diff --git a/wiki/pages/contribution.html b/wiki/pages/contribution.html
index 6a49bd6d8b6218765e5f2026f3b6fe922044522e..b599a8db4d4a1d468a1d6dd1e6a32ae77d7fec9b 100644
--- a/wiki/pages/contribution.html
+++ b/wiki/pages/contribution.html
@@ -464,11 +464,7 @@
<p class="xiaobiaoti" id="s6">2. Recombinant construction plasmid</p>
<div class="wenbenkuang">
- <p>
- As is shown in the figure, our Pymaker originated promoter sequence adds into the frame work of yeast promoter ADH1,
- where <a style="font-weight: bolder">all possible cis elements have been knocked off</a> (‘pT’ and ‘pA’ sign in the figure). Then, the
- whole promoter sequence is ligated into the plasmid framework, driving the expression of <a style="font-weight: bolder">yeGFP</a>.
- </p>
+ <p>As is shown in the figure, our Pymaker originated promoter PYPH/PYPLs consists of two parts: the core promoter and the scaffold. The core promoter is an 80 bp sequence and is seated at approximately -170 to -90 upstream to the codon (which is the presumed transcription start site-TSS and is where most transcription factors binding sites lie). The scaffold is a preserved sequence in all PYPH/PYPLs (‘pT’ and ‘pA’ sign in the figure) . It is a structure that we learned and utilized from previous research that can link the core promoter with the codon and provide restriction sites of BamH I and Xho I which make it possible for the plasmids with the scaffold to be inserted by various core promoter sequences at ease. Then, the whole promoter sequence is ligated into the plasmid framework, driving the expression of YeGFP(details can be found in <a href="http://parts.igem.org/Part:BBa_K4815011">Part:BBa K4815011 - parts.igem.org</a>).</p>
</div>
<br>
diff --git a/wiki/pages/experiments.html b/wiki/pages/experiments.html
index 5256ec89193feef0d653c761f0d14a1ae8630818..c44b7bae2939f86fae5d469019fb47f409cfcd1c 100644
--- a/wiki/pages/experiments.html
+++ b/wiki/pages/experiments.html
@@ -269,7 +269,7 @@ page_content %}
style="margin-bottom: -200px; margin-top: -100px"
>
<div class="book">
- <div class="bp book-page-1" style="--i: 1; --s: 7">
+ <div class="bp book-page-1" style="--i: 1; --s: 8">
<!-- 书皮 -->
<p
style="
@@ -284,7 +284,7 @@ page_content %}
Dry Lab
</p>
</div>
- <div class="bp book-page-2" style="--i: 2; --s: 6">
+ <div class="bp book-page-2" style="--i: 2; --s: 5">
<div class="book-mark">1</div>
<div class="front" padding-right="5px">
<p class="xiaobiaoti">
@@ -298,13 +298,15 @@ page_content %}
consists of a total of 30 million pairs of core promoter
sequences and expression levels. Random synthetic core
promoter sequences are in the front and high-throughput
- measured expression intensities in the back. Specifically,
- the log2(RFP/YFP) of the dual-fluorescent expression
- driven by the promoter is the data (further details in the
- wet lab section).
+ measured expression intensities in the back.
</p>
</div>
<div class="back" padding-right="5px">
+ <p>
+ Specifically, the log2(RFP/YFP) of the dual-fluorescent
+ expression driven by the promoter is the data (further
+ details in the wet lab section).
+ </p>
<p>4.8-4.14</p>
<p>
Initially, we chose DNABERT as the pre-trained model to
@@ -318,12 +320,7 @@ page_content %}
<p>4.14-4.20</p>
<p>
We determined the format of the raw data and wrote code to
- read and transform it into the appropriate format.
- </p>
- <p>
- We developed a code for a linear layer to be added to the
- original BERT model, enabling the use of the BERT
- pre-trained model to obtain a single output.
+ read
</p>
</div>
</div>
@@ -331,6 +328,12 @@ page_content %}
<div class="bp book-page-3" style="--i: 3; --s: 5">
<div class="book-mark">2</div>
<div class="front" padding-right="5px">
+ <p>and transform it into the appropriate format.</p>
+ <p>
+ We developed a code for a linear layer to be added to the
+ original BERT model, enabling the use of the BERT
+ pre-trained model to obtain a single output.
+ </p>
<p>4.21-4.27</p>
<p>
We determined the evaluation metrics for the regression
@@ -338,6 +341,8 @@ page_content %}
correlation coefficient. We then developed code to
calculate these evaluation metrics.
</p>
+ </div>
+ <div class="back" padding-right="5px">
<p>4.28-5.10</p>
<p>
We wrote code to record the evaluation metrics calculated
@@ -349,12 +354,18 @@ page_content %}
multiple GPUs for parallel training and implemented it
through code.
</p>
- </div>
- <div class="back" padding-right="5px">
<p class="xiaobiaoti">Fine-tuning</p>
<p>5.11-5.17</p>
<p>
We reviewed the Nature paper as the source of the data and
+ </p>
+ </div>
+ </div>
+
+ <div class="bp book-page-4" style="--i: 4; --s: 4">
+ <div class="book-mark">3</div>
+ <div class="front">
+ <p>
determined their use of the Adam optimizer and loss
function. We temporarily adopted them as our optimizer and
loss function.
@@ -370,14 +381,8 @@ page_content %}
learning rate until the calculated Pearson correlation
coefficient no longer showed "NUM"
</p>
-
- <p></p>
</div>
- </div>
-
- <div class="bp book-page-4" style="--i: 4; --s: 4">
- <div class="book-mark">3</div>
- <div class="front">
+ <div class="back">
<p>
but displayed a normal numeric value. This helped us
determine the maximum learning rate.
@@ -394,13 +399,18 @@ page_content %}
<p>
Due to the large scale of the entire dataset, training
with all the data consumes a significant amount of time.
+ </p>
+ </div>
+ </div>
+ <div class="bp book-page-5" style="--i: 5; --s: 3">
+ <div class="book-mark">4</div>
+ <div class="front">
+ <p>
Therefore, in the initial stage, a training set consisting
of only 10% of the data is chosen, and the SGD optimizer,
which is suitable for handling random mini-batches of
samples, is utilized.
</p>
- </div>
- <div class="back">
<p>
Subsequently, deep training is performed by gradually
decreasing the learning rate until the Pearson correlation
@@ -410,29 +420,35 @@ page_content %}
<p>6.7-6.13</p>
<p>
We then attempted different optimizers, including a
- variant of Adam called Adamax, RMSprop, which addresses
- the gradient explosion problem and is suitable for
- non-stationary objectives, and Adagrad, which
+ variant of Adam called Adamax, RMSprop,
+ </p>
+ </div>
+ <div class="back">
+ <p>
+ which addresses the gradient explosion problem and is
+ suitable for non-stationary objectives, and Adagrad, which
automatically adjusts the learning rate for each
parameter. However, the Pearson correlation coefficient
remained around 0.84.
</p>
<p>6.14-6.20</p>
- <p></p>
- </div>
- </div>
- <div class="bp book-page-5" style="--i: 5; --s: 3">
- <div class="book-mark">4</div>
- <div class="front">
<p>
During discussions with other iGEM teams, they pointed out
the presence of conserved sequences at both ends of the
original sequences. We speculated that these conserved
sequences may have affected the deep learning feature
- extraction of the model. Subsequently, we removed the
- conserved sequences at both ends and reinitialized the
- training. However, we observed no significant impact, and
- the final performance remained at 0.84.
+ extraction of the model.
+ </p>
+ </div>
+ </div>
+ <div class="bp book-page-6" style="--i: 6; --s: 2">
+ <div class="book-mark">5</div>
+ <div class="front">
+ <p>
+ Subsequently, we removed the conserved sequences at both
+ ends and reinitialized the training. However, we observed
+ no significant impact, and the final performance remained
+ at 0.84.
</p>
<p>6.21-6.27</p>
<p>
@@ -456,6 +472,11 @@ page_content %}
Pearson correlation coefficient reached 0.85, indicating
only a marginal improvement.
</p>
+ </div>
+ </div>
+ <div class="bp book-page-8" style="--i: 7; --s: 1">
+ <div class="book-mark">6</div>
+ <div class="front">
<p>6.27-7.10</p>
<p>
We used our model to predict the efficient and the lowest
@@ -463,28 +484,10 @@ page_content %}
sequences and chose 10 efficient promoters and 3
inefficient promoters randomly.
</p>
- </div>
- </div>
- <div class="bp book-page-6" style="--i: 6; --s: 2">
- <div class="book-mark">5</div>
- <div class="front">
<p>
The efficiency of these promoters were tested by the wet
lab.
</p>
- <p></p>
- </div>
- <div class="back">
- <p class="xiaobiaoti"></p>
- <p></p>
- </div>
- </div>
-
- <div class="bp book-page-8" style="--i: 7; --s: 1">
- <div class="book-mark">6</div>
- <div class="front">
- <p class="xiaobiaoti"></p>
- <p></p>
</div>
<div class="back">
<p class="xiaobiaoti"></p>
@@ -537,12 +540,13 @@ page_content %}
</p>
<p>
The plasmids were stored at -20℃(the plasmids were
- introduced with the AmpR gene and the URA3 gene)
+ introduced with the
</p>
- <p>Made 20 YPD culture medium added Amp</p>
- <p>Made the yeast-competent cells and store at -80℃</p>
</div>
<div class="back">
+ <p>AmpR gene and the URA3 gene)</p>
+ <p>Made 20 YPD culture medium added Amp</p>
+ <p>Made the yeast-competent cells and store at -80℃</p>
<p>7.14-7.20</p>
<p>
Inserted the mcherry plasmid and mcherry+YeGFP plasmid
@@ -554,7 +558,12 @@ page_content %}
°C for 72 h. Screen the colonies on the YPD solid medium
with amp.
</p>
+ </div>
+ </div>
+ <div class="bp book-page-3" style="--i: 3; --s: 6">
+ <div class="book-mark">2</div>
+ <div class="front">
<p>
Made the YPD and Sc-Ura fluid nutrient medium and
autoclaved it for 20 minutes.
@@ -569,17 +578,13 @@ page_content %}
YPD fluid nutrient medium and we inserted the plasmid
again.
</p>
- </div>
- </div>
-
- <div class="bp book-page-3" style="--i: 3; --s: 6">
- <div class="book-mark">2</div>
- <div class="front">
<p>7.21-7.27</p>
<p>
Extracted the plasmids from the yeast and store it at
-80℃.
</p>
+ </div>
+ <div class="back">
<p>
After Diluted the yeast for four times in 48h, with the
first and the second time using the YPD,while the third
@@ -597,7 +602,10 @@ page_content %}
reportthemcherry or the GFP expression signal
</p>
</div>
- <div class="back">
+ </div>
+ <div class="bp book-page-4" style="--i: 4; --s: 5">
+ <div class="book-mark">3</div>
+ <div class="front">
<p>
Made the slide using the INVSC1 yeasts cell suspension
and then oberserved the slides under the fluorescent
@@ -612,15 +620,12 @@ page_content %}
totally 20 plasmids.
</p>
<p>Made 40 YPDA culture mediums added Amp</p>
+ </div>
+ <div class="back">
<p>
Cultivated the INVSC1 yeasts for three days and made the
INVSC1 yeast-competent cells and store at -80℃
</p>
- </div>
- </div>
- <div class="bp book-page-4" style="--i: 4; --s: 5">
- <div class="book-mark">3</div>
- <div class="front">
<p>8.11-8.17</p>
<p>
Inserted the plasmids into the INVSC1 yeast, all the
@@ -633,12 +638,15 @@ page_content %}
out the single colony into the YPD fluid nutrient medium
and putting into the 30℃ horizontal rotators.
</p>
+ </div>
+ </div>
+ <div class="bp book-page-5" style="--i: 5; --s: 4">
+ <div class="book-mark">4</div>
+ <div class="front">
<p>
The INVSC1 yeasts which were inserted with H1, ADH
plasmid failed to grow on the culture medium.
</p>
- </div>
- <div class="back">
<p>8.18-8.24</p>
<p>
Diluted the INVSC1 yeasts for four times in 48h, the
@@ -652,14 +660,13 @@ page_content %}
<p>
During the dilution,the INVSC1 yeasts which were
inserted with H2,H4,H6,H7,L3,TEF,LTB-eGFP were polluted.
+ </p>
+ </div>
+ <div class="back">
+ <p>
We inserted these plasmids into the INVSC1 yeasts
renewedly.
</p>
- </div>
- </div>
- <div class="bp book-page-5" style="--i: 5; --s: 4">
- <div class="book-mark">4</div>
- <div class="front">
<p>8.25-8.31</p>
<p>
After inserting the plasmid renewedlly, incubating the
@@ -674,12 +681,16 @@ page_content %}
OD600 of this diluted INVSC1 yeast suspension.
Centrifuged at 4 °C at 3,500 rpm for 7 min and washed it
with PBS for two times , useing flow cytometry to
- reportthemcherry and GFP expression signal
+ reportthemcherry and
</p>
+ </div>
+ </div>
+ <div class="bp book-page-6" style="--i: 6; --s: 3">
+ <div class="book-mark">5</div>
+ <div class="front">
+ <p>GFP expression signal</p>
<p class="xiaobiaoti">LTB-yeGFP</p>
<p>9.1-9.7</p>
- </div>
- <div class="back">
<p>
Extracted all the plasmids from the targeted
microorganism and stored it at -80℃ renewedly to get the
@@ -692,6 +703,8 @@ page_content %}
amplify. Ligated the LTB-eGFP plasmid frame with the
synthesized promoter and the nature promoter one by one.
</p>
+ </div>
+ <div class="back">
<p>9.8-9.14</p>
<p>
After we got the synthesized plasmid, inserted these
@@ -702,11 +715,6 @@ page_content %}
Extracted the synthesized plasmids from the yeasts and
store it at -80℃ to backup.
</p>
- </div>
- </div>
- <div class="bp book-page-6" style="--i: 6; --s: 3">
- <div class="book-mark">5</div>
- <div class="front">
<p>
During the extraction, we failed to extract the plasmids
and we extracted renewedly. Made 40 YPDA culture mediums
@@ -716,6 +724,11 @@ page_content %}
Made the YPD and Sc-Ura fluid nutrient medium and
autoclaved it for 20 minutes.
</p>
+ </div>
+ </div>
+ <div class="bp book-page-7" style="--i: 7; --s: 2">
+ <div class="book-mark">6</div>
+ <div class="front">
<p>9.15-9.21</p>
<p>
The INVSC1 yeasts with synthesized plasmids were
@@ -725,15 +738,18 @@ page_content %}
Each sample took four single conoly and cultivated
individually with four 50ml centrifuge tube.
</p>
- <p></p>
- </div>
- <div class="back">
<p>
Diluted the INVSC1 yeasts with synthesized plasmids for
four times, measuring OD600 of this diluted INVSC1 yeast
suspension. Centrifuged at 4 °C at 3,500 rpm for 7 min
- and washed it with PBS for two times , useing flow
- cytometry to reporttheLTB-eGFP expression signal.
+ and washed it
+ </p>
+ </div>
+ <div class="back">
+ <p class="xiaobiaoti" style="margin: 0px"></p>
+ <p>
+ with PBS for two times , useing flow cytometry to
+ reporttheLTB-eGFP expression signal.
</p>
<p>9.22-9.28</p>
<p>
@@ -748,29 +764,17 @@ page_content %}
Ran the SDS gel of the INVSC1 yeasts and chose a
suitable WB internal reference.
</p>
+
</div>
</div>
- <div class="bp book-page-7" style="--i: 7; --s: 2">
- <div class="book-mark">6</div>
- <div class="front">
- <p>9.29-11.5</p>
+ <div class="bp book-page-8" style="--i: 8; --s: 1">
+ <div class="book-mark">7</div>
+ <div class="front"><p><p>9.29-11.5</p>
<p>
We used the Gapdh as the internal reference and ran the
SDS gel, we also ran the Q-PCR to detect the gene
expression.
- </p>
-
- <p></p>
- <p></p>
- </div>
- <div class="back">
- <p class="xiaobiaoti" style="margin: 0px"></p>
- <p></p>
- <p></p>
- </div>
- </div>
- <div class="bp book-page-8" style="--i: 8; --s: 1">
- <div class="book-mark">7</div>
+ </p></p></div>
</div>
</div>
</div>