Team:SUSTC-Shenzhen-B/future plan
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- | <a href="http://www.terminatorefficiency.com/ | + | <a href="http://www.terminatorefficiency.com/software.aspx"><h2><p>Future Version of Our Software</a></p></h2> |
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Latest revision as of 03:35, 27 September 2012
Future Version of Our Software
Introduction
Now our pc software and online tool can predict the efficiency of rho-independent terminator. The algorithm is based on two scoring systems, which were created by d'Aubenton Carafa and Elena A Lesnik respectively. In the future, we want to better predict the efficiency of terminators using better formula and create a model of terminator efficiency prediction. What’s more, we hope we can do mutation on user’s terminator sequence to give a derived terminator which meet the user’s requirement of efficiency.
Future Plan
1. Mutate the coefficients of the scoring formular to help get the best simulation formular of score and efficiency
The formula of d score calculation is :
D Score = nT * 18.16 + deltaG / LH * 96.59 – 116.87
(nT is the score of t tail, deltaG is the energy change of the stemloop formation and LH is the length of stemloop sequence.)
Here the coefficient of each terms can be adjusted to help make the best simulation between score and efficiency. We can even try to treat efficiency as a function of those terms directly, which means we can calculate terminator efficiency using nt, deltaG and LH directly without calculating the score first, ie : Efficiency = E(nt, deltaG,LH).
2. Create a model of terminator efficiency prediction
The score of terminator includes two parts, stemloop and ttail. We can do some experiments to know how stemloop and ttail effect the efficiency of terminators and then create a model of that. We’ve bought about 100 terminators sequences. These sequences are mutated in their stem,loop or t tail. We will measure their efficiency and then analyze the experiment data to find some regular pattern and create our own model.
3. Modify the terminator sequence to match the user selected efficiency
Sometimes the user wants a terminator with specific efficiency. If the current efficiency of users terminator is not the one he want, our program can do mutation on terminator sequences and evolve a terminator that meets the requirement of efficiency.