Team:SUSTC-Shenzhen-B/achievements

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<article>
<article>
<h1><p>Results</p></h1>
<h1><p>Results</p></h1>
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                 <h3>1, Theoretical model of predicting efficiency of terminators</h3>
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                 <h3>1. Theoretical model of predicting efficiency of terminators</h3>
<p>The goal of theoretical model to predict the efficiency of a terminator from its
<p>The goal of theoretical model to predict the efficiency of a terminator from its
nucleotide sequence. We use free energy methods to predict the secondary structure
nucleotide sequence. We use free energy methods to predict the secondary structure
of terminator. A d score is defined as<br>
of terminator. A d score is defined as<br>
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D=-96.6DΔ/L+18.6T-116.9    (2)<br>
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D=-96.6DΔG/L+18.6T-116.9    (1)<br>
Here, ΔG is the Gibbs free energy change of stemloop formation. L is the length of stemloop. T is the score of T tail.
Here, ΔG is the Gibbs free energy change of stemloop formation. L is the length of stemloop. T is the score of T tail.
</p>
</p>
<p>To get a relationship between d score and efficiency, we use the biofab data as
<p>To get a relationship between d score and efficiency, we use the biofab data as
training dataset. Biofab is the International Open Facility Advancing Biotechnology, which was founded in 2009. It's led by bioengineers from UC Berkeley and Stanford. In biofab data, there are 40 terminators with efficiency data available. We calculated the d score of terminators in Biofab and plot it with efficiency (Figure 1).</p>
training dataset. Biofab is the International Open Facility Advancing Biotechnology, which was founded in 2009. It's led by bioengineers from UC Berkeley and Stanford. In biofab data, there are 40 terminators with efficiency data available. We calculated the d score of terminators in Biofab and plot it with efficiency (Figure 1).</p>
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<img src=" http://2012.igem.org/wiki/images/d/db/Result-1.png" alt="" class="change" /><br>
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<img src="http://2012.igem.org/wiki/images/0/0e/Result-7.png" alt="" class="change" /><br>
(Figure 1 diagram showing the correlation between d score and efficiency)
(Figure 1 diagram showing the correlation between d score and efficiency)
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<p>We found that d score and efficiency is positively correlated. Linear fitting is
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<p>We found that d score and efficiency is positively correlated. Linear fitting by parts is performed.
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performed and the fitting curve is<br>
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We calculate the average error as follows:<br>
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E=1.4D+39.1   (2)<br>
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<img src="http://2012.igem.org/wiki/images/6/6d/Result-8.1.JPG" alt="" class="change" />    (2)<br>
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The R^2 is 0.54.</p>
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Here Δe is the average error, n is the number of data , E(prediction) is the efficiency predicted by our model and  E(measurement) is the efficiency measured in experiment.<br>
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For Figure 1, the average error is 16%.
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 +
 
<p>We proposed that terminators can be classified into three classes based on efficiency.<br>
<p>We proposed that terminators can be classified into three classes based on efficiency.<br>
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  <img src=" http://2012.igem.org/wiki/images/7/78/Result-2.JPG" alt="" class="change" /><br>
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  <img src="http://2012.igem.org/wiki/images/7/77/Result-9.JPG" alt="" class="change" /><br>
(Table.1 Table of  efficiency and d score correspond to different class of terminators).
(Table.1 Table of  efficiency and d score correspond to different class of terminators).
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<h3>2, Validating theoretical model by existing data</h3>
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<h3>2, Validating theoretical model by our own experimental data</h3>
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<p>We collect existing data of efficiency of terminators from literatures and databases except Biofab. Using these data, we plot the predicted efficiency based on formula (2) with efficiency data (Figure 2). We found that our theoretical predication fit experiemental data quite well with correlation coefficient 0.8<br>
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<img src=" http://2012.igem.org/wiki/images/4/48/Result-3.png" alt="" class="change" /><br>
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(Figure 2, diagram of validation using our experimental data)</p>
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<p>We did experiment to measure the efficiency of terminators.Using the experimental data, we plot the predicted efficiency based on our model with efficiency data (Figure 2). We found that our theoretical predication fit experiemental data quite well.<br>
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<img src=" http://2012.igem.org/wiki/images/a/a5/Result-10.png" alt="" class="change" /><br>
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(Figure 2, diagram of validation using our experimental data)</p><br>
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<p>For Figure 2, we also calculate the average error. using equation(2).  The result is 18%.</p>
<h3>3, TTEC software and webtool</h3>
<h3>3, TTEC software and webtool</h3>
<p>We developed TTEC software to predict terminator efficiency, which is available at
<p>We developed TTEC software to predict terminator efficiency, which is available at

Latest revision as of 04:01, 27 October 2012

Title

Results

1. Theoretical model of predicting efficiency of terminators

The goal of theoretical model to predict the efficiency of a terminator from its nucleotide sequence. We use free energy methods to predict the secondary structure of terminator. A d score is defined as
D=-96.6DΔG/L+18.6T-116.9 (1)
Here, ΔG is the Gibbs free energy change of stemloop formation. L is the length of stemloop. T is the score of T tail.

To get a relationship between d score and efficiency, we use the biofab data as training dataset. Biofab is the International Open Facility Advancing Biotechnology, which was founded in 2009. It's led by bioengineers from UC Berkeley and Stanford. In biofab data, there are 40 terminators with efficiency data available. We calculated the d score of terminators in Biofab and plot it with efficiency (Figure 1).


(Figure 1 diagram showing the correlation between d score and efficiency)

We found that d score and efficiency is positively correlated. Linear fitting by parts is performed. We calculate the average error as follows:
(2)
Here Δe is the average error, n is the number of data , E(prediction) is the efficiency predicted by our model and E(measurement) is the efficiency measured in experiment.
For Figure 1, the average error is 16%.

We proposed that terminators can be classified into three classes based on efficiency.

(Table.1 Table of efficiency and d score correspond to different class of terminators).

2, Validating theoretical model by our own experimental data

We did experiment to measure the efficiency of terminators.Using the experimental data, we plot the predicted efficiency based on our model with efficiency data (Figure 2). We found that our theoretical predication fit experiemental data quite well.

(Figure 2, diagram of validation using our experimental data)


For Figure 2, we also calculate the average error. using equation(2). The result is 18%.

3, TTEC software and webtool

We developed TTEC software to predict terminator efficiency, which is available at www.terminator efficiency.com (for our web tool)
https://github.com/igemsoftware/SUSTC_Shenzhen_B_2012 (for our software)

(Figure 3 the interface of our web tool)

(Figure 4 the intrface of outr software)

4, Database of terminator efficiency

We built a database of terminators whose efficiency had been measured. Not only terminator efficiency , other information such as the direction, category and structure are also included. Some of the data were from partsregistry and Biofab.Terminator Library. Others were from papers. We read many papers to find those terminators and some of the information were got through our e-mail with the author.The database will continue to update to give it more utility.
(Figure 5 our database of terminators whose efficiency have been measured)


South University of Science and Technology of China