Difference between revisions of "Team:SKLMT-China/SoftWare Overview"
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| + | <h2 class="title">Results</h2> | ||
| + | <p class="content">Who are we?</p> | ||
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| + | <li><a href="https://2018.igem.org/Team:SKLMT-China"><i class="fa fa-home">  Home</i></a></li> | ||
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| + |   Overview | ||
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| + | <li><a href="#s1" class="scrolly">Introduction</a></li> | ||
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| − | <h2 class="title">introduction</h2> | + | <h2 class="title" id="s1">introduction</h2> |
<p>This year, the team SKLMT-China established a useful software tool based on our own wet lab results to help people easily search and predict a proper promoter for fine-tuning gene expression in the synthetic study. To make the <latin>Pseudomonas fluorescence </latin>a well-exploited chassis bacteria in synthetic biology, we develop a software <b>DePro </b>(promoter searching and strength prediction website based on deep learning and python), which enables our research results to interact well with other teams. With the expansion of the promoter data, it can quickly calculate the strength level of the new promoter with the help of our model. After entering the core sequence, our python program will calculate the strength level of the promoter for you. In some way, the software<b>DePro </b>is a collection of our wet lab results and achievements.</p> | <p>This year, the team SKLMT-China established a useful software tool based on our own wet lab results to help people easily search and predict a proper promoter for fine-tuning gene expression in the synthetic study. To make the <latin>Pseudomonas fluorescence </latin>a well-exploited chassis bacteria in synthetic biology, we develop a software <b>DePro </b>(promoter searching and strength prediction website based on deep learning and python), which enables our research results to interact well with other teams. With the expansion of the promoter data, it can quickly calculate the strength level of the new promoter with the help of our model. After entering the core sequence, our python program will calculate the strength level of the promoter for you. In some way, the software<b>DePro </b>is a collection of our wet lab results and achievements.</p> | ||
<p>Our Depro system is a platform for promoter researchers to exchange data and share results. Everyone can benefit from the test results of previous researchers or enrich our software with new test data to improve the accuracy of the fit. Through our software, you can:</p> | <p>Our Depro system is a platform for promoter researchers to exchange data and share results. Everyone can benefit from the test results of previous researchers or enrich our software with new test data to improve the accuracy of the fit. Through our software, you can:</p> | ||
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<p>(2) Use a new set of data to enrich the program's deep learning process. Your data will be imported into our database and will accompany our program to complete every deep learning in the future</p> | <p>(2) Use a new set of data to enrich the program's deep learning process. Your data will be imported into our database and will accompany our program to complete every deep learning in the future</p> | ||
<p>(3) Freely set the number of times to learn. You are free to decide how quickly and precisely your program will run to meet your needs</p> | <p>(3) Freely set the number of times to learn. You are free to decide how quickly and precisely your program will run to meet your needs</p> | ||
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Revision as of 18:15, 17 October 2018
introduction
This year, the team SKLMT-China established a useful software tool based on our own wet lab results to help people easily search and predict a proper promoter for fine-tuning gene expression in the synthetic study. To make the
Our Depro system is a platform for promoter researchers to exchange data and share results. Everyone can benefit from the test results of previous researchers or enrich our software with new test data to improve the accuracy of the fit. Through our software, you can:
(1) Predict a new promoter’s strength. Our program is based on all known data for the deep learning of supervised training. you are merely asked to input the core sequence of the promoter, we will immediately calculate the strength level of the promoter
(2) Use a new set of data to enrich the program's deep learning process. Your data will be imported into our database and will accompany our program to complete every deep learning in the future
(3) Freely set the number of times to learn. You are free to decide how quickly and precisely your program will run to meet your needs