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Team:HFUT CHINA/Overview.html
From 2014.igem.org
Overview
Introduction
Synthetic Biology is to create the new species by building parts and biobricks through the Genetic Engineering. iGEM is a worldwide synthetic biology competition. Till now, more than one thousand teams have participated in iGEM, resulting in a large number of synthetic devices designed. However, not many analyses are done on these devices. Are these existing devices could provide useful information for new participators to design new devices? In order to answer this question, we aim to developing a software to help designing devices.
The main function of our software “BioDesigner” is to recommend biobricks for participators when they are designing new devices. By collecting the information of existing devices and making analysis on these devices, Biodesigner will recommend biobricks based on the users’ habits or the biobricks users have been used.
SOFTWARE
BioDesigner contains two parts, server part and client part. The codes for server part are written in java programming language and the codes for client part are written in C++ programming language. The GUI is designed with Qt which is based on C++. As a result, all of them can be compiled across various platforms. The program has been built on Windows, Linux and Mac operating systems.
The server part is used to build the database that contains the information of existing devices, and make analysis on these information. The client part consists of GUI and analysis of users input. Users input there information through GUI, and client codes deal with the input and send requirements to the server. Server receives the requirements from client, and makes analysis based on the database. Then, it returns information to client. Client deals with the information and visualizes it.
OThe database is stored in server, which would simplify the installation. Since the server is more powerful, the algorithms for recommendation are executed on server, which will reduce the analysis time.
METHODOLOGY
In order to accomplish the function of BioDesigner, such as recommending biobricks, we adapt various recommendation algorithms to achieve the goal. These algorithms include Collaborative filtering and Association rules.
1. Collaborative filtering:
a. The collaborative filtering based on the content: Given a biobrick, Biodesigner finds a similar biobrick to recommend according to the sequence of biobrick.
b. The collaborative filtering based on the user: By storing the biobricks users have been used, Biodesigner statistics users’ habit to recommend the higher frequency biobrick.
2. Association rules: Based on existing device chains, implied relationship, including relationship between two successive biobricks, three successive biobricks, four successive biobirkcs and five successive biobricks, are obtained. Biodesigner uses these relationships to recommend the biobrick over the minimum confidence.
DATABASE
In order to support Biodesigner, we build a database that contains the systems designed by the teams of previous years. About 3600 device chains are collected and stored in our database. We also download the biobrick information contained by these chains from Registry of Standard Biological Parts and stored these information in our database.
The database used in BioDesigner is flexible. The users can add or delete data freely. We use the Restlet and Hibernate to build the database framework. When the client sends a request, a respond will be sent from the serve.
