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Team:HFUT CHINA/Future Work.html
From 2014.igem.org
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<h2 align="center" class="STYLE9">Future works</h2> | <h2 align="center" class="STYLE9">Future works</h2> | ||
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<div align="center" class="STYLE2"><img src="https://static.igem.org/mediawiki/2014/e/ee/Hfut-B7caedead8d0bebbaf4d2384e0bfe387.jpg" width="785" height="115"> </div> </div> | <div align="center" class="STYLE2"><img src="https://static.igem.org/mediawiki/2014/e/ee/Hfut-B7caedead8d0bebbaf4d2384e0bfe387.jpg" width="785" height="115"> </div> </div> | ||
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<p align="justify"><span class="STYLE2">Currently, we collect the device information from teams of previous years. We hope to add the device information of this year’s team. This would make the recommendation algorithms more accurate. Besides, we also want to establish a database that contains the system information, for example, the function of systems, devices that a system contains, the relationships between devices in the same system. These information would provide more possibility for our software to recommend. For example, recommending the devices by function, recommending devices for a system.</span><br> | <p align="justify"><span class="STYLE2">Currently, we collect the device information from teams of previous years. We hope to add the device information of this year’s team. This would make the recommendation algorithms more accurate. Besides, we also want to establish a database that contains the system information, for example, the function of systems, devices that a system contains, the relationships between devices in the same system. These information would provide more possibility for our software to recommend. For example, recommending the devices by function, recommending devices for a system.</span><br> | ||
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<p class="STYLE2"><strong class="STYLE11">Recommendation algorithms:</strong><br> | <p class="STYLE2"><strong class="STYLE11">Recommendation algorithms:</strong><br> | ||
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<p align="justify" class="STYLE2">In the algorithms, we use hamming distance to measure the similarity of two biobricks. Edit distance would be a more powerful measurement for similarity. Thus, we would improve the algorithm by using edit distance. <br> | <p align="justify" class="STYLE2">In the algorithms, we use hamming distance to measure the similarity of two biobricks. Edit distance would be a more powerful measurement for similarity. Thus, we would improve the algorithm by using edit distance. <br> | ||
</p> | </p> | ||
<p align="justify" class="STYLE2">Besides, our software currently recommends biobricks for designing devices. We will use the synthetic systems’ informations to recommend devices. For a given systems, we also want to detect whether there is something wrong with this system by analyzing current systems’ information.<br> | <p align="justify" class="STYLE2">Besides, our software currently recommends biobricks for designing devices. We will use the synthetic systems’ informations to recommend devices. For a given systems, we also want to detect whether there is something wrong with this system by analyzing current systems’ information.<br> | ||
</p> | </p> | ||
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<p align="justify" class="STYLE8">Visualization GUI | <p align="justify" class="STYLE8">Visualization GUI | ||
</p> | </p> | ||
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<p align="justify" class="STYLE2">In the future, we will allow the software to accept various types of input, such as figures or text. Thus, when users need to input a whole system, they could use the figures or texts that have been generated. </p> | <p align="justify" class="STYLE2">In the future, we will allow the software to accept various types of input, such as figures or text. Thus, when users need to input a whole system, they could use the figures or texts that have been generated. </p> | ||
Revision as of 09:25, 16 October 2014
Future works
Database:
Currently, we collect the device information from teams of previous years. We hope to add the device information of this year’s team. This would make the recommendation algorithms more accurate. Besides, we also want to establish a database that contains the system information, for example, the function of systems, devices that a system contains, the relationships between devices in the same system. These information would provide more possibility for our software to recommend. For example, recommending the devices by function, recommending devices for a system.
Recommendation algorithms:
In the algorithms, we use hamming distance to measure the similarity of two biobricks. Edit distance would be a more powerful measurement for similarity. Thus, we would improve the algorithm by using edit distance.
Besides, our software currently recommends biobricks for designing devices. We will use the synthetic systems’ informations to recommend devices. For a given systems, we also want to detect whether there is something wrong with this system by analyzing current systems’ information.
Visualization GUI
In the future, we will allow the software to accept various types of input, such as figures or text. Thus, when users need to input a whole system, they could use the figures or texts that have been generated.
