.
In addition to our experimental results, we programmed computational models to inform our design decisions. We used Visual DSD to design a strand displacement NOT gate, and we used Visual GEC to design the mRNA sensor and an inverted mRNA sensor. Check it out!