Detecting two-dimensional spatial structure in biological data

Summary Cliff and Ord (1973) made versatile methods available for the direct utilization of location data in the analysis of dispersion patterns, but their monograph has as yet seen little use in the ecological literature. Application of their weighted forms of Geary's c and Moran's I indices of spatial autocorrelation to some marine benthos data demonstrates a diversity of population structure not anticipated on the basis of more common measures of pattern. These indices provide objective means to evaluate numerous recent spatial models and hypotheses in geographical ecology and genetics. The procedures are particularly attractive because (1) they efficiently utilize data which are often wasted (i.e., sample coordinates), (2) their application puts few constraints on sampling designs which would otherwise be employed, and (3) they reveal and quantify pattern differences which are not obvious to the untrained eye.Contribution #949 from the Department of Oceanography, University of Washington     

Detecting conserved interaction patterns in biological networks.

Molecular interaction data plays an important role in understanding biological processes at a modular level by providing a framework for understanding cellular organization, functional hierarchy, and evolutionary conservation. As the quality and quantity of network and interaction data increases rapidly, the problem of effectively analyzing this data becomes significant. Graph theoretic formalisms, commonly used for these analysis tasks, often lead to computationally hard problems due to their relation to subgraph isomorphism. This paper presents an innovative new algorithm, MULE, for detecting frequently occurring patterns and modules in biological networks. Using an innovative graph simplification technique based on ortholog contraction, which is ideally suited to biological networks, our algorithm renders these problems computationally tractable and scalable to large numbers of networks. We show, experimentally, that our algorithm can extract frequently occurring patterns in metabolic pathways and protein interaction networks from the KEGG, DIP, and BIND databases within seconds. When compared to existing approaches, our graph simplification technique can be viewed either as a pruning heuristic, or a closely related, but computationally simpler task. When used as a pruning heuristic, we show that our technique reduces effective graph sizes significantly, accelerating existing techniques by several orders of magnitude! Indeed, for most of the test cases, existing techniques could not even be applied without our pruning step. When used as a stand-alone analysis technique, MULE is shown to convey significant biological insights at near-interactive rates. The software, sample input graphs, and detailed results for comprehensive analysis of nine eukaryotic PPI networks are available at www.cs.purdue.edu/homes/koyuturk/mule.     

Detecting spatial patterns in species composition with multiple plot similarity coefficients and singularity measures

Recently, several multiple plot similarity indices have been presented that cure some of the problems associated with the approaches for the calculation of compositional similarity for groups of plots by averaging pairwise similarities. These new indices calculate the similarity between more than two plots whilst considering the species composition on all compared plots. The resulting similarity value is true for the whole group of plots considered (called neighborhood in the following). Here, we review the possibilities for multiple plot similarity calculation and additionally explore coefficients that examine multiple plot similarity between a reference plot (named focal plot in the following) and any number of surrounding plots. The latter represent measures of singularity. Further, we establish a framework for applying these two kinds of multiple plot measures to gridded data including an algorithm for testing the significance of calculated values against random expectations. The capability of multiple plot measures for detecting species compositional gradients and local/regional hotspots within this framework is tested. For this purpose, several artificial data sets with known gradients in species composition (random, gradient, central hotspot, hotspot bottom right) are constructed on the basis of a real data set from a Tundra ecosystem in northern Sweden (Abisko). The coefficients that best reflect the positions of the plots on the realized gradients in species composition are considered as performing best with regard to pattern detection. The tested measures of multiple plot similarity and singularity produced considerably different results when applied to one real and 4 artificial data sets. The newly proposed symmetric singularity coefficient has the best overall performance which makes it suitable for local/regional hotspot detection and for incorporating local to regional similarity analyses in reserve selection procedures.     

对生化分离技术实验的探讨

实验教学的改进和提高,是教学改革的重要一环。阐述了作者在教学实践的过程中,对生化分离技术实验中的原料选取、处理方法、仪器设备等方面所作的改进尝试而取得的成效。     

Detecting spatial hot spots in landscape ecology

Hot spots are typically locations of abundant phenomena. In ecology, hot spots are often detected with a spatially global threshold, where a value for a given observation is compared with all values in a data set. When spatial relationships are important, spatially local definitions – those that compare the value for a given observation with locations in the vicinity, or the neighbourhood of the observation – provide a more explicit consideration of space. Here we outline spatial methods for hot spot detection: kernel estimation and local measures of spatial autocorrelation. To demonstrate these approaches, hot spots are detected in landscape level data on the magnitude of mountain pine beetle infestations. Using kernel estimators, we explore how selection of the neighbourhood size (τ) and hot spot threshold impact hot spot detection. We found that as τ increases, hot spots are larger and fewer; as the hot spot threshold increases, hot spots become larger and more plentiful and hot spots will reflect coarser scale spatial processes. The impact of spatial neighbourhood definitions on the delineation of hot spots identified with local measures of spatial autocorrelation was also investigated. In general, the larger the spatial neighbourhood used for analysis, the larger the area, or greater the number of areas, identified as hot spots.     

Detecting changes in soil carbon in CO2 enrichment experiments

After four growing seasons, elevated CO₂ did not significantly alter surface soil C pools in two intact annual grasslands. However, soil C pools in these systems are large compared to the likely changes caused by elevated CO₂. We calculated statistical power to detect changes in soil C, using an approach applicable to all elevated CO₂ experiments. The distinctive isotopic signature of the fossil-fuel-derived CO₂ added to the elevated CO₂ treatment provides a C tracer to determine the rate of incorporation of newly-fixed C into soil. This rate constrains the size of the possible effect of eievated CO₂ on soil C. Even after four years of treatment, statistical power to detect plausible changes in soil C under elevated CO₂ is quite low. Analysis of other elevated CO₂ experiments in the literature indicates that either CO₂ does not affect soil C content, or that reported CO₂ effects on soil C are too large to be a simple consequence of increased plant carbon inputs, suggesting that other mechanisms are involved, or that the differences are due to chance. Determining the effects of elevated CO₂ on total soil C and long-term C storage requires more powerful experimental techniques or experiments of longer duration.     

Automated image analysis for array hybridization experiments.

MOTIVATION: Image analysis is a major part of data evaluation for array hybridization experiments in molecular biology. The program presented here is designed to analyze automatically images from hybridization experiments with various arrangements: different kinds of probes (oligonucleotides or complex probes), different supports (nylon filters or glass slides), different labeling of probes (radioactively or fluorescently). The program is currently applied to oligonucleotide fingerprinting projects and complex hybridizations. The only precondition for the use of the program is that the targets are arrayed in a grid, which can be approximately transformed to an orthogonal equidistant grid by a projective mapping. RESULTS: We demonstrate that our program can cope with the following problems: global distortion of the grid, missing of grid nodes, local deviation of the spot from its specified grid position. This is checked by different quality measures. The image analysis of oligonucleotide fingerprint experiments on an entire genetic library is used, in clustering procedures, to group related clones together. The results show that the program yields automatically generated high quality input data for follow up analysis such as clustering procedures. AVAILABILITY: The executable files will be available upon request for academics.     

Photolysis of cholesterol during biological experiments

1. When dilute aqueous emulsions of radioactive cholesterol are exposed to daylight, extensive photolysis may take place. This results chiefly in the formation of substances more polar than cholesterol, some of which are probably acidic. Substances less polar than cholesterol are formed to a smaller extent. Photolysis is greatest when the emulsions are strongly acidic or strongly alkaline. 2. Photolysis takes place rapidly if radioactive cholesterol stored in the dry state, either on glass or on filter paper, is exposed to daylight. 3. If precautions are taken to minimize exposure to daylight during analysis and storage of the samples, the amount of non-enzymic alteration of cholesterol in biological experiments may be negligible.     

Geometry and spatial patterns in Polysphondylium pallidum

The formation of secondary sori in whorls of Polysphondylium pallidum provides an attractive model system for the study of symmetry breaking during morphogenesis. Tip-specific antibodies that permit detection of very early stages in this patterning process are available. We have found that the patterns of tip-specific antigen expression vary considerably depending on the size, shape, and developmental stage of the whorl. All of these patterns, however, are well explained by patterning models that rely on short-range autocatalysis and long-range inhibition, as exemplified by reaction-diffusion theories. In the context of reaction-diffusion, we discuss the possible effects of initial conditions, boundary conditions, and nonlinearities on the selection of patterns in P. pallidum whorls.     

Passive loss of hydrogen sulfide in biological experiments

Hydrogen sulfide (H(2)S) is a volatile gas of considerable interest as a physiologically relevant signaling molecule, but this volatility has typically been overlooked in the context of biological experiments. We examined volatility of 10 and 100 μM H(2)S (Na(2)S·9H(2)O) in real time with polarographic electrodes in three commonly employed experimental apparatuses: 24-well tissue culture plates (WP), muscle myograph baths (MB), and the Langendorff perfused heart apparatus (LPH). H(2)S loss from all apparatuses was rapid and exponential, with half-times (t(1/2)) of 5 min (WP), less than 4 min (MB), and less than 0.5 min (LPH). The t(1/2) for H(2)S loss from MB bubbled with 100% oxygen was slightly longer than that for MB bubbled with 100% nitrogen; both were significantly shorter than stirred but unbubbled MB (>9 min). Therefore, even without tissue, H(2)S rapidly disappears from buffer under a variety of experimental conditions, and this is due to volatilization, not oxidation. The inability to maintain H(2)S concentration, even briefly, questions the accuracy of dose-response studies and the relevance of long-term (>10 min) exposure to a single treatment of H(2)S. These results also help to explain the discrepancy between low H(2)S concentrations in blood and tissues versus high concentrations of exogenous H(2)S required to produce physiological responses.     

Algorithmic approaches to selecting control clones in DNA array hybridization experiments

We study the problem of selecting control clones in DNA array hybridization experiments. The problem arises in the OFRG method for analyzing microbial communities. The OFRG method performs classification of rRNA gene clones using binary fingerprints created from a series of hybridization experiments, where each experiment consists of hybridizing a collection of arrayed clones with a single oligonucleotide probe. This experiment produces analog signals, one for each clone, which then need to be classified, that is, converted into binary values 1 and 0 that represent hybridization and non-hybridization events. In addition to the sample rRNA gene clones, the array contains a number of control clones needed to calibrate the classification procedure of the hybridization signals. These control clones must be selected with care to optimize the classification process. We formulate this as a combinatorial optimization problem called Balanced Covering. We prove that the problem is NP-hard, and we show some results on hardness of approximation. We propose approximation algorithms based on randomized rounding, and we show that, with high probability, our algorithms approximate well the optimum solution. The experimental results confirm that the algorithms find high quality control clones. The algorithms have been implemented and are publicly available as part of the software package called CloneTools.     

视觉图形诱发的瞳孔反应

以图形变化刺激进行瞳孔反应研究,实验表明：（１）空间平均亮度守恒的光栅或棋盘格图形翻转能激发起瞳孔反应,为瞬态收缩波形,与ｐｕｐｉｌｌａｒｙ ｅｓｃａｐｅ相似;（２）光栅或棋盘格的空间频率的变化也能引起瞳孔反应,且反应幅度随空间频率差别增大而变大;（３）从均匀亮背景变化到棋盘格图形或者从棋盘格图形变化到黑暗背景,虽然不存在任何局部亮度增强,皆能引起瞳孔反应。实验结果明确证明了人的瞳孔反应系统除接收     

Statistical evaluation of colocalization patterns in immunogold labeling experiments

The ultrastructural localization of various antigens in a cell using antibodies conjugated to gold particles is a powerful instrument in biological research. However, statistical or stereological tools for testing the observed patterns for significant clustering or colocalization are missing. The paper presents a method for the quantitative analysis of single or multiple immunogold labeling patterns using interpoint distances and tests the method using experimental data. The clustering or colocalization of gold particles was detected using various characteristics of the distribution of distances between them. Pair correlation and cross-correlation functions were used for exploratory analysis; second order reduced K (or cross-K) functions were used for testing the statistical significance of observed events. Confidence intervals of function values were estimated by Monte Carlo simulations of the Poisson process for independent particles, and results were visualized in histograms. Furthermore, a suitability of K functions modified by censoring or weighting was tested. The reliability of the method was assessed by evaluating the labeling patterns of nascent DNA and several nuclear proteins with known functions in replication foci of HeLa cells. The results demonstrate that the method is a powerful tool in biological investigations for testing the statistical significance of observed clustering or colocalization patterns in immunogold labeling experiments.     

Analysis of spatial point patterns in nuclear biology

There is considerable interest in cell biology in determining whether, and to what extent, the spatial arrangement of nuclear objects affects nuclear function. A common approach to address this issue involves analyzing a collection of images produced using some form of fluorescence microscopy. We assume that these images have been successfully pre-processed and a spatial point pattern representation of the objects of interest within the nuclear boundary is available. Typically in these scenarios, the number of objects per nucleus is low, which has consequences on the ability of standard analysis procedures to demonstrate the existence of spatial preference in the pattern. There are broadly two common approaches to look for structure in these spatial point patterns. First a spatial point pattern for each image is analyzed individually, or second a simple normalization is performed and the patterns are aggregated. In this paper we demonstrate using synthetic spatial point patterns drawn from predefined point processes how difficult it is to distinguish a pattern from complete spatial randomness using these techniques and hence how easy it is to miss interesting spatial preferences in the arrangement of nuclear objects. The impact of this problem is also illustrated on data related to the configuration of PML nuclear bodies in mammalian fibroblast cells.     

Bistability and regular spatial patterns in arid ecosystems

A variety of patterns observed in ecosystems can be explained by resource–concentration mechanisms. A resource–concentration mechanism occurs when organisms increase the lateral flow of a resource toward them, leading to a local concentration of this resource and to its depletion from areas farther away. In resource–concentration systems, it has been proposed that certain spatial patterns could indicate proximity to discontinuous transitions where an ecosystem abruptly shifts from one stable state to another. Here, we test this hypothesis using a model of vegetation dynamics in arid ecosystems. In this model, a resource–concentration mechanism drives a positive feedback between vegetation and soil water availability. We derived the conditions leading to bistability and pattern formation. Our analysis revealed that bistability and regular pattern formation are linked in our model. This means that, when regular vegetation patterns occur, they indicate that the system is along a discontinuous transition to desertification. Yet, in real systems, only observing regular vegetation patterns without identifying the pattern-driving mechanism might not be enough to conclude that an ecosystem is along a discontinuous transition because similar patterns can emerge from different ecological mechanisms.