Difference between revisions of "Team:Cornell"

 
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     <title>Team:Cornell - 2018.igem.org</title>
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                                <a href="https://2018.igem.org/Team:Cornell/Team">BIOS</a>
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                     <div class="home-banner-caption">Introducing novelty through a frequency-based biological band-pass filter.</div>
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                     <div class="home-banner-caption">Introducing a novel frequency-based biological band-pass filter.</div>
 
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                 We are building a <span id="home-description-emphasis-words">biological band-pass filter</span>. While biological band pass filters have been developed before, none respond to frequency-based inputs but instead respond to amplitude based inputs.
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                 At Cornell iGEM, we look to the future to build now what synthetic biology needs next. We developed our project with the synthetic biology community in mind, and built a tool that the field can use for years to come. Our project shifts the paradigm of cellular signaling to a frequency-based signal and is an innovative step in mimicking digital systems.  <br><br><div><span id="home-description-emphasis-words"><i>Come explore the future with us.</i></span></div>  
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                By controlling the rates of degradation of the components of our system, we are putting together a <span id="home-description-emphasis-words">frequency-response</span> low-pass and high-pass filter to create a <span id="home-description-emphasis-words">novel</span>           band-pass filter.
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                <br><br> Our filter would allow bacteria to respond only to certain frequency-based inputs, and give it even more <span id="home-description-emphasis-words">digital logic-like</span> character, long a goal of synthetic biology. Moving forward,
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                our project could be an important tool for scientists as synthetic biology branches into increasingly diverse fields.
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                     <div>We are building a <span id="home-description-emphasis-words">biological band-pass filter</span>. While biological band pass filters have been developed before, none respond to frequency-based inputs but instead respond to amplitude based inputs. By controlling the rates of degradation of the components of our system, we are putting together a <span id="home-description-emphasis-words">frequency-response</span> low-pass and high-pass filter to create a <span id="home-description-emphasis-words">novel</span> band-pass filter.</div>
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                     <div>But how? We rely on sensory elements to allow cells to respond to frequency signals, while combining them with tunable protein degradation tags to control the kinetics of protein expression. This has allowed us to develop a tunable gene-expression system developed to respond to controlled and defined stimuli. This further acts as a template for development of systems responsive to various frequency input signals, from heat to light to sound.</div>
 
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                 <div>We are building a <span id="home-description-emphasis-words">biological band-pass filter</span>. While biological band pass filters have been developed before, none respond to frequency-based inputs but instead respond to amplitude based inputs. By controlling the rates of degradation of the components of our system, we are putting together a <span id="home-description-emphasis-words">frequency-response</span> low-pass and high-pass filter to create a <span id="home-description-emphasis-words">novel</span> band-pass filter.</div>
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                 <div>Innovative modeling serves as a critical component of our toolkit and as a modular tool that other teams can use in the future. We developed advanced deterministic and stochastic models using a unique proof-based approach. Further, we were able to draw from Degree Theory in mathematics to construct formal proofs regarding the nature of our dynamical system independent of specific parameter values to create a robust modeling framework.</div>
 
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                     <div>We are building a <span id="home-description-emphasis-words">biological band-pass filter</span>. While biological band pass filters have been developed before, none respond to frequency-based inputs but instead respond to amplitude based inputs. By controlling the rates of degradation of the components of our system, we are putting together a <span id="home-description-emphasis-words">frequency-response</span> low-pass and high-pass filter to create a <span id="home-description-emphasis-words">novel</span> band-pass filter.</div>
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                     <div>As a team, we always try to keep in mind the impact of our projects as well as the considerations we make in their design. We spoke with other iGEM teams and synthetic biologists to learn more about how to design our system, and where it could go in the future. We further integrated ourselves in the local and national communities, leading workshops and teaching local students about the growing field of synthetic biology and the exciting possibilities it can have!</div>
 
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                <div>We are building a <span id="home-description-emphasis-words">biological band-pass filter</span>. While biological band pass filters have been developed before, none respond to frequency-based inputs but instead respond to amplitude based inputs. By controlling the rates of degradation of the components of our system, we are putting together a <span id="home-description-emphasis-words">frequency-response</span> low-pass and high-pass filter to create a <span id="home-description-emphasis-words">novel</span> band-pass filter.</div>
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Latest revision as of 19:40, 21 November 2018

Team:Cornell - 2018.igem.org

Introducing a novel frequency-based biological band-pass filter.
At Cornell iGEM, we look to the future to build now what synthetic biology needs next. We developed our project with the synthetic biology community in mind, and built a tool that the field can use for years to come. Our project shifts the paradigm of cellular signaling to a frequency-based signal and is an innovative step in mimicking digital systems.

Come explore the future with us.
Wet Lab
But how? We rely on sensory elements to allow cells to respond to frequency signals, while combining them with tunable protein degradation tags to control the kinetics of protein expression. This has allowed us to develop a tunable gene-expression system developed to respond to controlled and defined stimuli. This further acts as a template for development of systems responsive to various frequency input signals, from heat to light to sound.
Modeling
Innovative modeling serves as a critical component of our toolkit and as a modular tool that other teams can use in the future. We developed advanced deterministic and stochastic models using a unique proof-based approach. Further, we were able to draw from Degree Theory in mathematics to construct formal proofs regarding the nature of our dynamical system independent of specific parameter values to create a robust modeling framework.
Human Practices
As a team, we always try to keep in mind the impact of our projects as well as the considerations we make in their design. We spoke with other iGEM teams and synthetic biologists to learn more about how to design our system, and where it could go in the future. We further integrated ourselves in the local and national communities, leading workshops and teaching local students about the growing field of synthetic biology and the exciting possibilities it can have!