蛋白质序列的六维表示与相似性分析

给出了蛋白质序列的一种六维表示方法,根据这种表示方法有3种不同表示形式,利用这3种形式来构造距离矩阵的信息熵,然后通过信息熵向量的欧式距离、夹角来比较序列之间的相似性。     

The control of copy number of IS6110 in Mycobacterium tuberculosis

Insertion sequence (IS) elements are bacterial genes that are able to transpose to different locations in the genome. These elements are often used in molecular epidemiology as genetic markers that track the spread of pathogens. Transposable elements have frequently been described as "selfish DNA" because they facilitate their own transposition, causing damage when they insert into coding regions, while contributing little if anything to the bacterial host. According to this hypothesis, the expansion of copy number of insertion sequences is opposed by negative selection against high copy numbers. From an alternative point of view, we might expect IS elements to intrinsically regulate transposition within cells, thereby limiting damage to their bacterial host. Here, we report evidence that the copy number of IS6110 in Mycobacterium tuberculosis is controlled by selection against the element. We first construct 12 different models of marker change resulting from a combination of possible transposition functions and selective regimes. We then compute the Akaike Information Criterion for each model to identify the models that best explain data consisting of serial isolates of M. tuberculosis genotyped with IS6110. We find that the best performing models all include selection against the accumulation of copies. Specifically, our analysis points to the interaction of separate copies of the element causing lethal effects. We discuss the implications of these findings for genome evolution and molecular epidemiology.     

Neural Population Structures and Consequences for Neural Coding

Researchers studying neural coding have speculated that populations of neurons would more effectively represent the stimulus if the neurons "cooperated:" by interacting through lateral connections, the neurons would process and represent information better than if they functioned independently. We apply our new theory of information processing to determine the fidelity limits of simple population structures to encode stimulus features. We focus on noncooperative populations, which have no lateral connections. We show that they always exhibit positively correlated responses and that as population size increases, they perfectly represent the information conveyed by their inputs regardless of the individual neuron's coding scheme. Cooperative populations, which do have lateral connections, can, depending on the nature of the connections, perform better or worse than their noncooperative counterparts. We further show that common notions of synergy fail to capture the level of cooperation and to reflect the information processing properties of populations.     

大鼠初级传入纤维与脊髓背角神经元间的动作电序列的突触传递

外周感觉神经元通过动作电位序列对信号进行编码,这些动作电位序列经过突触传递最终到达脑部。但是各种脉冲序列如何通过神经元之间的化学突触进行传递依然是一个悬而未决的问题。研究了初级传入A6纤维与背角神经元之间各种动作电位序列的突触传递过程。用于刺激的规则,周期、随机脉冲序列由短簇脉冲或单个脉冲构成。定义“事件”(event)为峰峰问期(intefspike interval)小于或等于规定阈值的最长动作电位串,然后从脉冲序列中提取事件间间期(interevent interval,IEI)。用时间,IEI图与回归映射的方法分析IEI序列,结果表明在突触后输出脉冲序列中可以检测到突触前脉冲序列的主要时间结构特征,特别是在短簇脉冲作为刺激单位时。通过计算输入与输出脉冲序列的互信息,发现短簇脉冲可以更可靠地跨突触传递由输入序列携带的神经信息。这些结果表明外周输入脉冲序列的主要时间结构特征可以跨突触传递,在突触传递神经信息的过程中短簇脉冲更为有效。这一研究在从突触传递角度探索神经信息编码方面迈出了一步。     

大鼠皮层听-视多感觉神经元和听-视信息整合

应用常规电生理技术,研究SD大鼠皮层听-视多感觉神经元的分布和听-视信息整合.共记录到130个听-视双模态神经元,其中65个A-V型神经元,28个v-A型神经元和37个a-V型神经元.这些双模态神经元主要分布于听区的背侧,听皮层和视皮层的交界处,具有明显的区域性,呈条带状分布,v-A型神经元较多地位于近听皮层一侧,a-V型神经元则主要位于近视皮层一侧,A-V型神经元位于两者之间.在条带中,双模态神经元分布不均一,有片状分布趋势.双模态神经元的听-视信息整合效应分为增强型、抑制型和调制型.整合效应与声-光组合刺激的时间间隔有关,其中75%的神经元获得最大整合效应的时间间隔在30～50ms之间.研究结果提示,大鼠皮层存在听-视多感觉神经元分布区,这些神经元遵循存在于其他动物相关脑区多感觉信息整合规律,参与听-视感觉信息整合.     

种群分布格局测定的样方尺度效应

以粤西黑石顶自然保护区西部船底窝的永久样地为研究对象,在一个面积为1600m2的人工次生裸地样地上,借助地理信息系统(GIS)技术,对各个种群分别用3种不同的样方面积(10m×10m,8m×8m,5m×5m)和不同的测定方法来研究演替初期优势种群的分布格局,从而研究不同的样方面积对测定南亚热带森林群落内种群分布格局的影响。结果表明,在南亚热带森林群落演替初期以8m×8m的样方面积来测定种群分布格局较为有效。同时运用GIS技术作数据处理及图形输出,大大简化了分析过程,提高了分析水平。     

Relationships between land use, spatial scale and stream macroinvertebrate communities

1. The structure of lotic macroinvertebrate communities may be strongly influenced by land‐use practices within catchments. However, the relative magnitude of influence on the benthos may depend upon the spatial arrangement of different land uses in the catchment. 2. We examined the influence of land‐cover patterns on in‐stream physico‐chemical features and macroinvertebrate assemblages in nine southern Appalachian headwater basins characterized by a mixture of land‐use practices. Using a geographical information system (GIS)/remote sensing approach, we quantified land‐cover at five spatial scales; the entire catchment, the riparian corridor, and three riparian ‘sub‐corridors’ extending 200, 1000 and 2000 m upstream of sampling reaches. 3. Stream water chemistry was generally related to features at the catchment scale. Conversely, stream temperature and substratum characteristics were strongly influenced by land‐cover patterns at the riparian corridor and sub‐corridor scales. 4. Macroinvertebrate assemblage structure was quantified using the slope of rank‐abundance plots, and further described using diversity and evenness indices. Taxon richness ranged from 24 to 54 among sites, and the analysis of rank‐abundance curves defined three distinct groups with high, medium and low diversity. In general, other macroinvertebrate indices were in accord with rank‐abundance groups, with richness and evenness decreasing among sites with maximum stream temperature. 5. Macroinvertebrate indices were most closely related to land‐cover patterns evaluated at the 200 m sub‐corridor scale, suggesting that local, streamside development effectively alters assemblage structure. 6. Results suggest that differences in macroinvertebrate assemblage structure can be explained by land‐cover patterns when appropriate spatial scales are employed. In addition, the influence of riparian forest patches on in‐stream habitat features (e.g. the thermal regime) may be critical to the distribution of many taxa in headwater streams draining catchments with mixed land‐use practices.     

A bioinformatics-based update on microRNAs and their targets in rainbow trout (Oncorhynchus mykiss)

MicroRNAs (miRNAs) participate in various vitally biological processes via controlling target genes activity and thousands of miRNAs have been identified in many species to date, including 18,698 known animal miRNA in miRBase. However, there are only limited studies reported in rainbow trout (Oncorhynchus mykiss) especially via the computational-based approaches. In present study, we systematically investigated the miRNAs in rainbow trout using a well-developed comparative genome-based homologue search. A total of 196 potential miRNAs, belonging to 124 miRNA families, were identified, most of which were firstly reported in rainbow trout. The length of miRNAs ranged from 17 to 24 nt with an average of 20 nt while the length of their precursors varied from 47 to 152 nt with an average of 85 nt. The identified miRNAs were not evenly distributed in each miRNA family, with only one member per family for a majority, and multiple members were also identified for several families. Nucleotide U was dominant in the pre-miRNAs with a percentage of 30.04%. The rainbow trout pre-miRNAs had relatively high negative minimal folding free energy (MFE) and adjusted MFE (AMFE). Not only the mature miRNAs but their precursor sequences are conserved among the living organisms. About 2466 O. mykiss genes were predicted as potential targets for 189 miRNAs. Gene Ontology (GO) analysis showed that nearly 2093, 2107, and 2081 target genes are involved in cellular component, molecular function, and biological processes respectively. KEGG pathway enrichment analysis illuminated that these miRNAs targets might regulate 105 metabolic pathways, including those of purine metabolism, nitrogen metabolism, and oxidative phosphorylation. This study has provided an update on rainbow trout miRNAs and their targets, which represents a foundation for future studies.     

How can quantum mechanics of material evolution be possible?: Symmetry and symmetry-breaking in protobiological evolution

Material self-assembly as a self-organizing process is always accompanied by symmetry-breaking in the material configuration. Self-sequencing of amino acids during their thermal polymerization has lost a certain property of permutation symmetry that was observed in the mixture of free amino acids. The evolutionary precursor state is more symmetrical about its internal material configuration and more degenerate due to the multitude of the indistinguishable individuals. The evolution proceeds in the direction along which the degeneracy in the internal states dissolves owing to the symmetry-breaking originating in material flow equilibrium of open material aggregates. Protobiological information is latent in the material system which is highly symmetrical and highly degenerate in its internal states. Evolution of matter is an endogenous process in which the earlier symmetric property is lost and less degenerate states are approached. Quantum-mechanically, the generation of protobiological information is due to the symmetry-breaking of the Hamiltonian originating in the interaction with the exterior through material flow, in contrast to the Schrödinger equation which preserves a symmetry and the associated invariants.     

Gene regulatory network inference by point-based Gaussian approximation filters incorporating the prior information

Abstract

The extended Kalman filter (EKF) has been applied to inferring gene regulatory networks. However, it is well known that the EKF becomes less accurate when the system exhibits high nonlinearity. In addition, certain prior information about the gene regulatory network exists in practice, and no systematic approach has been developed to incorporate such prior information into the Kalman-type filter for inferring the structure of the gene regulatory network. In this paper, an inference framework based on point-based Gaussian approximation filters that can exploit the prior information is developed to solve the gene regulatory network inference problem. Different point-based Gaussian approximation filters, including the unscented Kalman filter (UKF), the third-degree cubature Kalman filter (CKF₃), and the fifth-degree cubature Kalman filter (CKF₅) are employed. Several types of network prior information, including the existing network structure information, sparsity assumption, and the range constraint of parameters, are considered, and the corresponding filters incorporating the prior information are developed. Experiments on a synthetic network of eight genes and the yeast protein synthesis network of five genes are carried out to demonstrate the performance of the proposed framework. The results show that the proposed methods provide more accurate inference results than existing methods, such as the EKF and the traditional UKF.