Difference between revisions of "Team:USTC/Software"
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<p>This is the final program used to get our NDM calibration. Based on this software program, we are able to count the number of bright fringes. As a matter of fact, the variation of bright fringes is the key breakthrough to antibiotic analysis.</p> | <p>This is the final program used to get our NDM calibration. Based on this software program, we are able to count the number of bright fringes. As a matter of fact, the variation of bright fringes is the key breakthrough to antibiotic analysis.</p> | ||
<p>Code</p> | <p>Code</p> | ||
− | < | + | <div><textarea id="code3" name="code">function seeim(i) |
name=num2str(i); | name=num2str(i); | ||
I=imread(name,'pnm'); | I=imread(name,'pnm'); | ||
G=rgb2gray(I); | G=rgb2gray(I); | ||
imshow(G); | imshow(G); | ||
− | </ | + | </textarea></div><p>Demo<br><img src="https://static.igem.org/mediawiki/2015/2/2d/20150919072.png" alt="Figure 4: Checking figure program"></p> |
− | < | + | <div><textarea id="code4" name="code">function A=getfr(i) |
name=num2str(i); | name=num2str(i); | ||
I=imread(name,'pnm'); | I=imread(name,'pnm'); | ||
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end | end | ||
A=r; | A=r; | ||
− | </ | + | </textarea></div><div><textarea id="code5" name="code">function M=getfrs(i) |
A=getfr(i); | A=getfr(i); | ||
t=1:480; | t=1:480; | ||
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[a,k]=size(pksa); | [a,k]=size(pksa); | ||
M=a; | M=a; | ||
− | </ | + | </textarea></div><p>Running result<br>ans =<br> 78</p> |
<p><img src="https://static.igem.org/mediawiki/2015/c/c1/20150919073.png" alt="Figure 5: Fringes counting program running result"></p> | <p><img src="https://static.igem.org/mediawiki/2015/c/c1/20150919073.png" alt="Figure 5: Fringes counting program running result"></p> | ||
<p>To get a series of results, this program is required.</p> | <p>To get a series of results, this program is required.</p> | ||
− | < | + | </textarea></div><div><textarea id="code6" name="code">function N=getpkss(i,j) |
B=zeros(j-i+1,1); | B=zeros(j-i+1,1); | ||
for m=i:j | for m=i:j | ||
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end | end | ||
N=B; | N=B; | ||
− | </ | + | </textarea></div><p>Demo</p> |
<p>ans =</p> | <p>ans =</p> | ||
− | < | + | <div><textarea id="code7" name="code">78 |
80 | 80 | ||
77 | 77 | ||
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81 | 81 | ||
79 | 79 | ||
− | </ | + | </textarea></div> |
</div> | </div> | ||
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<p>This program is used to count the total number of bacteria.</p> | <p>This program is used to count the total number of bacteria.</p> | ||
<p>Code</p> | <p>Code</p> | ||
− | < | + | <div><textarea id="code8" name="code">function a=shujun(i) |
name=num2str(i); | name=num2str(i); | ||
I=imread(name,'jpg'); | I=imread(name,'jpg'); | ||
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a=num; | a=num; | ||
end | end | ||
− | </ | + | </textarea></div><p>Demo</p> |
<p>input image:<br><img src="https://static.igem.org/mediawiki/2015/0/0e/20150919074.jpg" alt="Figure 6: Adhesion Assay image"><br>output result<br>ans =<br> 865</p> | <p>input image:<br><img src="https://static.igem.org/mediawiki/2015/0/0e/20150919074.jpg" alt="Figure 6: Adhesion Assay image"><br>output result<br>ans =<br> 865</p> | ||
− | < | + | <div><textarea id="code8" name="code">function A=mulshu(m) |
A=zeros(m,1); | A=zeros(m,1); | ||
for i=1:m | for i=1:m | ||
A(i,1)=shujun(i); | A(i,1)=shujun(i); | ||
end | end | ||
− | </ | + | </textarea></div> |
<div class="divider"></div> | <div class="divider"></div> | ||
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<p>This program is used to count the total number of moving bacteria. Along with bacterial counting program, we finally got the mechanism of polylysine interaction.</p> | <p>This program is used to count the total number of moving bacteria. Along with bacterial counting program, we finally got the mechanism of polylysine interaction.</p> | ||
<p>Code</p> | <p>Code</p> | ||
− | < | + | <div><textarea id="code9" name="code">function b=act(m,n) |
s1=num2str(m); | s1=num2str(m); | ||
s2=num2str(n); | s2=num2str(n); | ||
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b=shujun(G); | b=shujun(G); | ||
end | end | ||
− | </ | + | </textarea></div><div><textarea id="code9" name="code">function A=mulact(m) |
A=zeros(m,1); | A=zeros(m,1); | ||
for i=1:m | for i=1:m | ||
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A(i,1)=c; | A(i,1)=c; | ||
end | end | ||
− | </ | + | </textarea></div><p>Demo</p> |
<p>ans =<br> 405 </p> | <p>ans =<br> 405 </p> | ||
<div class="divider"></div> | <div class="divider"></div> | ||
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<h4 id="Bacteria-total-number-time-curve" class="scrollspy">Bacteria total number-time curve</h4> | <h4 id="Bacteria-total-number-time-curve" class="scrollspy">Bacteria total number-time curve</h4> | ||
<p>Coding</p> | <p>Coding</p> | ||
− | < | + | </textarea></div><div><textarea id="code10" name="code">function drawBT1(Ka,Kd,C,Vz,sigma0)%Ka is the adhesive rate of bacteria, Kd is the drop rate of bacteria, C is the density of bacteria solution,Vz is the velocity of bacteria,sigma0 is the maximum density of baacteria on surface |
t=linspace(0,100,101); | t=linspace(0,100,101); | ||
K=Ka*C*Vz/(Kd*sigma0+Ka*C*Vz); | K=Ka*C*Vz/(Kd*sigma0+Ka*C*Vz); | ||
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plot(t,sigma) | plot(t,sigma) | ||
end | end | ||
− | </ | + | </textarea></div><p>Running result<br><img src="https://static.igem.org/mediawiki/2015/9/99/20150901024.png" alt="Figure 7: Movement number simulation result"></p> |
<div class="divider"></div> | <div class="divider"></div> | ||
<h4 id="Bacteria-movement-number-Time-curve" class="scrollspy">Bacteria movement number-Time curve</h4> | <h4 id="Bacteria-movement-number-Time-curve" class="scrollspy">Bacteria movement number-Time curve</h4> | ||
<p>Coding</p> | <p>Coding</p> | ||
− | < | + | <textarea id="code11" name="code">function drawBMT(c,b,m0,k) |
t=linspace(0,100,101); | t=linspace(0,100,101); | ||
M=c*(1-exp(-b*t))*m0.*exp(-k*t); | M=c*(1-exp(-b*t))*m0.*exp(-k*t); | ||
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title('PAO1-PLL-0 Movement number-time'); | title('PAO1-PLL-0 Movement number-time'); | ||
end | end | ||
− | </ | + | </textarea></div><p>Running result<br><img src="https://static.igem.org/mediawiki/2015/8/88/20150907052.png" alt="Figure8:Bacteria movement number-Time simulation result"></p> |
</div> | </div> | ||
</div> | </div> | ||
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<p>This program is used to predict the advantages of ROSE construction. We successfully demonstrate our ROSE will be able to amplify fluorescence siganl.</p> | <p>This program is used to predict the advantages of ROSE construction. We successfully demonstrate our ROSE will be able to amplify fluorescence siganl.</p> | ||
<p>Code</p> | <p>Code</p> | ||
− | < | + | <textarea id="code12" name="code">clear all |
R=R,k=k,k1=k1,k2=k2,k3=k3,k4=k4,k5=k5,k6=k6,k7=k7,k0=k0; %define the constant | R=R,k=k,k1=k1,k2=k2,k3=k3,k4=k4,k5=k5,k6=k6,k7=k7,k0=k0; %define the constant | ||
t=linspace(0,10); %detecting time range | t=linspace(0,10); %detecting time range | ||
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hold on | hold on | ||
plot(k0*t,t); %print the traditional strategy result in the same image | plot(k0*t,t); %print the traditional strategy result in the same image | ||
− | </ | + | </textarea></div><p>Demo</p> |
<p><img src="https://static.igem.org/mediawiki/2015/1/1b/20150906Circuit.jpg" alt="Figure 9: ROSE Dynamics simulation result" data-image-src="https://static.igem.org/mediawiki/2015/1/1b/20150906Circuit.jpg"></p> | <p><img src="https://static.igem.org/mediawiki/2015/1/1b/20150906Circuit.jpg" alt="Figure 9: ROSE Dynamics simulation result" data-image-src="https://static.igem.org/mediawiki/2015/1/1b/20150906Circuit.jpg"></p> | ||
</div> | </div> | ||
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}); | }); | ||
− | var | + | var editor = CodeMirror.fromTextArea(document.getElementById("code2"), { |
mode: {name: "octave", | mode: {name: "octave", | ||
version: 2, | version: 2, | ||
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matchBrackets: true | matchBrackets: true | ||
}); | }); | ||
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</script> | </script> | ||
</html> | </html> | ||
{{USTC/footer}} | {{USTC/footer}} |
Revision as of 23:56, 18 September 2015
In this section, we will introduce all the software program we used when processing our modeling and experimental data. Through our modeling, many complicated processdures are simply omitted by our convenient programs.
In general, our software programs are used in several sections,
- Fringes Analysis, analysis of interference pattern.
- Adhesion Dynamics, a series of programs relating to bacteria adhesion dynamics.
- Rose Prediction, which calculate the advantages of our ROSE improvement.
All software of our project, you can download them at Github:2015USTCiGEM. All codes are based on
Fringes Pattern Simulation-Film I
This program is used to simulate fringes pattern deliverd by film I.
Code:
Demo
After the formation of demo, we are able to recongize the real situation in our pre-experiment.
Fringes Pattern Simulation-Film II
This program is used to simulate fringes pattern deliverd by film II.
Code
Demo
Film I Fringes Analysis
Using this code, we are able to capture some important parameters in Film I.
Code
Demo
Film II Fringes Analysis-Fringes number analysis
This is the final program used to get our NDM calibration. Based on this software program, we are able to count the number of bright fringes. As a matter of fact, the variation of bright fringes is the key breakthrough to antibiotic analysis.
Code
Demo
Running result
ans =
78
To get a series of results, this program is required.
Demo
ans =
During analysis of ahdesion assay results, we are quite annoyed about counting total bacteria number and moving bacteria number, which is really important for mechanism analysis and results determination. Consequently, this part explains how we efficiently accomplished these tough work based on our software.
Bacteria counting program
This program is used to count the total number of bacteria.
Code
Demo
input image:
output result
ans =
865
Moving Bacteria Counting Program
This program is used to count the total number of moving bacteria. Along with bacterial counting program, we finally got the mechanism of polylysine interaction.
Code
Demo
ans =
405
Bacteria total number-time curve
Coding
Running result
Bacteria movement number-Time curve
Coding
Running result
This program is used to predict the advantages of ROSE construction. We successfully demonstrate our ROSE will be able to amplify fluorescence siganl.
Code
Demo