Difference between revisions of "Team:SEU/Collaborations"

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                                          <h2>Collaboration</h2>
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      .diagram{
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                                          <p>As a competition encouraging cooperation, our team has established a partnership with the team NANJING-CHINA in Nanjing University. Considering that both Southeast University and Nanjing University are originated from the National Central University and located in the same city, two teams often exchange ideas on research. With mutual help, we improved our professionalism and promoted friendship with other teams.</p>
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            /*width:1320px;*/
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                                          <p>In this year, NANJING-CHINA has mainly developed a simple solo medium copy plasmid-based polyphosphate kinase (PPK1) overexpression strategy for achieving maximum intracellular polyphosphate accumulation by environmental bacteria. The team SEU gives the views on data modeling, including data fitting for the overall process and solving differential equations for bacterial concentration changes. SEU helps to propose a curve of the concentration of bacteria in the whole process of absorbing and releasing phosphorus and the concentration of elements in the solution. Finally, two teams exchange opinions on the selection of variables and fitting parameters.</p>
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                                          <p>At the same time, SEU’s project focuses on the experiment based on DNA to achieve molecular calculations, which is a promising emerging technology. In the seminar between SEU and NANJING-CHINA, members of two teams discuss the engineering ethics behind this technology, and analyze how genetic engineering technology changes society. At the same time, molecular computational techniques with high parallelism and recognition capabilities in chemical reactions are discussed.</p>
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                                          <p>Finally, two teams also cooperate in other areas such as the collaboration on IGEM's web design, the beautification of team clothing and logo, the airfare, and accommodation arrangements. The cooperation with NANJING-CHINA is enjoyable and rewarding. We hope that two teams continue to cooperate in the iGEM competition next year.</p>
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        <div id="fullpage" class="fullpage-default">
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            <div>
 +
                <div class="section-inner">
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                    <div class="about-section">
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                        <div class="row justify-content-center">
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                            <div>
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                                <div class="row">
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                                    <div class="about-contentbox">
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                                        <br><br><br><br>
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                                        <h1>User Instruction</h1>
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                                        <p align="left">This tool is developed to generate DNA-based neural networks and corresponding DNA sequences. We simply provide the reactions that are required in a single neuron, as a layer of neural network can be directly implemented by combining each neuron.</p>
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                                        <p align="left">To use this tool, users should firstly specify the number of inputs to a neuron by typing the value in the <b>Number</b> frame and click <b>Submit</b>. After clicking the <b>Submit</b> button, sequences will be generated and shown in the lower diagram. Users can also click the <b>Download Sequences</b> button to download the generated sequences as a .txt file.</p>
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                                        <p align="left">By cliking on the three figures below the <b>Number</b> frame, reactions utilized in the three parts of the neuron will be shown respectively. Structures of DNA strands will be given in the upper diagram.</p>
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 +
                                        <p>Our theory is able to construct a neuron with arbitrary inputs. However, due to the limitation of computation capacity of web browsers, we limit the number of inputs of each neuron to 8 (generation of a DNA-based neuron might take 0-20 seconds depending on the input size).</p>
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                                        <img src="https://static.igem.org/mediawiki/2019/a/a8/T--SEU--tool.png" style="background-color: transparent;width:80%"><br><br>
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                                        <center>
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                                        Number:
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                                        <input type="text" id="number" name="number" value="">
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                                        <button onclick="clearCanvas();draw();showSeq();" type="submit">Submit</button><br><br>
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                                        <div id="alreadySubmit"></div>
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                                        <button onclick="clearCanvas();drawWeightedSum([2*DNAseperate,2*DNAseperate]);" class="buttonInputLayer">Click to show: Weighted Sum</button>
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                                        <button onclick="clearCanvas();drawSubNeuron([2*DNAseperate,2*DNAseperate]);" class="buttonActivation">Click to show: Activation</button>
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                                        <button onclick="clearCanvas();drawBackprop([2*DNAseperate,2*DNAseperate]);" class="buttonBackpropagation">Click to show: Backpropagation</button><br>
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                                    <body>
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                                                <div class="diagram" id="words">
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                                                    <!-- <script type="text/javascript">draw();</script> -->
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                                                </div>
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                                                <button onclick="windowSeq();">Download Sequences</button>
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                                                <div class="sequence" id="sequence">
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                                                  <!-- <canvas id="seqCanvas"  width="200" height="20000"></canvas> -->
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                                                    <!-- <script type="text/javascript">draw();</script> -->
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                                                </div>
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Revision as of 05:00, 3 October 2019









User Instruction

This tool is developed to generate DNA-based neural networks and corresponding DNA sequences. We simply provide the reactions that are required in a single neuron, as a layer of neural network can be directly implemented by combining each neuron.

To use this tool, users should firstly specify the number of inputs to a neuron by typing the value in the Number frame and click Submit. After clicking the Submit button, sequences will be generated and shown in the lower diagram. Users can also click the Download Sequences button to download the generated sequences as a .txt file.

By cliking on the three figures below the Number frame, reactions utilized in the three parts of the neuron will be shown respectively. Structures of DNA strands will be given in the upper diagram.

Our theory is able to construct a neuron with arbitrary inputs. However, due to the limitation of computation capacity of web browsers, we limit the number of inputs of each neuron to 8 (generation of a DNA-based neuron might take 0-20 seconds depending on the input size).



Number: