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Team:Warsaw/Software
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| - | <div class="note"> | + | <div class="note">Instalation</div> |
| - | <div> | + | <div align="justify"> |
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| + | The expression adaptors generator software is written in Java 6 and distributed as <a href="http://eclipse.org">Eclipse</a> project. It depends on RBSCalculator [H.M. Salis, E.A. Mirsky, C.A. Voigt, Nat. Biotech., 2009] which depends on <a href="http://www.nupack.org/">Nupack</a> and VennaRNA software packages. This restricts platform compatibility because Nupack can only run on Linux. After importing project to Eclipse please change <i>executables.ExpressionAdaptorGenerator.ViennaRNAPath</i> to reflect location of NuPack and Vienna executables (usualy /usr/local/bin). </div> | ||
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| + | <div class="note">Structure</div> | ||
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| + | Expression Adaptors generator consists of two main programs <i>ExpressionAdaptorsGenerator.java</i> which implements genetic algorithm frontend and <i>GenerationToFasta.java</i> which performs data analysis. | ||
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| + | <div class="note">How it works</div> | ||
| + | <div align="justify"> | ||
| + | The algorithm itself is described <a href="https://2011.igem.org/Team:Warsaw/ExpressionAdaptors/Solution">here</a>. Its implemented in <i>dataStructures.Generation class</i>. </div> | ||
| + | <p align="justify"> | ||
| + | The most important thing about implementation is fact that it's recursive. Calling copy constructor dataStructures.Generation(Generation prevGen) causes automaticaly random recombination of adaptors, their mutation and calculation of expression srtength for all proteins defined in proteins array of particular Generation class instance. This simplifies rest of the code because recursive calling of Generation copy constructor is all you need to do for basic implementation of this algorithm. This functionality is illustrated in <i>ExpressionAdaptorsGenerator.java</i>. | ||
| + | </p> | ||
| + | <p align="justify"> | ||
| + | Additionally </i>ExpressionAdaptorsGenerator</i> saves each generation of adaptors to separate file generationXXX.sav in save directory. This provides resume point i case of abnormal termination of the program and also serves as a data source for the second program - <i>GenerationToFasta</i>. It serves as data anlysis tool that picks best hits from all generations and produces file in FASTA format. | ||
| + | </p> | ||
| + | </div> | ||
| + | </div> | ||
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Latest revision as of 20:18, 21 September 2011
Instalation
The expression adaptors generator software is written in Java 6 and distributed as Eclipse project. It depends on RBSCalculator [H.M. Salis, E.A. Mirsky, C.A. Voigt, Nat. Biotech., 2009] which depends on Nupack and VennaRNA software packages. This restricts platform compatibility because Nupack can only run on Linux. After importing project to Eclipse please change executables.ExpressionAdaptorGenerator.ViennaRNAPath to reflect location of NuPack and Vienna executables (usualy /usr/local/bin).
Structure
Expression Adaptors generator consists of two main programs ExpressionAdaptorsGenerator.java which implements genetic algorithm frontend and GenerationToFasta.java which performs data analysis.
How it works
The algorithm itself is described here. Its implemented in dataStructures.Generation class.
The most important thing about implementation is fact that it's recursive. Calling copy constructor dataStructures.Generation(Generation prevGen) causes automaticaly random recombination of adaptors, their mutation and calculation of expression srtength for all proteins defined in proteins array of particular Generation class instance. This simplifies rest of the code because recursive calling of Generation copy constructor is all you need to do for basic implementation of this algorithm. This functionality is illustrated in ExpressionAdaptorsGenerator.java.
Additionally ExpressionAdaptorsGenerator saves each generation of adaptors to separate file generationXXX.sav in save directory. This provides resume point i case of abnormal termination of the program and also serves as a data source for the second program - GenerationToFasta. It serves as data anlysis tool that picks best hits from all generations and produces file in FASTA format.
