中国科学院沈阳自动化研究所机构知识库
Advanced  
SIA OpenIR  > 装备制造技术研究室  > 学位论文
题名: 基因芯片PCR热循环控制及微阵列图像分析关键技术研究
其他题名: Research on PCR Thermal Cycling Control and Microarray Images Analysis Key Technologies for Gene Chips
作者: 刘军
导师: 王天然 ; 刘伟军
分类号: Q78
关键词: 基因芯片 ; PCR热循环控制 ; 微阵列图像扫描采集 ; 网格定位 ; 靶点图像分割
索取号: Q78/L73/2010
学位专业: 机械电子工程
学位类别: 博士
答辩日期: 2010-05-29
授予单位: 中国科学院沈阳自动化研究所
学位授予地点: 中国科学院沈阳自动化研究所
作者部门: 装备制造技术研究室
中文摘要: 基因芯片技术是对微观生物遗传物质进行提取、处理、检测和分析的一种新型分子生物学试验方法。基因芯片设计、加工、制备与检测分析是实现基因芯片分析设备微型化、集成化、自动化、智能化的四项关键技术,必将对揭示生命本质和发展规律、提高临床医疗水平、保证药物食品质量和安全做出重大贡献。  基因芯片PCR(Polymerase Chain Reaction,聚合酶链式反应)热循环控制以及微阵列图像分析是基因芯片检测分析设备中的两个关键技术,决定着基因芯片检测分析系统的性能。 根据自动控制、数字信号处理、图像处理与模式识别、生物信息学等基础理论,对基因芯片PCR热循环控制和微阵列图像分析两项关键技术进行深入研究,构建了基因芯片PCR热循环控制、微阵列图像扫描采集、微阵列图像处理和分析以及基因芯片数据抽取分析的理论框架。 根据PCR温度均匀性、精确性、快变性的控制特点和要求,提出一种基于环形管道“风浴”炉的PCR方案。针对PCR温度升降速度慢、恒温精度低和系统不稳定等问题,采取一系列技术措施对PCR温控方案以及加热结构进行改进。采用MATLAB仿真工具对温度控制算法进行仿真实验研究,并对不同控制算法的控制仿真实验性能进行分析和比较。提出一种基于常规PID、风门开关控制、温度误差死区、风门开度调节联合控制策略的PCR热循环控制算法,实现了PCR温度的快速高精度控制,有效改善了温度控制的动态和稳态性能。 针对基因芯片微阵列图像CCD扫描采集系统存在的显微成像人工调焦困难、荧光靶点人工识别、图像分辨率低、扫描拼接速度慢等技术问题,提出一种基于荧光靶点检测识别、显微自动调焦、芯片扫描路径规划、显微图像拼接的基因芯片微阵列图像CCD自动扫描采集系统,实现了基因芯片靶点阵列图像的自动扫描和采集。 在基因芯片图像预处理中,针对图像信噪比低、靶点阵列倾斜等问题,采用人工交互方式和图像旋转变换实现微阵列图像倾斜校正;采用数学形态学算子进行微阵列图像去噪,改善了微阵列图像分割质量,提高了基因芯片网格定位分析的准确性;采用基于热传导方程、中值曲率驱动方程、AMSS方程的图像滤波算子,有效提高了基因芯片微阵列及靶点图像的信噪比。 网格定位是确定和表达各个靶点在整个基因芯片微阵列图像上的二维空间几何位置的一种图像分析技术,然而图像噪声和计算误差常常导致网格定位分析存在误划分问题。分别采用基于投影变换功率谱分析和峰值搜索的一维数字信号分析方法以及基于固定圆形模板匹配的方法,实现基因芯片微阵列图像的网格定位。提出一种基于投影变换差分序列分析和局部极值搜索的网格定位方法,提高了定位分析效率,降低了算法的复杂度。 基因芯片靶点图像分割是在网格定位确定的靶点方格区域内提取出单个靶点目标的图像分析技术。靶点图像分割质量决定了靶点数据抽取的准确性,但由于图像噪声的影响,一些靶点图像分割方法存在着过分割、误分割等问题。采用基于阈值、基于区域、基于边缘、基于C-V模型变分水平集等四种不同的分割方法进行靶点图像分割试验,通过后续靶点数据抽取对不同靶点图像分割方法的分割质量进行分析和比较。针对基因芯片靶点数据抽取问题,对常用的荧光靶点特征参数进行抽取并进行修正处理。在基因芯片数据表达方法方面,进行了数据数值表达方法和图形化表达方法的试验研究。上述工作为进一步的基因芯片数据分析和数据挖掘研究奠定了技术基础。 综合上述理论和关键技术,利用MS VC++开发了一套基于WINDOWS操作系统的核酸扩增杂交基因芯片检测分析系统软件,包括基因芯片PCR热循环温度控制模块、芯片注液清洗控制模块、微阵列图像CCD检测分析模块,通过上述连续的基因芯片制备和分析过程,就能自动获取镶嵌于基因芯片中的物理和生物数据信息。设备运行及试验结果表明该系统及软件在基因芯片分析工程中具有较好的实用价值。
英文摘要: Gene chip technology is a brand new molecular biology experimental method of distilling, processing, detecting, and analyzing microbial genetic materials. Gene chip designing, machining, processing, and detecting & analyzing are the four critical and key technologies for the miniaturization, integration, automation, and intellectualization of gene chip analysis equipments. These four technologies will be seriously favorable for discovering the natures of life and its developing laws, improving clinical services quality, and assuring pharmacy & food quality and safety. Gene chip PCR (Polymerase Chain Reaction) thermal cycling control and microarray images analysis are the two key technologies which strongly ensure the capabilities of gene chip detecting and analyzing system.According to the basic theories of automatic control, digital signal processing, image analysis and pattern recognition, bio-informatics etc., the two key technologies: PCR thermal cycling control and microarray images analysis are researched in depth. The theoretical frame of gene chip PCR thermal cycling control, microarray images scanning, microarray images processing and analysis, microarray spots data extraction and analysis is proposed. According to the control characteristics and quality requirements of PCR temperature uniformity, stable state accuracy, and fast responding ability, a PCR scheme based on a kind of circular piping and hot air bathing oven is proposed. To tackle the problems of low temperature ascending and descending speeds, bad temperature stable state accuracy, and system instability, some improving measures for the PCR control scheme and heating structure are proposed. The PCR thermal cycling control algorithms are researched by simulation with MATLAB and the simulation experimental results of the algorithms are analyzed and compared. A PCR thermal cycling control algorithm based on united control strategies of conventional PID, wind doors on-off switching, temperature error dead zone, and wind doors opening adjustment is proposed to realize fast and high precision PCR thermal cycling temperature control and improve the temperature stable state accuracy and dynamic performances significantly. To tackle the technical problems of manual microscopic focusing, manual fluorescent spots localization and recognition, low microarray image resolution and low microarray images stitching, a CCD microarray images scanning and acquiring system based on automatic microscopic focusing, spots detection and recognition, microarray image scanning path programming, microarray image stitching is proposed to realize automatic microarray images scanning. In microarray images preprocessing, image skew correcting is realized by human machine interaction and skew rotating correction method. Mathematical morphological operators are utilized to remove noises of microarray images, improve the quality of microarray image segmentation, and promote the accuracy of microarray image gridding. The images smoothing methods based on linear heat flow, Mean Curvature Motion ( MCM ), Affine Morphological Scale Space ( AMSS ) PDEs are used to remove image noises and preserve spots edges before images gridding analysis. Gridding is an image analysis technology which detects and expresses the accurate 2D (two dimensions) positions of every spots in the microarray image. However, image noises and computing errors always lead to error gridding problems. A 1D ( one dimension ) signal analysis method based on image projection, power spectra analysis and projection peak values searching and another method based on fixed radius circular spot template image matching are applied to microarray image gridding. However, to promote the efficiency and decrease the complexity of computation, a novel method based on image projection, projection sequence differencing and sequences maxima and minima searching is proposed for microarray image gridding. Microarray spots images segmentation is an image analysis technology separating the single spot object from the background in each microcell rectangle region. The following four different image segmentation methods: threshholding, regioning, edging, and variational level set are utilized to spots images segmentation experiments, moreover, through the subsequent spots data extracting and comparing, the qualities of images segmentation with the different methods are analyzed and compared. For the spots data extracting problem, the main characteristic parameters of spots are extracted and amended. For gene chip data expression methods, the two main expression methods: numerical and graphical expressions are introduced and experimented. The above work supplied the technical foundation for the further research on gene chip data analysis and data mining. With the above theories and key technologies synthesized, A suite of software for nucleic acids amplification and hybridization gene chips detection and analysis is designed with Microsoft Visual C++ software developing tool. This software includes the following modules: PCR thermal cycling control, gene chip reactants injection and syringing control, microarray images CCD scanning and acquiring, microarray image gridding and spots images segmentation, and gene chip spots data extracting. Through the above consecutive procedures for gene chip PCR preparation, detection and analysis, the physical and biological information embedding in the gene chips can be obtained automatically. Many operations and experiments for this equipment showed that this system and its software are of practical values in gene chip analysis engineering.
语种: 中文
产权排序: 1
内容类型: 学位论文
URI标识: http://ir.sia.cn/handle/173321/9296
Appears in Collections:装备制造技术研究室_学位论文

Files in This Item:
File Name/ File Size Content Type Version Access License
基因芯片PCR热循环控制及微阵列图像分析关键技术研究.pdf(3341KB)----限制开放 联系获取全文

Recommended Citation:
刘军.基因芯片PCR热循环控制及微阵列图像分析关键技术研究.[博士学位论文].中国科学院沈阳自动化研究所.2010
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[刘军]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[刘军]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.

 

 

Valid XHTML 1.0!
Copyright © 2007-2016  中国科学院沈阳自动化研究所 - Feedback
Powered by CSpace