Use of the β‐function to estimate the skewness of species responses

Abstract. Response of a species to an environmental variable may be modeled and predicted using a wide spectrum of different functions. Contrary to other functions (Gaussian, polynomial etc), all parameters of the β‐function are interpretable in ecological terms. However, computational difficulties in the determination of the β‐function parameters initiated controversial debates on the applicability and usefulness of this function in vegetation modelling and gradient analysis. We propose a simple algorithm for fitting the β‐function to observed data. Analytic properties of the algorithm (its ability to recover the known species responses along gradients) are tested using a series of simulated data. In most cases the algorithm correctly estimated parameters of the simulated responses.     

生态样带边界分析的改进算法与网络计算

确定生态样带的边界,其目的是找出样带中的一系列不连续点,判定生物物种扩散的自然屏障,分析生物分布及其景观多样性．生态样带边界分析对有害生物的扩散、生物物种分布研究以及生物多样性保护具有一定的意义．本文在前人研究的基础上,对生态样带边界分析算法进行了改进,在算法中加入了不同的距离测度,由方差／均值比率确定窗口宽度数,用置信区间及其统计检验来确定样带边界．改进算法减少了主观性,具有较高的灵敏度,可检测出更细致的边界点．研制了改进算法的Java网络软件,可在多种兼容Java的网络洲览器,如Internet Explorer,HotJava,Nescape Navigator上调用和运行．以稻田生态环境的节肢动物样带对算法进行了检验和实例分析．结果显示,低营养级的植食性节肢动物,其分布受可见边界的显著影响．高营养级的捕食性节肢动物和寄生性节肢动物的分布也受到可见边界的一定影响,但不很显著．另外,也检测到植食性节肢动物在样带中的扩散方向．相对于植食性节肢动物,捕食性节肢动物和寄生性节肢动物的扩散无明显规律性．     

A simple method to improve probe set estimates from oligonucleotide arrays

A popular commercially available oligonucleotide microarray technology employs sets of 25 base pair oligonucleotide probes for measurement of gene expression levels. A mathematical algorithm is required to compute an estimate of gene expression from the multiple probes. Previously proposed methods for summarizing gene expression data have either been substantially ad hoc or have relied on model assumptions that may be easily violated. Here we present a new algorithm for calculating gene expression from probe sets. Our approach is functionally related to leave-one-out cross-validation, a non-parametric statistical technique that is often applied in limited data situations. We illustrate this approach using data from our study seeking a molecular fingerprint of STAT3 regulated genes for early detection of human cancer.     

The community structure of human cellular signaling network

Living cell is highly responsive to specific chemicals in its environment, such as hormones and molecules in food or aromas. The reason is ascribed to the existence of widespread and diverse signal transduction pathways, between which crosstalks usually exist, thus constitute a complex signaling network. Evidently, knowledge of topology characteristic of this network could contribute a lot to the understanding of diverse cellular behaviors and life phenomena thus come into being. In this presentation, signal transduction data is extracted from KEGG to construct a cellular signaling network of Homo sapiens, which has 931 nodes and 6798 links in total. Computing the degree distribution, we find it is not a random network, but a scale-free network following a power-law of P(K) approximately K(-gamma), with gamma approximately equal to 2.2. Among three graph partition algorithms, the Guimera's simulated annealing method is chosen to study the details of topology structure and other properties of this cellular signaling network, as it shows the best performance. To reveal the underlying biological implications, further investigation is conducted on ad hoc community and sketch map of individual community is drawn accordingly. The involved experiment data can be found in the supplementary material.     

The neurodynamics underlying attentional control in set shifting tasks

In this work we address key phenomena observed with classical set shifting tasks as the “Wisconsin Card Sorting Test” or the “Stroop” task: Different types of errors and increased response times reflecting decreased attention. A component of major importance in these tasks is referred to as the “attentional control” thought to be implemented by the prefrontal cortex which acts primarily by an amplification of task relevant information. This mode of operation is illustrated by a neurodynamical model developed for a new kind of set shifting experiment: The Wisconsin-Delayed-Match-to-Sample task combines uninstructed shifts as investigated in Wisconsin-like tasks with a Delayed-Match-to-Sample paradigm. These newly developed WDMS experiments in conjunction with the neurodynamical simulations are able to explain the reason for decreased attention in set shifting experiments as well the different consequences of decreased attention in tasks requiring bivalent yes/no responses compared to tasks requiring multivalent responses. Electronic supplementary material  The online version of this article (doi: ) contains supplementary material, which is available to authorized users.

Organelle dynamics and viral infections: at cross roads

Viruses are obligate intracellular parasites of the host cells. A commonly accepted view is the requirement of internal membranous structures for various aspects of viral life cycle. Organelles enable favourable intracellular environment for several viruses. However, studies reporting organelle dynamics upon viral infections are scant. In this review, we aim to summarize and highlight modulations caused to various organelles upon viral infection or expression of its proteins.     

应用流式细胞Index Sorting技术研究小鼠胚胎生血内皮细胞

目的:应用流式Index Sorting技术鉴定小鼠胚胎期d10(E10)的主动脉中生血内皮细胞(HEC)的表面分子表达特征,并结合体外孵育实验及免疫组化染色验证HEC的生血潜能。方法:已有研究显示细胞表面分子Kit和CD47均能标记造血相关群体。在此基础上,应用流式细胞Index Sorting技术分选单个分子表型为CD41^-CD43^-CD45^-CD31^+Kit^+的主动脉内皮细胞,并与基质细胞OP9-DL1共孵育诱导培养7 d,进而结合单个内皮细胞的流式分选特征参数,及诱导后生成CD45^+造血细胞和CD31^+内皮细胞的效率,综合回溯分析Kit和CD47富集HEC的效果。结果:具有生血潜能的HEC均富集在CD47^+内皮细胞群体中,CD47分子将HEC群体的精度提高1.5倍;CD47^+内皮群体中,仍有60%以上的内皮不具备生血能力,提示进一步探索寻找富集HEC表面标志的必要性。结论:应用流式细胞Index Sorting技术发现CD47分子能显著富集小鼠胚胎期HEC,为进一步精准富集并研究HEC提供了重要的技术手段。     

真核蛋白质的亚细胞位点预测研究进展

研究真核蛋白质的亚细胞位点是了解真核蛋白质功能,深入研究蛋白质相关信号通路内在机制的基础。同时,可以为了解 疾病发病机制及为新药研发提供帮助。因此,研究真核蛋白质的亚细胞位点意义十分重大。随着基因组测序的完成,真核蛋白质 序列信息增长迅速,为真核蛋白质亚细胞位点的研究提出了更多的挑战。传统的实验法难以满足蛋白质信息量迅速增长的需求。 而采用生物信息学手段处理大规模数据的计算预测方法,可在较短时间内获得大量真核蛋白质亚细胞位点信息,弥补了实验法 的不足。因此,运用计算预测法预测真核蛋白质的亚细胞位点成为生物信息学领域的研究热点之一。本文主要从提取真核蛋白质 的特征信息、计算预测方法及预测效果的评价三个方面,介绍近年来真核蛋白质亚细胞位点预测的研究进展。