Difference between revisions of "Team:Carnegie Mellon/Measurement"
| Line 75: | Line 75: | ||
/* /jumbotron code */ | /* /jumbotron code */ | ||
| + | |||
| + | .description { | ||
| + | font-family: Palatino Linotype; | ||
| + | font-size: 25px; | ||
| + | line-height: 30px; | ||
| + | } | ||
</style> | </style> | ||
| Line 90: | Line 96: | ||
<div id = "bodybody"> | <div id = "bodybody"> | ||
| + | <div class = "description">Measurement is an important facet of synthetic biology. In order for experiments to run smoothly, measurements should be consistent across different research teams. One standing goal for iGEM is to characterize biological parts using precise measurements so that new systems can be created. Our Carnegie Mellon iGEM team chose to participate in the measurement track to lay a foundation for future measurement activities in iGEM. | ||
| + | <br></br> | ||
| + | In being part of this track, there are a few requirements we needed to fulfill. We took part in the international iGEM collaboration called the interlab study where we measured the same property of known samples to see if we could quantify the calculated measurements across different teams. Each team was recommended a protocol but was free to do any of their choosing. Our team decided to use the classical cloning protocol due to the versatility of this protocol and the supplies we had. In addition to the Interlab study, we needed to register our team, make a wiki page describing our project, and present a poster at the Jamboree. Being part of the measurement track has allowed us to focus our skills on making several biological and triplicate replicates to make sure our data was consistent across the board. We also learned how to problem solve and analyze our results based on the values we obtained.</div> | ||
</div><!-- bodybody --> | </div><!-- bodybody --> | ||
</body> | </body> | ||
Revision as of 19:35, 18 September 2015
Measurement.
Simple, low cost flourometers & luminometers.
Measurement is an important facet of synthetic biology. In order for experiments to run smoothly, measurements should be consistent across different research teams. One standing goal for iGEM is to characterize biological parts using precise measurements so that new systems can be created. Our Carnegie Mellon iGEM team chose to participate in the measurement track to lay a foundation for future measurement activities in iGEM.
In being part of this track, there are a few requirements we needed to fulfill. We took part in the international iGEM collaboration called the interlab study where we measured the same property of known samples to see if we could quantify the calculated measurements across different teams. Each team was recommended a protocol but was free to do any of their choosing. Our team decided to use the classical cloning protocol due to the versatility of this protocol and the supplies we had. In addition to the Interlab study, we needed to register our team, make a wiki page describing our project, and present a poster at the Jamboree. Being part of the measurement track has allowed us to focus our skills on making several biological and triplicate replicates to make sure our data was consistent across the board. We also learned how to problem solve and analyze our results based on the values we obtained.
In being part of this track, there are a few requirements we needed to fulfill. We took part in the international iGEM collaboration called the interlab study where we measured the same property of known samples to see if we could quantify the calculated measurements across different teams. Each team was recommended a protocol but was free to do any of their choosing. Our team decided to use the classical cloning protocol due to the versatility of this protocol and the supplies we had. In addition to the Interlab study, we needed to register our team, make a wiki page describing our project, and present a poster at the Jamboree. Being part of the measurement track has allowed us to focus our skills on making several biological and triplicate replicates to make sure our data was consistent across the board. We also learned how to problem solve and analyze our results based on the values we obtained.