项目名称: 细菌基因组调控基元和必需基因的识别与分析
项目编号: No.31271351
项目类型: 面上项目
立项/批准年度: 2013
项目学科: 生物科学
项目作者: 宋凯
作者单位: 天津大学
项目金额: 80万元
中文摘要: 随着基因组测序和基因合成技术的迅速提高,对基因组序列分析提出了更高的要求。而合成生物学的飞速发展和应用,更是对基因调控部件(启动子、终止子、转录因子结合位点等)的序列识别、调控机理研究以及必需基因的研究提出了新的迫切要求。本项目充分利用Z曲线等生物信息学方法,利用先进的机器识别技术开发新的算法,提高细菌基因组调控区域DNA序列和必需基因识别算法的精度。在保证识别精度的基础上,运用各种先进算法降低程序在运行时间和空间方面的要求。研究调控区域DNA序列、密码子序列等与基因必需性之间的关系,同时充分利用合成生物学工程化的思想和模块化、层次化的设计思路,从基因调控网络的全局角度分析调控部件调控能力的变化对调控网络鲁棒性、稳定性等重要性能的影响规律,为合成生物学的工程化和广泛应用开辟新方法,寻找新思路。
中文关键词: 必需基因;特征基因;模式识别;机器学习;
英文摘要: With the ever-increasing pace of synthetic biology, there is a more and more urgent demand for fast and accurate computational tools to identify regulatory motifs and essential genes automatically. Essential genes are genes that are indispensable to support cellular life. These genes constitute a minimal gene set required for a living cell. The regulatory motifs (such as: promoters, terminators, etc) largely account for the expression level of the corresponding genes, and further largely account for the response of gene circuits or gene networks. The main topics are developing new efficient methods to predict regulatory motifs and essential genes. Moreover, prerequisite of prediction precision, the research is aiming at reduce the memory and time requirements of the methods. So advanced algorithms would be used and proposed. Furthermore, regulatory dynamics of gene circuits, including stability, robustness, and so on, would be researched using Chaos and other nonlinear dynamic theories and methods. And then making good use of modularization and hierarchical concepts of synthetic biology, regulatory dynamics of comparatively more complex gene networks would be researched. Our work are hopefully finding out new ideas and new methods to improve the development of synthetic biology.
英文关键词: Essential genes;Signature genes;Pattern recognition;Machine learning;