时间延迟基因调控网络重构的决策树方法研究

基因调控网络的重构是功能基因组中最具挑战性的课题之一. 针对基因间转录调控的时间延迟性, 提出了一种寻找时间延迟调控关系的方法: 多点延迟调控网络算法, 简称TdGRN (time-delayed gene regulatory networking). 该方法根据时间序列基因表达谱数据, 构建时间延迟基因表达矩阵, 利用有监督决策树分类器方法和随机重排技术挖掘基因之间的时间延迟调控关系, 从而构建时间延迟的基因调控网络. 该方法是一种不依赖模型的基因网络重建方法, 相对于目前采用的基于模型的网络重建方法有显著优势, 可直接利用连续的基因表达谱数据发现延迟任一时间单位差的基因表达调控关系, 并避免了目前一些研究方法中需要人为设定基因的最大调控子数目(k)的问题. 将该方法应用于酿酒酵母细胞周期的基因表达谱数据, 并构建时间延迟的基因调控网络, 结果发现多数时间延迟调控关系获得了已有知识的支持.     

植物抗寒基因表达调控研究进展

低温胁迫是植物生长过程中的主要非生物胁迫因子之一,也是影响农作物生产的主要因素之一。研究表明,在植物体内存在着一个复杂的对低温胁迫信号感知及传导的网络系统,该系统中大量的相关基因已有报道,这些基因不仅仅涉及植物激素的应答,还涉及到植物基因的转录调控及转录后的修饰与调控等各个方面。该文就近年来国内外有关植物抗寒基因表达调控的研究进展进行综述。     

内皮素基因表达及调控研究

内皮素（ＥＴ）是近年发现的一种血管活性多肽,其基因表达受许多因素调节。调控位点存在于基因启动子,结构基因和ＥＴ ｍＲＮＡ ３‘端非翻译区等处,启动子Ａ区和Ｂ区可能发挥主要作用。影响基因表达的因素,如缺氧,血管紧张素Ⅱ,凝血酶和心钠素等分别作用于各自受体,通过细胞内信使系统,作用于相应的调控位点,发挥正性或负性调节作用。     

目的基因表达调控研究进展

载体技术的发展使基因治疗中的安全性问题及外源基因的转移效率等技术难题已部分解决,越来越多的研究显示目的基因体内表达的可控性是决定基因治疗成功的关键,组织特异性启动子,诱导性调控元件,增强子,静息子及反式作用因子作用机制的阐明为改造,增强基因治疗载体表达特性,实现人类基因治疗目的基因表达的可控性,靶向性目标,为基因治疗真正进入临床奠定了基础。     

干扰素基因表达调控研究进展

干扰素基因表达调控研究进展孙劲综述方企圣审（中国预防医学科学院病毒研究所,北京１０００５２）近年来,有关于扰素（ＩＦＮ）分子生物学的研究以及基因工程方法生产干扰素取得很大进展。本文将有关ＩＦＮ蛋白的诱导和基因调控机理方面最新进展作一综述。ＩＦＮ蛋白的...     

甲胎蛋白的基因表达与调控

甲胎蛋白基因的调控主要是转录水平的。其中顺式作用片段和逆式作用因子对其表达的正匀调起着关键作用,这种正负调节既互相制约,又彼此协调从而使甲胎蛋白能够正常表达。另外,甲基化调节机理对甲胎蛋白基因也有作用。激素主要是糖蛋质激素也参与了它的调节。但甲胎蛋白基因在组织和发育过程中特异性表达机理尚待进一步深入研究。     

细菌芽孢基因表达的调控

细菌芽孢基因表达的调控范玉贞（河北省衡水师范专科学校生物系,０５３０００）在一定条件下,某些细菌生长到一定阶段,在细胞内形成一个圆形、椭圆形或圆柱形的休眠体,称为芽孢（或内生孢子）。能否形成芽孢是细菌种的遗传特征,而且现已查明具有芽孢的细菌（芽孢细菌...     

细菌芽孢基因表达的调控

细菌芽孢基因表达的调控范玉贞（河北省衡水师范专科学校生物系０５３０００）能否形成芽泡是细菌种的遗传特征，现已查明具有芽泡的细菌（芽抱细菌）在其染色体上都有控制芽抱形成的基因，即芽抱基因。细菌能够根据外界环境条件的变化主动控制芽抱基因的表达，以提高本身...     

A novel model-free approach for reconstruction of time-delayed gene regulatory networks

Many important biological processes (e.g. cellular differentiation during development, aging, disease etiology etc.) are very unlikely controlled by a single gene instead by the underlying complex regulatory interactions between thousands of genes within …     

大花杓兰亲环素基因(CmCyP)的克隆及生物信息学分析

亲环素是一个多基因家族,在植物生命活动中发挥着重要的作用。该研究以大花杓兰(Cypripedium macranthum)为材料,采用RT-PCR技术克隆到1个亲环素基因(CyP),并对其进行生物信息学分析。结果表明:大花杓兰CyP基因的开放阅读框序列为525 bp,命名为CmCyP(GenBank登录号为MH411125),编码174个氨基酸。预测CmCyP蛋白是一个位于细胞质、相对分子量约为18 kD、理论pI为8.73、无信号肽、跨膜结构域的亲水性蛋白质。磷酸化和糖基化位点预测分析发现,CmCyP蛋白存在18个潜在的磷酸化位点和2个潜在的糖基化位点。蛋白保守结构域预测分析发现,CmCyP蛋白包含一个高度保守的肽脯氨酰顺反异构酶结构域,属于单结构域亲环素。对二级结构进行预测分析发现,CmCyP蛋白中存在无规卷曲70个、延伸链56个、α-螺旋23个、β-折叠25个,这4种结构元件在三级结构中也有体现。系统进化树结果显示,大花杓兰CmCyP蛋白与铁皮石斛(Dendrobium catenatum)和万带兰(Vanda hybrid cultivar)的CyP蛋白的亲缘关系较近。该研究首次克隆了大花杓兰亲环素基因(CmCyP),为进一步探讨CmCyP基因的生物学功能奠定了基础。     

An ensemble method for gene discovery based on DNA microarray data

The advent of DNA microarray technology has offered the promise of casting new insights onto deciphering secrets of life by monitoring activities of thousands of genes simultaneously. Current analyses of microarray data focus on precise classification of biological types, for example, tumor versus normal tissues. A further scientific challenging task is to extract disease-relevant genes from the bewildering amounts of raw data, which is one of the most critical themes in the post-genomic era, but it is generally ignored due to lack of an efficient approach. In this paper, we present a novel ensemble method for gene extraction that can be tailored to fulfill multiple biological tasks including (i) precise classification of biological types; (ii) disease gene mining; and (iii) target-driven gene networking. We also give a numerical application for(i) and (ii) using a public microarrary data set and set aside a separate paper to address (iii).     

An ensemble method for gene discovery based on DNA microarray data

DNA microarrays are now able to measure the expressions of thousands of genes simultaneously. These measurements or gene profiling provides a snapshot?of life that maps to a cross section of ge-netic activities in a four-dimension space of time and the biological entity. Although recent microarray ex-periments[1, 2] hold the promise of the innovative tech-nology to cast new insights onto discovery of secrets of life, development of powerful and efficient analysis strategies for microarray dat…     

A toolbox for the immunomagnetic purification of signaling organelles

Homeostasis and the complex functions of organisms and cells rely on the sophisticated spatial and temporal regulation of signaling in different intra‐ and extracellular compartments and via different mediators. We here present a set of fast and easy to use protocols for the target‐specific immunomagnetic enrichment of receptor containing endosomes (receptosomes), plasma membranes, lysosomes and exosomes. Isolation of subcellular organelles and exosomes is prerequisite for and will advance their detailed subsequent biochemical and functional analysis. Sequential application of the different subprotocols allows isolation of morphological and functional intact organelles from one pool of cells. The enrichment is based on a selective labelling using receptor ligands or antibodies together with superparamagnetic microbeads followed by separation in a patented matrix‐free high‐gradient magnetic purification device. This unique magnetic chamber is based on a focusing system outside of the empty separation column, generating an up to 3 T high‐gradient magnetic field focused at the wall of the column.      

基因鉴定集成法:全基因组基因表达研究的新策略

人类基因组包含的核苷酸数目庞大,基因鉴定（识别）的技术策略是基因克隆研究至为重要的基础。在全基因组基因表达分析策略方面,已相继建立了ｍＲＮＡ差异显示、代表性差异分析、抑制性消减杂交、基因表达系列分析和ｃＤＮＡ微阵列等技术。基因鉴定集成法是新近在综合上述技术的优缺点的基础上建立的全基因组分析新策略,具有充分利用生物基因信息数据库进行基因鉴定（识别）,并能提高稀有拷贝基因鉴定效率的优点。本文简要介绍其     

A toolbox for systematic discovery of stable and transient protein interactors in baker's yeast

Identification of both stable and transient interactions is essential for understanding protein function and regulation. While assessing stable interactions is more straightforward, capturing transient ones is challenging. In recent years, sophisticated tools have emerged to improve transient interactor discovery, with many harnessing the power of evolved biotin ligases for proximity labelling. However, biotinylation‐based methods have lagged behind in the model eukaryote, Saccharomyces cerevisiae, possibly due to the presence of several abundant, endogenously biotinylated proteins. In this study, we optimised robust biotin‐ligation methodologies in yeast and increased their sensitivity by creating a bespoke technique for downregulating endogenous biotinylation, which we term ABOLISH (Auxin‐induced BiOtin LIgase diminiSHing). We used the endoplasmic reticulum insertase complex (EMC) to demonstrate our approaches and uncover new substrates. To make these tools available for systematic probing of both stable and transient interactions, we generated five full‐genome collections of strains in which every yeast protein is tagged with each of the tested biotinylation machineries, some on the background of the ABOLISH system. This comprehensive toolkit enables functional interactomics of the entire yeast proteome.     

基于线性判别分析的基因表达数据分类方法研究

由于基因表达数据高属性维、低样本维的特点,Fisher分类器对该种数据分类性能不是很高。本文提出了Fisher的改进算法Fisher-List。该算法独特之处在于为每个类别确定一个决策阀值,每个阀值既包含总体样本信息,又含有某些对分类至关重要的个体样本信息。本文用实验证明新算法在基因表达数据分类方面比Fisher、LogitBoost、AdaBoost、k-近邻法、决策树和支持向量机具有更高的性能。