农业生态系统能量分析

农业生态系统的能量分析从能流着手进行农业生态系统的功能量化分析,是农业生态系统重要的研究方法之一。本文简要回顾讨论了农业生态系统能量分析研究的历史和进展。着重讨论了能值分析方法对传统能量分析方法的新发展,分析了农业生态系统能量分析目前存在的问题,并就其进一步发展方向进行了探讨能值分析方法用生产某种能量或物质所直接或间接耗用的太阳能值量来衡量该能量或物质的价值,不仅在概念上而且在算法上都是原有能量分析方法的新发展．发展到能值分析阶段的农业生态系统的能量分析方法亦存有自身的不足之处,如能值转换率的计算过于繁复,能值指标体系缺乏统一性及系统可持续发展的能值综合评价指标缺乏等。这些问题的解决与能值最大功率的明晰化、能值分析与能量及耗散分析的结合、与物质分析及景观结构分析的结合等研究等共同构成了农业生态系统能量分析的几大发展方向。     

新基因功能研究的策略与方法

开展新基因功能研究在当前生物医学研究中变得日益重要.基因功能的研究策略主要包括新基因的生物信息学及体内表达规律分析、功能获得与功能失活策略研究、基因编码产物相互作用蛋白的研究.同时,结合近年来国内外的一些新进展,对与各种策略相关的一些技术方法也进行了介绍.     

MAGMA: Generalized Gene-Set Analysis of GWAS Data

By aggregating data for complex traits in a biologically meaningful way, gene and gene-set analysis constitute a valuable addition to single-marker analysis. However, although various methods for gene and gene-set analysis currently exist, they generally suffer from a number of issues. Statistical power for most methods is strongly affected by linkage disequilibrium between markers, multi-marker associations are often hard to detect, and the reliance on permutation to compute p-values tends to make the analysis computationally very expensive. To address these issues we have developed MAGMA, a novel tool for gene and gene-set analysis. The gene analysis is based on a multiple regression model, to provide better statistical performance. The gene-set analysis is built as a separate layer around the gene analysis for additional flexibility. This gene-set analysis also uses a regression structure to allow generalization to analysis of continuous properties of genes and simultaneous analysis of multiple gene sets and other gene properties. Simulations and an analysis of Crohn’s Disease data are used to evaluate the performance of MAGMA and to compare it to a number of other gene and gene-set analysis tools. The results show that MAGMA has significantly more power than other tools for both the gene and the gene-set analysis, identifying more genes and gene sets associated with Crohn’s Disease while maintaining a correct type 1 error rate. Moreover, the MAGMA analysis of the Crohn’s Disease data was found to be considerably faster as well.     

Excel在药学数据分析工作中的应用

目的：采用常用的电子表格处理系统Microsoft Excel解决药学实验过程中遇到的数据分析问题。方法：应用工作表函数中内置的统计函数,以线性回归为例说明源数据的输入与结果返回的具体操作过程;对数据分析工具中的＂描述统计＂工具、t检验与方差分析,结合具体实例对药学实践中遇到的药学统计实际问题进行综合探讨。结果：用Excel表中内置的统计函数工具进行线性回归分析,方法简单、结果可靠;Excel表中的数据分析工具适用于日常药学实验数据分析过程中遇到的描述统计分析、t检验与方差分析。Excel与其它数据处理软件相比具有操作快捷、使用方便、计算精确、易于学习与掌握等优点。结论：Excel友好的界面,清晰的统计分析结果,使医药工作者在使用Excel的数据分析软件时会感到非常的方便快捷,灵活实用,值得在药学实践中应用推广。     

Biosensors and flow injection analysis.

Combining flow injection analysis with a biosensor is a novel biosensing process which has allowed speedy and accurate analysis. Diagnostic analysis is the most important application for biosensing flow injection analysis, but other applications include bioprocess monitoring, analysis of food and agricultural products, as well as environmental analysis. In addition, the analysis of compounds, such as explosives and abused drugs, and monitoring of Salmonella, the microorganism that causes food poisoning, have been reported.     

群落二维格局分析的两种方法

群落二维空间格局研究能够更好地揭示群落的特征,但在分析方法上有较大的困难。用垂直相交的两条样带在两个方向上同时取样的二维取样法,获得数据,用DCA排序与格局分析相结合的方法,得到群落不同格局规模斑块的长、宽及面积,实现二维格局研究。在亚高山草甸群落格局研究中应用表明,两个方法均是有效的。     

谱分析在DNA序列分析中的应用

目的：谱分析是信号处理的常用方法,其中的统计相关分析、傅里叶变换、小波变换和数字滤波等手段已逐渐应用到DNA序列的分析中,这些应用包括DNA序列的周期性分析、基因识别和同源性分析等方面。本文对谱分析方法在DNA序列分析中的应用情况进行简单的综述。     

环境投入产出分析在产业生态学中的应用

综述了环境投入产出分析的基本知识及其在产业生态学领域的应用。环境投入产出分析的核心是投入产出模型,包括价值型投入产出模型、实物型投入产出模型和混合型投入产出模型。环境投入产出分析在产业生态学领域主要用于环境压力核算、生命周期评估、社会经济因素相对贡献分析、产业链路径分析、风险影响分析和环境网络分析。同时,相关学者进行环境投入产出数据库开发,给环境投入产出分析提供便捷、标准化的数据渠道。讨论了环境投入产出分析的若干发展趋势。     

Co-inertia analysis: an alternative method for studying species–environment relationships

• 1 Methods used for the study of species–environment relationships can be grouped into: (i) simple indirect and direct gradient analysis and multivariate direct gradient analysis (e.g. canonical correspondence analysis), all of which search for non-symmetric patterns between environmental data sets and species data sets; and (ii) analysis of juxtaposed tables, canonical correlation analysis, and intertable ordination, which examine species–environment relationships by considering each data set equally. Different analytical techniques are appropriate for fulfilling different objectives.
• 2 We propose a method, co-inertia analysis, that can synthesize various approaches encountered in the ecological literature. Co-inertia analysis is based on the mathematically coherent Euclidean model and can be universally reproduced (i.e. independently of software) because of its numerical stability. The method performs simultaneous analysis of two tables. The optimizing criterion in co-inertia analysis is that the resulting sample scores (environmental scores and faunistic scores) are the most covariant. Such analysis is particularly suitable for the simultaneous detection of faunistic and environmental features in studies of ecosystem structure.
• 3 The method was demonstrated using faunistic and environmental data from Friday (Freshwater Biology 18, 87-104, 1987). In this example, non-symmetric analyses is inappropriate because of the large number of variables (species and environmental variables) compared with the small number of samples.
• 4 Co-inertia analysis is an extension of the analysis of cross tables previously attempted by others. It serves as a general method to relate any kinds of data set, using any kinds of standard analysis (e.g. principal components analysis, correspondence analysis, multiple correspondence analysis) or between-class and within-class analyses.

     

Comparison of methods for enumeration of interacting species in a biological system

Matrix rank analysis, a method extensively used to enumerate interacting species or components in various biological systems, has been compared with the more readily available technique of factor analysis. Data previously analyzed by matrix rank analysis has been subjected to factor analysis. The results show that there are some agreements and disagreements between the two methods. The sources and nature of the disagreements are discussed. Our work indicates that factor analysis may be preferable to matrix rank analysis.     

On the Effect of Correlation Between Plots in Randomized Block Experiments

Correlation between adjacent plots in field experiments are common. In this paper the effect of correlation on the usual analysis of variance in a randomized block design is studied. A generalised analysis of variance where correlation is taken into consideration, and the analysis of covariance where the residuals of the neighbouring plots are used as covariates, is discussed. Uniformity trials are used as a basis of a Monte-Carlo study. The generalised analysis improved the power of the tests. The analysis of covariance method was not better than the usual analysis of variance method.     

DNA分析技术及其在植物研究中的应用

从DNA/DNA杂交、RFLP分析、DNA的限制酶图谱和核苷酸序列分析、PCR技术、DNA指纹技术、RAPD分析等六个方面详细描述DNA分析技术在植物学研究中的应用 ,并讨论了DNA分析技术与植物系统学的关系。     

Bioinformatic and image analyses of the cellular localization of the apoptotic proteins endonuclease G,AIF, and AMID during apoptosis in human cells

We studied the cellular localization of the apoptotic proteins endonuclease G, AIF, and AMID in silico using three prediction tools and in living cells using both single-cell colocalization image analysis and nuclear translocation analysis. We confirmed the mitochondrial localization of endonuclease G and AIF by prediction analysis and by single-cell colocalization image analysis. We found the AMID protein to be cytoplasmic, most probably incorporated into the cytoplasmic side of the membranes of various organelles. The highest concentration of AMID was observed associated with the Golgi. Colocalization of AMID with lysosomes was also indirectly confirmed by analysis of AMID-rich vesicle velocity using manual tracking analysis. Bioinformatic analysis also detected nuclear localization signals in endonuclease G and AIF, but not in AMID. A novel analysis of time-lapse fluorescence image data during staurosporine-induced apoptosis revealed nuclear translocation only for endonuclease G and AIF.     

中国串珠藻科植物地理分布及与环境因子的关系

研究以中国串珠藻科Batrachospermaceae的串珠藻属Batrachospermum、熊野藻属Kumanoa和西斯藻属Sheathia植物样本的经纬度和一些重要环境因子数据为研究材料, 采用方差分析、相关分析、主成分分析和线性判别分析的方法, 分析这些环境因子对3个属的地理分布影响及3个属地理分布和生长环境的差异性。根据方差分析和线性判别分析结果可知, 串珠藻属、熊野藻属和西斯藻属的地理分布和生长环境具有明显差异性。相关分析和主成分分析结果显示, 海拔高度、平均相对湿度、平均风速、最大可持续风速和大气压强是影响串珠藻属、熊野藻属和西斯藻属地理分布的重要环境因素。研究结果可为丰富我国淡水红藻生态地理分布和地理起源研究提供重要科学依据。     

文本分析技术在蛋白质生物信息学中应用的案例综述

海量数据时代考察文本分析技术在生物信息学领域的应用具有重要的理论和现实价值。本文讨论了文本分析在蛋白质计算分析中的几个应用实例以及核心技术内容。文本分析技术应用于生物信息学领域可发挥引领和导向作用,在生物信息学中的应用又进一步促进了文本分析技术的发展。文本分析技术虽然广泛在生物信息学中应用,但是其发展仍然有需要尚待解决的几个问题,本文对此也进行了讨论。     

基因芯片数据分析过程:从原始数据到生物学意义

基因芯片实验要得到可靠的生物学结论,必须基于优化的实验设计和科学的数据分析。讨论了与基因芯片数据分析方法相关的实验设计方面的几个问题,简述了差异表达分析、聚类分析及功能富集分析等分析方法及其进展,并介绍了部分软件及应用。     

CorrXpression--identification of significant groups of genes and experiments by means of correspondence analysis and ratio analysis

CorrXpression is a stand-alone desktop application for the identification of significant genes within collections of microarrays. The software combines three methods in two steps of analysis: correspondence analysis (CA), ratio analysis and correlation analysis. The graphical interface of CorrXpression visualizes the result of the CA with a biplot and the expression of selected genes in dependency of the experiments as bar diagrams. The CA-plot is an excellent tool for visualization and evaluation of data and results of ratio analysis and correlation analysis. The input data are selected from a database or from appropriate ASCII files.