基于混沌游走方法的Rh血型系统中RHD基因的分析

利用基于经典HP模型的蛋白质序列混沌游走方法（chaos game representation,CGR）,给出了RHD基因的蛋白质序列CGR图,可视作蛋白质序列二级结构的一个特征图谱描述．对临床上的血型鉴别有一定的参考价值．另外．还根据由Jeffrey在1990年提出的描绘DNA序列的CGR方法,给出了RHD基因的DNA序列的CGR图．并且根据RHD基因DNA序列的CGR图算出了尺日D基因相应的马尔可夫两步转移概率矩阵,从概率矩阵表可以看出RHD基因对编码氨基酸的三联子的第3个碱基的使用偏好性．     

Entropic Profiles of DNA Sequences Through Chaos-game-derived Images

A new method to determine entropic profiles in DNA sequences is presented. It is based on the chaos-game representation (CGR) of gene structure, a technique which produces a fractal-like picture of DNA sequences. First, the CGR image was divided into squares 4^-m in size (m being the desired resolution), and the point density counted. Second, appropriate intervals were adjusted, and then a histogram of densities was prepared. Third, Shannon's formula was applied to the probability-distribution histogram, thus obtaining a new entropic estimate for DNA sequences, the histogram entropy , a measurement that goes with the level of constraints on the DNA sequence. Lastly, the entropic profile for the sequence was drawn, by considering the entropies at each resolution level, thus providing a way to summarize the complexity of large genomic regions or even entire genomes at different resolution levels. The application of the method to DNA sequences reveals that entropic profiles obtained in this way, as opposed to previously published ones, clearly discriminate between random and natural DNA sequences. Entropic profiles also show a different degree of variability within and between genomes. The results of these analyses are discussed in relation both to the genome compartmentalization in vertebrates and to the differential action of compositional and/or functional constraints on DNA sequences.     

Mathematical characterization of Chaos Game Representation. New algorithms for nucleotide sequence analysis.

Chaos Game Representation (CGR) can recognize patterns in the nucleotide sequences, obtained from databases, of a class of genes using the techniques of fractal structures and by considering DNA sequences as strings composed of four units, G, A, T and C. Such recognition of patterns relies only on visual identification and no mathematical characterization of CGR is known. The present report describes two algorithms that can predict the presence or absence of a stretch of nucleotides in any gene family. The first algorithm can be used to generate DNA sequences represented by any point in the CGR. The second algorithm can simulate known CGR patterns for different gene families by setting the probabilities of occurrence of different di- or trinucleotides by a trial and error process using some guidelines and approximate rules-of-thumb. The validity of the second algorithm has been tested by simulating sequences that can mimic the CGRs of vertebrate non-oncogenes, proto-oncogenes and oncogenes. These algorithms can provide a mathematical basis of the CGR patterns obtained using nucleotide sequences from databases.     

Nucleotide, dinucleotide and trinucleotide frequencies explain patterns observed in chaos game representations of DNA sequences.

The chaos game representation (CGR) is a scatter plot derived from a DNA sequence, with each point of the plot corresponding to one base of the sequence. If the DNA sequence were a random collection of bases, the CGR would be a uniformly filled square; conversely, any patterns visible in the CGR represent some pattern (information) in the DNA sequence. In this paper, patterns previously observed in a variety of DNA sequences are explained solely in terms of nucleotide, dinucleotide and trinucleotide frequencies.     

Applying MSSIM combined chaos game representation to genome sequences analysis

Converting DNA sequence to image by using chaos game representation (CGR) is an effective genome sequence pretreatment technology, which provides the basis for further analysis between the different genes. In this paper, we have constructed 10 mammal species, 48 hepatitis E virus (HEV), and 10 kinds of bacteria genetic CGR images, respectively, to calculate the mean structural similarity (MSSIM) coefficient between every two CGR images. From our analysis, the MSSIM coefficient of gene CGR images can accurately reflect the similarity degrees between different genomes. Hierarchical clustering analysis was used to calculate the class affiliation and construct a dendrogram. Large numbers of experiments showed that this method gives comparable results to the traditional Clustal X phylogenetic tree construction method, and is significantly faster in the clustering analysis process. Meanwhile MSSIM combined CGR method was also able to efficiently clustering of large genome sequences, which the traditional multiple sequence alignment methods (e.g. Clustal X, Clustal Omega, Clustal W, et al.) cannot classify.     

Chaos game representation of coding regions of human globin genes and alcohol dehydrogenase genes of phylogenetically divergent species

Summary Chaos game representation (CGR) is a novel holistic approach that provides a visual image of a DNA sequence quite different from the traditional linear arrangement of nucleotides. Although it is known that CGR patterns depict base composition and sequentiality, the biological significance of the specific features of each pattern is not understood. To systematically examine these features, we have examined the coding sequences of 7 human globin genes and 29 relatively conserved alcohol dehydrogenase (Adh) genes from phylogenetically divergent species. The CGRs of human globin cDNAs were similar to one another and to the entire human globin gene complex. Interestingly, human globin CGRs were also strikingly similar to human Adh CGRs. Adh CGRs were similar for genes of the same or closely related species but were different for relatively conserved Adh genes from distantly related species. Dinucleotide frequencies may account for the self-similar pattern that is characteristic of vertebrate CGRs and the genome-specific features of CGR patterns. Mutational frequencies of dinucleotides may vary among genome types. The special features of CG dinucleotides of vertebrates represent such an example. The CGR patterns examined thus far suggest that the evolution of a gene and its coding sequence should not be examined in isolation. Consideration should be given to genome-specific differential mutation rates for different dinucleotides or specific oligonucleotides. Offprint requests to: S. M. Singh     

Structural analysis of DNA sequence: evidence for lateral gene transfer in Thermotoga maritima

The recently published complete DNA sequence of the bacterium Thermotoga maritima provides evidence, based on protein sequence conservation, for lateral gene transfer between Archaea and Bacteria. We introduce a new method of periodicity analysis of DNA sequences, based on structural parameters, which brings independent evidence for the lateral gene transfer in the genome of T.maritima. The structural analysis relates the Archaea-like DNA sequences to the genome of Pyrococcus horikoshii. Analysis of 24 complete genomic DNA sequences shows different periodicity patterns for organisms of different origin. The typical genomic periodicity for Bacteria is 11 bp whilst it is 10 bp for Archaea. Eukaryotes have more complex spectra but the dominant period in the yeast Saccharomyces cerevisiae is 10.2 bp. These periodicities are most likely reflective of differences in chromatin structure.     

Predicting thermophilic proteins with pseudo amino acid composition:approached from chaos game representation and principal component analysis

Comprehensive knowledge of thermophilic mechanisms about some organisms whose optimum growth temperature (OGT) ranges from 50 to 80 °C degree plays a major role for helping to design stable proteins. How to predict function-unknown proteins to be thermophilic is a long but not fairly resolved problem. Chaos game representation (CGR) can investigate hidden patterns in protein sequences, and also can visually reveal their previously unknown structures. In this paper, using the general form of pseudo amino acid composition to represent protein samples, we proposed a novel method for presenting protein sequence to a CGR picture using CGR algorithm. A 24-dimensional vector extracted from these CGR segments and the first two PCA features are used to classify thermophilic and mesophilic proteins by Support Vector Machine (SVM). Our method is evaluated by the jackknife test. For the 24-dimensional vector, the accuracy is 0.8792 and Matthews Correlation Coefficient (MCC) is 0.7587. The 26-dimensional vector by hybridizing with PCA components performs highly satisfaction, in which the accuracy achieves 0.9944 and MCC achieves 0.9888. The results show the effectiveness of the new hybrid method.     

乙型、丙型流感病毒的长记忆ARFIMA模型

用时间序列模型来分析乙型、丙型这两种流感病毒,对乙流、丙流病毒DNA序列提供了一种新的时间序列模型,即CGR弧度序列。利用CGR坐标将乙流、丙流病毒DNA序列转换成CGR弧度序列,且引入长记忆ARFIMA模型去拟合这两类序列。发现随机找来的10条乙流序列,10条丙流序列都具有长相关性且拟合很好,并且还发现这两种病毒序列可以尝试用不同的ARFIMA模型ARFIMA(0,d,4)模型,ARFIMA(1,d,1)模型去识别。     

Chaos game representation of protein sequences based on the detailed HP model and their multifractal and correlation analyses

Similar to the chaos game representation (CGR) of DNA sequences proposed by Jeffrey (Nucleic Acid Res. 18 (1990) 2163), a new CGR of protein sequences based on the detailed HP model is proposed. Multifractal and correlation analyses of the measures based on the CGR of protein sequences from complete genomes are performed. The Dq spectra of all organisms studied are multifractal-like and sufficiently smooth for the Cq curves to be meaningful. The Cq curves of bacteria resemble a classical phase transition at a critical point. The correlation distance of the difference between the measure based on the CGR of protein sequences and its fractal background is also proposed to construct a more precise phylogenetic tree of bacteria.     

Analysis of genomic sequences by Chaos Game Representation

MOTIVATION: Chaos Game Representation (CGR) is an iterative mapping technique that processes sequences of units, such as nucleotides in a DNA sequence or amino acids in a protein, in order to find the coordinates for their position in a continuous space. This distribution of positions has two properties: it is unique, and the source sequence can be recovered from the coordinates such that distance between positions measures similarity between the corresponding sequences. The possibility of using the latter property to identify succession schemes have been entirely overlooked in previous studies which raises the possibility that CGR may be upgraded from a mere representation technique to a sequence modeling tool. RESULTS: The distribution of positions in the CGR plane were shown to be a generalization of Markov chain probability tables that accommodates non-integer orders. Therefore, Markov models are particular cases of CGR models rather than the reverse, as currently accepted. In addition, the CGR generalization has both practical (computational efficiency) and fundamental (scale independence) advantages. These results are illustrated by using Escherichia coli K-12 as a test data-set, in particular, the genes thrA, thrB and thrC of the threonine operon.     

Local Renyi entropic profiles of DNA sequences

Background  

In a recent report the authors presented a new measure of continuous entropy for DNA sequences, which allows the estimation of their randomness level. The definition therein explored was based on the Rényi entropy of probability density estimation (pdf) using the Parzen's window method and applied to Chaos Game Representation/Universal Sequence Maps (CGR/USM). Subsequent work proposed a fractal pdf kernel as a more exact solution for the iterated map representation. This report extends the concepts of continuous entropy by defining DNA sequence entropic profiles using the new pdf estimations to refine the density estimation of motifs.     

Efficient Boolean implementation of universal sequence maps (bUSM)

Background  

Recently, Almeida and Vinga offered a new approach for the representation of arbitrary discrete sequences, referred to as Universal Sequence Maps (USM), and discussed its applicability to genomic sequence analysis. Their work generalizes and extends Chaos Game Representation (CGR) of DNA for arbitrary discrete sequences.     

基于CGR的DNA序列的时间序列模型(英文)

利用DNA序列的混沌游戏表示(chaos game representation,CGR),提出了将2维DNA图谱转化成相应的类谱格式的方法。该方法不仅提供了一个较好的视觉表示,而且可将DNA序列转化成一个时间序列。利用CGR坐标将DNA序列转化成CGR弧度序列,并引入长记忆ARFIMA(p,d,q)模型去拟合此类序列,发现此类序列中有显著的长相关性且拟合度很好。     

Exploring an alignment free approach for protein classification and structural class prediction

Alignment free methods based on Chaos Game Representation (CGR), also known as sequence signature approaches, have proven of great interest for DNA sequence analysis. Indeed, they have been successfully applied for sequence comparison, phylogeny, detection of horizontal transfers or extraction of representative motifs in regulation sequences. Transposing such methods to proteins poses several fundamental questions related to representation space dimensionality. Several studies have tackled these points, but none has, so far, brought the application of CGRs to proteins to their fully expected potential. Yet, several studies have shown that techniques based on n-peptide frequencies can be relevant for proteins. Here, we investigate the effectiveness of a strategy based on the CGR approach using a fixed reverse encoding of amino acids into nucleic sequences. We first explore its relevance to protein classification into functional families. We then attempt to apply it to the prediction of protein structural classes. Our results suggest that the reverse encoding approach could be relevant in both cases. We show that it is able to classify functional families of proteins by extracting signatures close to the ProSite patterns. Applied to structural classification, the approach reaches scores of correct classification close to 84%, i.e. close to the scores of related methods in the field. Various optimizations of the approach are still possible, which open the door for future applications.     

Similarity Estimation Between DNA Sequences Based on Local Pattern Histograms of Binary Images

Graphical representation of DNA sequences is one of the most popular techniques for alignment-free sequence comparison. Here, we propose a new method for the feature extraction of DNA sequences represented by binary images, by estimating the similarity between DNA sequences using the frequency histograms of local bitmap patterns of images. Our method shows linear time complexity for the length of DNA sequences, which is practical even when long sequences, such as whole genome sequences, are compared. We tested five distance measures for the estimation of sequence similarities, and found that the histogram intersection and Manhattan distance are the most appropriate ones for phylogenetic analyses.     

Bacterial classification with convolutional neural networks based on different data reduction layers

Abstract

For high accuracy classification of DNA sequences through Convolutional Neural Networks (CNNs), it is essential to use an efficient sequence representation that can accelerate similarity comparison between DNA sequences. In addition, CNN networks can be improved by avoiding the dimensionality problem associated with multi-layer CNN features. This paper presents a new approach for classification of bacterial DNA sequences based on a custom layer. A CNN is used with Frequency Chaos Game Representation (FCGR) of DNA. The FCGR is adopted as a sequence representation method with a suitable choice of the frequency k-lengthen words occurrence in DNA sequences. The DNA sequence is mapped using FCGR that produces an image of a gene sequence. This sequence displays both local and global patterns. A pre-trained CNN is built for image classification. First, the image is converted to feature maps through convolutional layers. This is sometimes followed by a down-sampling operation that reduces the spatial size of the feature map and removes redundant spatial information using the pooling layers. The Random Projection (RP) with an activation function, which carries data with a decent variety with some randomness, is suggested instead of the pooling layers. The feature reduction is achieved while keeping the high accuracy for classifying bacteria into taxonomic levels. The simulation results show that the proposed CNN based on RP has a trade-off between accuracy score and processing time.     

The wheat γ-gliadin genes: characterization of ten new sequences and further understanding of γ-gliadin gene family structure

Ten new wheat γ-gliadin gene sequences are reported and an analysis of γ-gliadin gene family structure is carried out using all known γ-gliadin sequences. The new sequences comprise four genomic clones with significantly more flanking DNA than previously reported, and six cDNA clones from a wheat endosperm EST project. Analysis of extended flanking DNA from the genomic clones indicates the limits of conservation of γ-gliadin DNA sequence that are similar to those previously found with other gliadin and glutenin genes and that are theorized to define the DNA sequence necessary for gene control. Most of the flanking DNA is not homologous to any reported DNA sequence, and one flanking region contains the first MITE-like (miniature inverted transposable element) DNA sequence associated with gliadin genes. About a quarter of the encoded polypeptides would contain a free cysteine residue – an observation that may relate to reports that at least some gliadins can participate in wheat endosperm glutenin polymer formation. The new sequences represent both genes closely related to those previously reported and a new sub-class of γ-gliadins.     

Sequence-dependent variability of DNA structure. Influence of flanking sequences and fragment length on digestion by conformationally sensitive nucleases

DNase I and 1,10-phenanthroline-copper are two nucleolytic activities which are sequence-dependent in their scission reaction yet are not nucleotide-specific at their site of cutting. When these two nucleases are used to digest identical sequences in 18-base pair oligonucleotides and in restriction fragments 10-fold longer, the digestion patterns are similar at sequence positions in the interior of the fragment. Changes in reactivity to 1,10-phenanthroline-copper associated with mutational changes in the lac promoter in biochemically functional restriction fragments are duplicated in 18-base pair oligonucleotides. The structural variability of a given DNA sequence detected by these conformationally sensitive nucleolytic activities is therefore encoded in local sequence and not sensitive to fragment length. Digestion patterns of a repeated 7-base pair sequence within a longer sequence have the same characteristic except for the two nucleotides at the 5' periphery of the direct repeat. This conclusion is based on the digestion pattern of a restriction fragment which contains the polyadenylation site of the mouse immunoglobulin mu heavy chain gene. Two pairs of different 7-base pair sequences repeated in this fragment retain their distinctive digestion patterns. DNA sequences which comprise the binding sites of regulatory proteins, retain a characteristic structure only influenced at their peripheries by two to three bases of the flanking sequence.     

基于后缀列的基因序列最大串联重复查找技术

重复序列分析在全基因组研究中起着重要作用,其首要任务就是在DNA序列中识别并定位所有的重复结构。本文提出了一种新的算法,此算法基于一种简单的数据结构——后缀数,用于查找给定的DNA序列中所有的最大串联重复。并且在该算法的基础上编写了一个有效实用的软件——RepLocate,同时给出了它应用到已知的DNA序列的实例。