Identification of domains and domain interface residues in multidomain proteins from graph spectral method

We present a novel method for the identification of structural domains and domain interface residues in proteins by graph spectral method. This method converts the three-dimensional structure of the protein into a graph by using atomic coordinates from the PDB file. Domain definitions are obtained by constructing either a protein backbone graph or a protein side-chain graph. The graph is constructed based on the interactions between amino acid residues in the three-dimensional structure of the proteins. The spectral parameters of such a graph contain information regarding the domains and subdomains in the protein structure. This is based on the fact that the interactions among amino acids are higher within a domain than across domains. This is evident in the spectra of the protein backbone and the side-chain graphs, thus differentiating the structural domains from one another. Further, residues that occur at the interface of two domains can also be easily identified from the spectra. This method is simple, elegant, and robust. Moreover, a single numeric computation yields both the domain definitions and the interface residues.     

Simple critical schemes in non-autocatalytic systems of biochemical reactions

Kinetic behavior of various reaction systems consisting of three compounds was analyzed in order to find and study the origin of multiple-steady-state and auto-oscillatory behavior in biochemical systems. More than 3000 such reactions were considered. Using the bigraph method, six simple critical reaction schemes were found. It is shown that the presence of these fragments in the composition of more complex biochemical systems may be the origin of the multiple steady-states and autooscillations.     

Disease gene identification by using graph kernels and Markov random fields

Genes associated with similar diseases are often functionally related. This principle is largely supported by many biological data sources, such as disease phenotype similarities, protein complexes, protein-protein interactions, pathways and gene expression profiles. Integrating multiple types of biological data is an effective method to identify disease genes for many genetic diseases. To capture the gene-disease associations based on biological networks, a kernel-based MRF method is proposed by combining graph kernels and the Markov random field (MRF) method. In the proposed method, three kinds of kernels are employed to describe the overall relationships of vertices in five biological networks, respectively, and a novel weighted MRF method is developed to integrate those data. In addition, an improved Gibbs sampling procedure and a novel parameter estimation method are proposed to generate predictions from the kernel-based MRF method. Numerical experiments are carried out by integrating known gene-disease associations, protein complexes, protein-protein interactions, pathways and gene expression profiles. The proposed kernel-based MRF method is evaluated by the leave-one-out cross validation paradigm, achieving an AUC score of 0.771 when integrating all those biological data in our experiments, which indicates that our proposed method is very promising compared with many existing methods.     

EPG technique as a tool to reveal host plant acceptance by xylem sap‐feeding insects

The discovery of a new exotic insect herbivore triggers responses from biosecurity agencies, one of which is the decision of whether or not to attempt eradication. Rapid determination of the host range of the new invader is necessary, but when sap‐sucking insects are first collected from plants, the lack of visible signs of feeding damage makes it difficult to determine their host status. We investigated the Electrical Penetration Graph (EPG‐DC) technique as tool to assess host range of a xylem sap‐feeding invader, using Carystoterpa fingens (Hemiptera: Aphrophoridae), a New Zealand endemic xylem feeder, as a model insect. Real‐time probing and feeding events over a 12‐h recording period were compared for adult C. fingens on 18 plant species. Hebe azure, a known host, was designated the ‘reference plant species’ against which events on all other plants were statistically compared. EPG waveforms were categorized on their amplitude, frequency, voltage and electrical origin, and six parameters (time taken to first probe, time to first xylem ingestion from first probe, total probing time, number of xylem‐ingesting events, duration of the longest xylem‐ingesting event and total xylem ingestion time) were measured. The total xylem ingestion period (i.e. the actual feeding period) on each plant species expressed as a percentage of total probing time was considered the best parameter for comparing the host status of plants with H. azure. Although the EPG data overestimated the actual host range of C. fingens, we consider that they provided a reasonable first guide to the potential host status of the unknown plants, and so might usefully be used to rapidly assess whether a plant from which a new invader was collected was a host, or whether the association was merely incidental.     

MapGene2Chrom基于Perl和SVG语言绘制基因物理图谱

遗传图谱表现形式简洁明了,为分析遗传规律、克隆基因提供了便利。Gbrowse、MapViewer等工具虽然能够协助研究人员绘制相似形式的物理图谱,但有很大的局限性:(1)数据需提前布置好;(2)输出结果无法灵活修改。鉴于此,文章基于Perl和SVG语言,开发了一款生物辅助作图软件MapGene2Chrom的本地版与网页版,该软件能够依据输入数据快速绘制相应的物理图谱。该软件输入数据格式简单,输出结果易于修改,图片格式为SVG矢量图,具有很好的移植性,以期为研究人员绘制物理图谱提供便利。     

木薯和玉米原料丁醇发酵中丁醇丙酮质量比的图论理论计算及其验证

在丁醇发酵产溶剂阶段,乙酸和丁酸的生成途径、消耗途径同时存在,各自形成一个闭环路径。本研究利用图论对丁醇发酵中丁醇丙酮质量比进行了理论计算,并对以木薯和玉米为原料的丁醇发酵进行了模拟计算,结果表明:丁酸闭环路径(L2环)的代谢强度是影响丁醇丙酮质量比的主要因素,并且L2环的代谢强度越弱,丁醇丙酮质量比越高;与玉米原料丁醇发酵相比,木薯原料发酵的m(丁醇)/m(丙酮)提高了16.7%。实验结果证实了以上计算结果:在传统发酵、油醇萃取发酵和生物柴油萃取发酵中,以木薯(适时添加酵母浸粉)为原料的发酵批次与以玉米为原料的发酵批次相比,由于其丁酸闭环路径代谢强度较弱,相应发酵方式下丁醇丙酮质量比分别提高了12.9%、61.4%和6.7%,而且两种原料相应发酵方式的丁醇总产量和生产效率基本持平。另外,高丁醇丙酮质量比的木薯发酵所得改良型生物柴油中丁醇浓度与玉米发酵的相比提高了16%,性能得到进一步提高。     

科技论文中线条图的优化编辑

线条图已在科技论文中得到广泛应用,良好的线条图可以将复杂的数据资料直观、简洁、明了地展现在读者面前,更有利于读者阅读和获取信息,更有助于作者思想的表达和科技信息的传播。以科技论文作者使用线条图中存在的问题为例,着重介绍了科技论文中线条图的几种优化方法。作者根据多年的编辑加工经验,通过对图类型选择、横纵坐标和图例的调整、图的合并拆分、图表转换、代码应用等方面的优化实例,为科技论文的合理加工提供信息和方法。通过线条图的优化,准确表达作者的思想和科学研究结果,有效地促进科技成果的快速传播。     

基于图论的两栖类生物栖息地网络规划——以黑斑侧褶蛙为例

生物多样性保护和生物栖息地网络建设是目前我国国土空间规划的重要内容,提升生物栖息地网络的景观功能连接度对生物多样性保护具有重要作用。目前,已有研究对生物栖息地网络规划进行了探索,但在实际规划层面仍缺乏可操作性强的技术方法支撑。本研究采用图论方法,聚焦国土空间规划中生物多样性保护和生态网络建设涉及的进行生物栖息地斑块重要性评价,以确定斑块优先保护次序;寻找最优新增斑块位置,以改善生物栖息地网络景观功能连接度;依据景观功能连接度的降低程度,判断建设项目的影响或评价规划新增建设项目的潜在影响3方面内容,在雄安新区两栖类生物黑斑侧褶蛙(Pelophylax nigromaculata)栖息地网络规划中进行应用研究。结果表明: 图论方法可以有效解决上述3方面的问题;本研究识别的5个最优新增黑斑侧褶蛙栖息地位置使栖息地网络整体景观功能连接度提升19%;通过评价G45高速公路对两栖类生物栖息地网络功能连接度的影响,找出了4个穿越通道设置以减弱G45高速公路的影响。