改进的K—mean聚类算法在基因系统发育谱分析中的应用

简要介绍了系统发育谱法的原理,着重阐述了K—mean聚类算法在对基因系统发育谱分析中的改进,并与传统的K—mean聚类算法进行比较。实验结果表明,改进的K—mean聚类算法在运用系统发育谱法进行基因功能注释上是快而有效的,可以快速收敛到近似最优解。     

系统发育谱（Phylogenetic Profile）生成软件

系统发育谱生成软件（Phylogenetie Profile Generator,PPG）采用Microsoft Visual Basic和Perl两种语言编写,将枸建系统发育谱所涉及的全部过程进行集成,用户只需提供原始的蛋白或核酸序列,软件即可生成所需的系统发育谱,并提供文本和XML两种形式的输出结果。软件具有Windows和Limix两个版本,可提供免费下载。软件下载地址：http：/／life．cnu．edu．cn／kexueyjshow．php？id=56     

基于统计建模的系统发育谱方法研究

系统发育谱算法作为一种有效的大规模基因组功能注释方法,已经被成功的应用到原核生物基因组的功能注释中去。通过对系统发育谱方法中的一个关键环节——相似谱的聚类进行分析,提出了一种基于统计建模的方法来对相似的系统发育谱进行聚类。实验表明,该方法在保证较高的覆盖率的同时,还有效的提高了算法的整体速度,且当参与建模的系统发育谱的数目越大时,算法的精确度越高。     

改进的系统发育谱算法在蛋白质功能注释中的应用

系统发育谱方法是目前研究较多的一种基于非同源性的生物大分子功能注释方法。针对现有算法存在的一些缺陷,从两个方面对该方法做了改进：一是构造基于权重的系统发育谱;二是采用改进的聚类算法对发育谱的相似性进行分析。从NCBI上下载100条Escherichia coli K12蛋白质作为实验数据,分别使用改进的算法和经典的层次聚类算法、K均值聚类算法对相似谱进行分析。结果显示,提出的改进算法在对相似谱聚类的精确度上明显优于后两种聚类算法。     

系统发育树的构建方法

构建系统树是为了鉴定菌株的分类学地位,应该使用正确的方法构建。具体要求如下:1.将鉴定菌的16S rRNA序列递交GenBank,用Blast软件搜索相似的16S rRNA,然后一起构树。     

系统发育树的构建方法

构建系统树是为了鉴定菌株的分类学地位,应该使用正确的方法构建。具体要求如下:1.将鉴定菌的16S rRNA序列递交GenBank,用Blast软件搜索相似的16S rRNA,然后一起构树。     

系统发育树的构建方法

构建系统树是为了鉴定菌株的分类学地位,应该使用正确的方法构建。具体要求如下:1.将鉴定菌的16S rRNA序列递交GenBank,用Blast软件搜索相似的16S rRNA,然后一起构树。2.采用能反应分支长度的软件(如NJ法),并用Boostrap值分析分支聚类的稳定性。     

系统发育树的构建方法

<正>构建系统树是为了鉴定菌株的分类学地位,应该使用正确的方法构建。具体要求如下:1.将鉴定菌的16S rRNA序列递交GenBank,用Blast软件搜索相似的16S rRNA,然后一起构树。2.采用能反应分支长度的软件(如NJ法),并用Boostrap值分析分支聚类的稳定性。3.用国际较为通用的一些建树方法,如Neighbour-Joining等,这样结果就更为可靠,更直观。4.请严格按照下列具体要求写作[参见:微生物学报,2004,44(2):143.]     

系统发育树的构建方法

构建系统树是为了鉴定菌株的分类学地位,应该使用正确的方法构建。具体要求如下:1.将鉴定菌的16SrRNA序列递交GenBank,用Blast软件搜索相似的16SrRNA,然后一起构树。2.采用能反应分支长度的软件(如NJ法),并用Boostrap值分析分支聚类的稳定性。     

系统发育树的构建方法

构建系统树是为了鉴定菌株的分类学地位,应该使用正确的方法构建。具体要求如下:1.将鉴定菌的16S rRNA序列递交GenBank,用Blast软件搜索相似的16S rRNA,然后一起构树。2.采用能反应分支长度的软件(如NJ法),并用Boostrap值分析分支聚类的稳定性。3.用国际较为通用的一些建树方法,如Neighbour-Joining等,这样结果就更为可靠,更直观。     

直系同源基因的识别方法与数据库

直系同源(orthology)是指由于物种形成事件而享有共同祖先的基因之间的关系,直系同源基因之间通常具有相似的结构和生物学功能.由于基因组和转录组序列的快速积累,精确的识别直系同源基因有助于功能基因的注释,比较和进化基因组学研究.综述了现有的识别直系同源基因的主要方法,并列举了由此构建的数据库.这些方法可以归纳为三大类,第一类是基于序列相似性的方法,具有识别速度快以及灵敏度高等优点;第二类是基于构建系统发育树的方法,具有准确性高和信息量大等优点;第三类是将上述两种方法结合起来的混合方法,更好地平衡了灵敏性和准确性.最后总结了识别过程所面临的问题.     

A Survey of Methods for Constructing Rooted Phylogenetic Networks

Rooted phylogenetic networks are primarily used to represent conflicting evolutionary information and describe the reticulate evolutionary events in phylogeny. So far a lot of methods have been presented for constructing rooted phylogenetic networks, of which the methods based on the decomposition property of networks and by means of the incompatible graph (such as the CASS, the LNETWORK and the BIMLR) are more efficient than other available methods. The paper will discuss and compare these methods by both the practical and artificial datasets, in the aspect of the running time of the methods and the effective of constructed phylogenetic networks. The results show that the LNETWORK can construct much simper networks than the others.     

应用SuperTRI方法重建百合目的系统发育关系

SuperTRI是Ropiquet等(2009)发表的一种新的超树方法,可以通过合并所有系统发育信息来共同组建大的系统发育树.该方法克服了超矩阵法和传统超树法的一些限制,使提出的系统发育假说可信度更高,更具有统计说服力.本文应用SupperTRI方法重建了百合目(Liliales)主要类群的系统发育关系,并与超矩阵法的分析结果进行了比较.结果显示:(1) SuperTRI方法产生了与超矩阵法相似的拓扑结构,但节点支持率相对较低,其中再现性指数对评判分支的可信性更容易理解,在系统树图示方法上也更直观;(2)SuperTRI系统树证实百合科、菝葜科、垂花科和菝葜藤科为一单系分支;黑药花科为一独立分支;秋水仙科、六出花科、刺藤科为一单系分支,但这3个大分支间的关系未明;支持白玉簪科和金梅草科互为姐妹群,是百合目最基部类群.     

Phylogenetic and Functional Assessment of Orthologs Inference Projects and Methods

Accurate genome-wide identification of orthologs is a central problem in comparative genomics, a fact reflected by the numerous orthology identification projects developed in recent years. However, only a few reports have compared their accuracy, and indeed, several recent efforts have not yet been systematically evaluated. Furthermore, orthology is typically only assessed in terms of function conservation, despite the phylogeny-based original definition of Fitch. We collected and mapped the results of nine leading orthology projects and methods (COG, KOG, Inparanoid, OrthoMCL, Ensembl Compara, Homologene, RoundUp, EggNOG, and OMA) and two standard methods (bidirectional best-hit and reciprocal smallest distance). We systematically compared their predictions with respect to both phylogeny and function, using six different tests. This required the mapping of millions of sequences, the handling of hundreds of millions of predicted pairs of orthologs, and the computation of tens of thousands of trees. In phylogenetic analysis or in functional analysis where high specificity is required, we find that OMA and Homologene perform best. At lower functional specificity but higher coverage level, OrthoMCL outperforms Ensembl Compara, and to a lesser extent Inparanoid. Lastly, the large coverage of the recent EggNOG can be of interest to build broad functional grouping, but the method is not specific enough for phylogenetic or detailed function analyses. In terms of general methodology, we observe that the more sophisticated tree reconstruction/reconciliation approach of Ensembl Compara was at times outperformed by pairwise comparison approaches, even in phylogenetic tests. Furthermore, we show that standard bidirectional best-hit often outperforms projects with more complex algorithms. First, the present study provides guidance for the broad community of orthology data users as to which database best suits their needs. Second, it introduces new methodology to verify orthology. And third, it sets performance standards for current and future approaches.     

Cloning of a FLOWERING LOCUS T Ortholog in Wasabia japonica (Matsum)

A FLOWERING LOCUS T ortholog (WjFT) was identified in Wasabia japonica. Heterologous expression of WjFT remarkably promoted the flowering of Arabidopsis. The expression of WjFT was examined in field-grown wasabi in October and November of 2009, and February of 2010 because the differentiation of flower buds occurs in autumn in field-grown wasabi. No expression of WjFT was detected in October, it was slightly increased in November, and highly increased in February. WjFT might be useful for examining the flowering response of wasabi.     

New Weighting Methods for Phylogenetic Tree Reconstruction Using Multiple Loci

Efficient determination of evolutionary distances is important for the correct reconstruction of phylogenetic trees. The performance of the pooled distance required for reconstructing a phylogenetic tree can be improved by applying large weights to appropriate distances for reconstructing phylogenetic trees and small weights to inappropriate distances. We developed two weighting methods, the modified Tajima–Takezaki method and the modified least-squares method, for reconstructing phylogenetic trees from multiple loci. By computer simulations, we found that both of the new methods were more efficient in reconstructing correct topologies than the no-weight method. Hence, we reconstructed hominoid phylogenetic trees from mitochondrial DNA using our new methods, and found that the levels of bootstrap support were significantly increased by the modified Tajima–Takezaki and by the modified least-squares method.