Team:Paris Liliane Bettencourt/Project/SIP/Results

From 2010.igem.org

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[https://2010.igem.org/Team:Paris_Liliane_Bettencourt/Project/SIP/Downloads We have calculate SIP words for each team and each year since 2007] using [https://2010.igem.org/Team:Paris_Liliane_Bettencourt/Project/SIP/Codes SIP.C], for each them we have take the 25 top sip valued words. We use [https://2010.igem.org/Team:Paris_Liliane_Bettencourt/Project/SIP/Codes TOP_SIP.C] to make that, this software see what is the hight SIP value and then '''take N words with this hight SIP'''.
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[https://2010.igem.org/Team:Paris_Liliane_Bettencourt/Project/SIP/Downloads We have calculated SIP words for each team and each year since 2007] using [https://2010.igem.org/Team:Paris_Liliane_Bettencourt/Project/SIP/Codes SIP.C], for each them we have take the 25 top sip valued words. We use [https://2010.igem.org/Team:Paris_Liliane_Bettencourt/Project/SIP/Codes TOP_SIP.C] to make that, this software see what is the hight SIP value and then '''take N words with this hight SIP'''.
When we got our words, we put in a [http://www.wordle.net/ software], to display them with graphical effect : words with hight frequencies has a big font, and words with low frequencies has a small font.
When we got our words, we put in a [http://www.wordle.net/ software], to display them with graphical effect : words with hight frequencies has a big font, and words with low frequencies has a small font.
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First, we analyse the [http://parts.mit.edu/igem07/index.php/Paris team Paris 2007] and we get that (we have selected 60 words to get, with a filter : all words like "p1", "f23" are removed) :
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This is the analysis for [http://parts.mit.edu/igem07/index.php/Paris team Paris 2007].We have selected 60 words and filtered out all words like "p1", "f23".
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You can see some gene displayed on the screen, which characterize the project :
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Just to let judge by yourself, here is the abstract of the 2007 Paris team.
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*'''smb''' : the name of the project.
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*'''cre/lox/lox66/DGAT/dapA''' etc. name of recomination site, molecules and genes, '''characterize''' their project.
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Revision as of 00:09, 28 October 2010



SIP Wiki Analyser







We have calculated SIP words for each team and each year since 2007 using SIP.C, for each them we have take the 25 top sip valued words. We use TOP_SIP.C to make that, this software see what is the hight SIP value and then take N words with this hight SIP. When we got our words, we put in a [http://www.wordle.net/ software], to display them with graphical effect : words with hight frequencies has a big font, and words with low frequencies has a small font.

Just to give you a glimpse of what our software can do and how it can characterise a project, here is some examples we made on last years' winners and on the Paris 2007 team. The aim of all this is to try to extract the main ideas or key terms of a given wiki.


Paris Team

This is the analysis for [http://parts.mit.edu/igem07/index.php/Paris team Paris 2007].We have selected 60 words and filtered out all words like "p1", "f23".


Sipwords paris2007.gif

Just to let judge by yourself, here is the abstract of the 2007 Paris team.
Subject of the project Paris 2007 was :

"The aim of our project is to engineer the first synthetic multicellular bacterium, the SMB. This new organism is a novel tool for the engineering of complex biological systems. It consists in two interdependent cell lines. The first, dedicated to reproduction is the germ line (red cells in the simulation below). It is able to differentiate into the second line: the soma (green cells), which is sterile and dedicated to support the germ line. The germ line is auxotroph for DAP (diaminopimelate) which is provided by the soma. There is thus an interdependency relationship. The soma, being sterile, requires the germ line for its generation, while the germ line needs the soma to complement its auxotrophy. We provide here both experimental and computational evidences that this system can work, as well as the almost complete construction of the SMB."

Last iGEM Winner

Next we have generate image for the three last iGEM winner.


Peking 2007

Sipwords peking.gif


Slovenia 2008

Sipwords slovenia.gif


Cambridge 2009

Sipwords cambridge.gif



iGEM Ranking

We try to aproach our first goal with determining the high words used by the last iGEM winner. So we generate for 2007 and 2009 year. We attribute points to winner using the next rules. We keep 15 words by team. Notice, people name and miss spelling words are remove to have a better display.

  • Grand prize : 5 pts.
  • Finalist : 3pts.
  • Other prize : 1pt.
  • Winner : 5pts.
  • 1st Runner up : 4pts.
  • 2nd runner up: 3pts.
  • Runner up : 2pts.


2007 year :

  • Peking: 6 pts.
  • Ljubljana: 4 pts.
  • Paris: 4 pts.
  • UCSF: 3 pts.
  • USTC: 4 pts.
  • Glasgow: 1 pt.
  • Alberta: 1 pt.
  • Cambridge: 1 pt.
  • Melbourne: 1 pt.
  • UC Berkeley: 1 pt.
  • Calgary: 1 pt.
  • ETHZ: 1 pt.


Sipwords 2007.gif


2009 year

  • Alberta: 1 pt.
  • ArtScienceBangalore: 1 pt.
  • BCCS-Bristol: 1 pt.
  • Berkeley Software: 1 pt.
  • Cambridge: 6 pts.
  • EPF-Lausanne: 1 pt.
  • Freiburg bioware: 4 pts.
  • Groningen: 2 pts.
  • Heidelberg: 6 pts
  • Illinois-Tools: 1 pt.
  • Imperial College London: 4 pts.
  • Paris: 1 pt.
  • Stanford: 1 pt.
  • TUDelft: 1 pt.
  • ULB-Brussels: 1 pt.
  • UNIPV-Pavia: 1 pt.
  • Valencia: 5 pts.


Sipwords 2009.gif