High-order extensions of the Double Chain Markov Model

The Double Chain Markov Model is a fully Markovian model for the representation of time-series in random environments. In this article, we show that it can handle transitions of high-order between both a set of observations and a set of hidden states. In order to reduce the number of parameters, each transition matrix can be replaced by a Mixture Transition Distribution model. We provide a complete derivation of the algorithms needed to compute the model. Three applications, the analysis of a sequence of DNA, the song of the wood pewee, and the behavior of young monkeys show that this model is of great interest for the representation of data that can be decomposed into a finite set of patterns.     

Fitting Markov chain models to discrete state series such as DNA sequences

Discrete state series such as DNA sequences can often be modelled by Markov chains. The analysis of such series is discussed in the context of log-linear models. The data produce contingency tables with similar margins due to the dependence of the observations. However, despite the unusual structure of the tables, the analysis is equivalent to that for data from multinomial sampling. The reason why the standard number of degrees of freedom is correct is explained by using theoretical arguments and the asymptotic distribution of the deviance is verified empirically. Problems involved with fitting high order Markov chain models, such as reduced power and computational expense, are also discussed.     

Detecting a changed segment in DNA sequences

Non-coding deoxyribonucleic acid (DNA) can typically be modelled by a sequence of Bernoulli random variables by coding one base, e.g. T, as 1 and other bases as 0. If a segment of a sequence is functionally important, the probability of a 1 will be different in this changed segment from that in the surrounding DNA. It is important to be able to see whether such a segment occurs in a particular DNA sequence and to pin-point it so that a molecular biologist can investigate its possible function. Here we discuss methods for testing the occurrence of such a changed segment and how to estimate the end points of it. Maximum-likelihood-based methods are not very tractable and so a nonparametric method based on the approach of Pettitt has been developed. The problem and its solution are illustrated by a specific DNA example.     

Extended pairwise local alignment of wild card DNA/RNA sequences using dynamic programming

Optimal string alignment is used to discover evolutionary relationships or mutations in DNA/RNA or protein sequences. Errors, missing parts or uncertainty in such a sequence can be covered with wild cards, so-called wild bases. This makes an alignment possible even when the data are corrupted or incomplete. The extended pairwise local alignment of wild card DNA/RNA sequences requires additional calculations in the dynamic programming algorithm and necessitates a subsequent best- and worst-case analysis for the wild card positions. In this paper, we propose an algorithm which solves the problem of input data wild cards, offers a highly flexible set of parameters and displays a detailed alignment output and a compact representation of the mutated positions of the alignment. An implementation of the algorithm can be obtained at https://github.com/sysbio-bioinf/swat+ and http://sysbio.uni-ulm.de/?Software:Swat+.     

企业DNA中的文化力

与生物体类似,企业也拥有其基因,了解这种基因有利于明确企业固有的特性,进而可以了解影响企业绩效的因素和原理.将企业基因与DNA模型相类比,研究对企业影响较大的四个因素(决策权、组织架构、激励机制和信息传导),可以构建出企业基因的模型,文化力作用于各因素之间,并对企业发展起着重要作用.     

多板纲动物的不同保存方法对基因组DNA提取的影响

为了探讨最佳的适合提取DNA的石鳖样本保方法,以日本花棘石鳖Liolophura japonica、日本宽板石鳖Placiphorella japonica、红条毛肤石鳖Acanthochiton ruhrolineatus、平濑锦石鳖Onithochiton hirasei、网纹鬃毛石鳖Mopalia retifera为实验材料,对其分别以甲醛浸泡、95%乙醇浸泡、-75℃超低温保存的样本进行基因组DNA提取.通过紫外分光光度计、琼脂糖凝胶电泳对DNA产物进行检测.结果表明：新鲜材料和用乙醇保存的样品比用-75℃超低温保存的样品提取出的DNA纯度和浓度都高,用甲醛浸泡的方法保存没有提取出DNA.结果表明,超低温保存适合用于DNA提取.但是由于条件限制,长距离外采集样本时适合于用乙醇保存,并且成本较低.     

基于粘贴和删除系统求解最小权生成树的DNA算法

最小权生成树是一类典型的NP完全问题.粘贴和删除模型是DNA计算的两个基本计算模型.利用粘贴和删除模型给出求解最小权生成树问题的DNA算法.     

透视科学技术引发的信任危机——以测谎仪、DNA亲子鉴定为视角

科学技术是一把双刃剑,它给人类社会带来了前所未有的物质文明和精神文明。与此同时,它的负面效应也日益凸显。其中,科技进步所引发的信任危机越来越受到人们的高度关注。以测谎仪、DNA亲子鉴定为切入点,梳理和把握科学技术引起的信任危机的典型表现、产生根源,并尝试提出相应的对策,力求为人们深化对科学技术的认识、培养理性的科学技术观提供有价值的理论参考。     

DNA甲基化检测方法的研究进展

DNA甲基化是一种重要的遗传外修饰,是表观遗传学(epigenetics)的重要组成部分[l]。它参与了动物胚胎发育、基因印迹和X染色体失活等过程,在基因表达的调控中具有重要作用,异常甲基化可以导致肿瘤的形成。近20年来,DNA甲基化的研究逐渐成为新的研究热点。随着对甲基化研究的不断深人,各种各样甲基化检测方法被开发出来以满足不同类型研究的要求。本文对目前现有常用的CpG岛甲基化检测方法作一综述,并着重介绍几项以芯片技术为基础的高通量研究DNA甲基化的方法。     

Tagged Probe Interval Graphs

A generalization of interval graph is introduced for cosmid contig mapping of DNA. A graph is a tagged probe interval graph if its vertex set can be partitioned into two subsets of probes and nonprobes, and a closed interval can be assigned to each vertex such that two vertices are adjacent if and only if at least one of them is a probe and one end of its corresponding interval is contained in the interval corresponding to the other vertex. We show that tagged probe interval graphs are weakly triangulated graphs, hence are perfect graphs. For a tagged probe interval graph with a given partition, we give a chordal completion that is consistent to any interval completions with respect to the same vertex partition.