Subjektive Unsicherheit und subjektive Information

Summary The classical measure of uncertanity does not consider the observer and the special nature of the message. The aim of this paper is to introduce a measure of uncertanity, which takes into consideration both the observer and the nature of the message in such a way, that the Shannon measure and the Bongard measure are special forms of our formula.     

Defining viability in mammalian cell cultures

A large number of assays are available to monitor viability in mammalian cell cultures with most defining loss of viability as a loss of plasma membrane integrity, a characteristic of necrotic cell death. However, the majority of cultured cells die by apoptosis and early apoptotic cells, although non-viable, maintain an intact plasma membrane and are thus ignored. Here we measure the viability of cultures of a number of common mammalian cell lines by assays that measure membrane integrity (a measure of necrotic cell death) and assays that measure apoptotic cells, and show that discrepancies in the measurement of culture viability have a significant impact on the calculation of cell culture parameters and lead to skewed experimental data.     

On using landscape metrics for landscape similarity search

Landscape similarity search involves finding landscapes from among a large collection that are similar to a query landscape. An example of such collection is a large land cover map subdivided into a grid of smaller local landscapes, a query is a local landscape of interest, and the task is to find other local landscapes within a map which are perceptually similar to the query. Landscape search and the related task of pattern-based regionalization, requires a measure of similarity – a function which quantifies the level of likeness between two landscapes. The standard approach is to use the Euclidean distance between vectors of landscape metrics derived from the two landscapes, but no in-depth analysis of this approach has been conducted. In this paper we investigate the performance of different implementations of the standard similarity measure. Five different implementations are tested against each other and against a control similarity measure based on histograms of class co-occurrence features and the Jensen–Shannon divergence. Testing consists of a series of numerical experiments combined with visual assessments on a set of 400 3 km-scale landscapes. Based on the cases where visual assessment provides definitive answer, we have determined that the standard similarity measure is sensitive to the way landscape metrics are normalized and, additionally, to whether weights aimed at controlling the relative contribution of landscape composition vs. configuration are used. The standard measure achieves the best performance when metrics are normalized using their extreme values extracted from all possible landscapes, not just the landscapes in the given collection, and when weights are assigned so the combined influence of composition metrics on the similarity value equals the combined influence of configuration metrics. We have also determined that the control similarity measure outperforms all implementations of the standard measure.     

On Population and Sample Measures for the Simple and Multiple Linear Relation

Here population measures and their sample analogue for the linear relation between two or more variables are proposed. Two approximations for the measure in the general case are derived and these are then compared with the exact measure in a special case.     

A comparison of patch connectivity measures using data on invertebrates in hollow oaks

This study aimed at comparing six patch connectivity measures by fitting them to field data. We used occupancy data for eight beetle and two pseudoscorpion species from 281 hollow oaks in southeast Sweden. Species occupancy was modelled in relation to tree characteristics and one measure of patch connectivity at a time. For each connectivity measure we searched for the spatial scale that generated the best fit to field data. Connectivity measures that only include occupied patches provided better model fits than those that include all patches. When occupancy data are absent for surrounding habitat patches, information that reflects occurrence probabilities can be included in the connectivity measure. However, in this study incorporation of such information resulted in only a slight improvement of model fit. A frequently used connectivity measure based on the negative exponential function was relatively poor in explaining species’ occurrence; for eight species out of nine a buffer measure was better. A better fit was obtained when the negative exponential function was modified to take into account that habitat patches may “compete” for the immigrants. The spatial scale with the best fit tended to be larger when we used connectivity measures in which dispersal sources are identified with lower precision. Thus, the outcomes from different multiple‐scale studies are not directly comparable if the density of dispersal sources is not measured in the same way. Overall we conclude that buffer measures are useful, as they give good predictions and are easy to understand and use. If a biologically more realistic measure is needed, one that up‐weights the closest patches should be used. Finally, the possibility that habitat patches may compete with each other for immigrants should be considered when selecting a connectivity measure.     

Some new results on Cox–Czanner divergence and their applications in survival studies

In the present communication, we propose a quantile-based measure for the divergence between two survival functions. This can also be used in a dynamic way where the divergence between survival functions varies with time. Several new properties of the proposed measure are investigated with suitable examples. The behavior of the measure for various reliability models is also investigated. A real data analysis is employed to compare the relative efficacy of two treatment groups using the proposed divergence measure.     

Evaluating the design of flexible manufacturing systems

Evaluating the design of flexible manufacturing systems is complex. Developing a measure of performance useful for evaluating alternate designs continues to be interesting. Here, total productivity of the system is proposed as an appropriate measure. Specification of parameters based upon strategic considerations for this measure are discussed. Finally, the usefulness of the measure is demonstrated through an example.     

A new measure of time-varying association for shared frailty models with bivariate current status data

In this paper, a new measure for assessing the temporal variation in the strength of association in bivariate current status data is proposed. This novel measure is relevant for shared frailty models. We show that this measure is particularly convenient, owing to its connection with the relative frailty variance and its interpretability in suggesting appropriate frailty models. We introduce a method of estimation and standard errors for this measure. We discuss its properties and compare it to an existing measure of association applicable to current status data. Small sample performance of the measure in realistic scenarios is investigated using simulations. The methods are illustrated with bivariate serological survey data on a pair of infections, where the time-varying association is likely to represent heterogeneities in activity levels and/or susceptibility to infection.     

A new distance measure for comparing sequence profiles based on path lengths along an entropy surface

We describe a new distance measure for comparing DNA sequence profiles. For this measure, columns in a multiple alignment are treated as character frequency vectors (sum of the frequencies equal to one). The distance between two vectors is based on minimum path length along an entropy surface. Path length is estimated using a random graph generated on the entropy surface and Dijkstra's algorithm for all shortest paths to a source. We use the new distance measure to analyze similarities within familes of tandem repeats in the C. elegans genome and show that this new measure gives more accurate refinement of family relationships than a method based on comparing consensus sequences.     

Associations between sperm competition and natural variation in male reproductive genes on the third chromosome of Drosophila melanogaster

We applied association analysis to elucidate the genetic basis for variation in phenotypes affecting postcopulatory sexual selection in a natural population of Drosophila melanogaster. We scored 96 third chromosome substitution lines for nine phenotypes affecting sperm competitive ability and genotyped them at 72 polymorphisms in 13 male reproductive genes. Significant heterogeneity among lines (P < 0.01) was detected for all phenotypes except male-induced refractoriness (P = 0.053). We identified 24 associations (8 single-marker associations, 12 three-marker haplotype associations, and 4 cases of epistasis revealed by single-marker interactions). Fewer than 9 of these associations are likely to be false positives. Several associations were consistent with previous findings [Acp70A with the male's influence on the female's refractoriness to remating (refractory), Esterase-6 with a male's remating probability (remating) and a measure of female offspring production (fecundity)], but many are novel associations with uncharacterized seminal fluid proteins. Four genes showed evidence for pleiotropic effects [CG6168 with a measure of sperm competition (P2') and refractory, CG14560 with a defensive measure of sperm competition (P1') and a measure of female fecundity, Acp62F with P2' and a measure of female fecundity, and Esterase-6 with remating and a measure of female fecundity]. Our findings provide evidence that pleiotropy and epistasis are important factors in the genetic architecture of male reproductive success and show that haplotype analyses can identify associations missed in the single-marker approach.     

Comments on the Manhattan Stratigraphic Measure

The Manhattan stratigraphic measure was proposed as a measure of congruence between temporal information retrieved from the fossil record and a phylogenetic hypothesis. This index is based on the fit of a Sankoff character representing the stratigraphic ages of terminal taxa and is calculated in a way analogous to the consistency index. Sample cases are analyzed in which this measure is insensitive to increasing amounts of conflict between stratigraphic and topological temporal information. A simple modification of the step matrix upon which the measure is based is proposed. The modified index, MSM*, overcomes the observed problem and is based on the measurement of the number and extent of ghost lineages.     

Identification and characterization of E.coli ribosomal binding sites by free energy computation.

Sequences upstream from translational initiation sites of different E.coli genes show various degrees of complementarity to the Shine-Dalgarno (SD) sequence at the 3' end of the 16S rRNA. We propose a quantitative measure for the SD region on the mRNA, that reflects its degree of complementarity to the rRNA. This measure is based on the stability of the rRNA-mRNA duplex as established by free energy computations. The free energy calculations are based on the same principles that are used for folding a single RNA molecule, and are executed by similar algorithms. Bulges and internal loops in the rRNA and mRNA are allowed. The mRNA string with maximum free energy gain upon binding to the rRNA is selected as the most favorable SD sequence of a gene. The free energy value that represents the SD region provides a quantitative measure that can be used for comparing SD sequences of different genes. The distribution of this measure in more than 1000 E.coli genes is presented and discussed.     

Analysis of the code relating sequence to conformation in globular proteins. An informational analysis of the role of the residue in determining the conformation of its neighbours in the primary sequence

1. The effect exerted by a residue on the conformation of neighbouring residues was analysed by using data from nine globular proteins of known sequence and conformation. 2. An information measure was used which estimated the role of a residue in influencing neighbouring conformations and also its tendency to influence the lengths of runs of residues in that conformation. This measure was estimated for each residue in all conformations defined by domains on the varphi, psi diagram. 3. Plots of the information measure yielded an intercept, which was a measure of intra-residue information for a residue. The slope was a measure of the statistical co-operativity or tendency of the residue to influence the occurrence of its neighbours in runs of a particular conformation. Both parameters are a function of the residue type. Statistical co-operativity is found in the alpha(1)-helical (H(1)) and beta-pleated-sheet (P(2)) conformations and, to a lesser extent, in their distorted variants H(2) and P(1). 4. The directional nature of these influences for H(1) and P(2) conformations is illustrated by plots of the information measure against the distance m from the residue, for m=-10 to +10. 5. The results for statistical co-operativity are discussed in relation to theories of helix-coil and pleated-sheet-coil transitions. The value of the information-theory-derived parameters in obtaining s parameters for the Zimm & Bragg (1959) equations is illustrated. 6. Directional effects are discussed with particular relation to mechanisms of the termination of helices and the involvement of the alpha(II) conformation and also to discontinuities in pleated-sheet conformations.     

Three-dimensional spectral signal-to-noise ratio for a class of reconstruction algorithms

A three-dimensional (3D) version of the spectral signal-to-noise ratio (SSNR)-based resolution measure is introduced. The measure is defined for a class of 3D reconstruction algorithms that use interpolation in Fourier space. The statistical properties of the SSNR are discussed and related to the properties of another resolution measure, the Fourier shell correlation (FSC). The new measure was tested on 3D structures calculated from a simulated set of quasi-evenly spaced 2D projections using a nearest-neighbor interpolation and a gridding algorithm. In the latter case, the results agree very well with the FSC-based estimate, with the exception of very high SSNR values. The main applicability of the 3D SSNR is tomography, where due to the small number of projections collected, FSC cannot be used. The new measure was applied to three sets of tomographic data. It was demonstrated that the measure is sufficiently sensitive to yield theoretically expected results. Therefore, the 3D SSNR opens up the possibility of evaluating the quality of tomographic reconstructions in an objective manner. The 3D distribution of SSNR is of major interest in single-particle analysis. It is shown that the new measure can be used to evaluate the anisotropy of 3D reconstructions. The distribution of SSNR is characterized by three anisotropy indices derived from principal axes of the 3D inertia covariance matrix of the SSNR. These indices are used to construct a 3D Fourier filter which, when applied to a 3D reconstruction of a macromolecule, maximizes the SNR in real space and minimizes real-space artifacts caused by uneven distribution of 2D projections.     

Measures of association for identifying microRNA-mRNA pairs of biological interest

MicroRNAs are a class of small non-protein coding RNAs that play an important role in the regulation of gene expression. Most studies on the identification of microRNA-mRNA pairs utilize the correlation coefficient as a measure of association. The use of correlation coefficient is appropriate if the expression data are available for several conditions and, for a given condition, both microRNA and mRNA expression profiles are obtained from the same set of individuals. However, there are many instances where one of the requirements is not satisfied. Therefore, there is a need for new measures of association to identify the microRNA-mRNA pairs of interest and we present two such measures. The first measure requires expression data for multiple conditions but, for a given condition, the microRNA and mRNA expression may be obtained from different individuals. The new measure, unlike the correlation coefficient, is suitable for analyzing large data sets which are obtained by combining several independent studies on microRNAs and mRNAs. Our second measure is able to handle expression data that correspond to just two conditions but, for a given condition, the microRNA and mRNA expression must be obtained from the same set of individuals. This measure, unlike the correlation coefficient, is appropriate for analyzing data sets with a small number of conditions. We apply our new measures of association to multiple myeloma data sets, which cannot be analyzed using the correlation coefficient, and identify several microRNA-mRNA pairs involved in apoptosis and cell proliferation.     

Disturbance analysis of nonlinear differential equation models of genetic SUM regulatory networks

Noise disturbances and time delays are frequently met in cellular genetic regulatory systems. This paper is concerned with the disturbance analysis of a class of genetic regulatory networks described by nonlinear differential equation models. The mechanisms of genetic regulatory networks to amplify (attenuate) external disturbance are explored, and a simple measure of the amplification (attenuation) level is developed from a nonlinear robust control point of view. It should be noted that the conditions used to measure the disturbance level are delay-independent or delay-dependent, and are expressed within the framework of linear matrix inequalities, which can be characterized as convex optimization, and computed by the interior-point algorithm easily. Finally, by the proposed method, a numerical example is provided to illustrate how to measure the attenuation of proteins in the presence of external disturbances.     

SVDMAN--singular value decomposition analysis of microarray data

SUMMARY: We have developed two novel methods for Singular Value Decomposition analysis (SVD) of microarray data. The first is a threshold-based method for obtaining gene groups, and the second is a method for obtaining a measure of confidence in SVD analysis. Gene groups are obtained by identifying elements of the left singular vectors, or gene coefficient vectors, that are greater in magnitude than the threshold W N(-1/2), where N is the number of genes, and W is a weight factor whose default value is 3. The groups are non-exclusive and may contain genes of opposite (i.e. inversely correlated) regulatory response. The confidence measure is obtained by systematically deleting assays from the data set, interpolating the SVD of the reduced data set to reconstruct the missing assay, and calculating the Pearson correlation between the reconstructed assay and the original data. This confidence measure is applicable when each experimental assay corresponds to a value of parameter that can be interpolated, such as time, dose or concentration. Algorithms for the grouping method and the confidence measure are available in a software application called SVD Microarray ANalysis (SVDMAN). In addition to calculating the SVD for generic analysis, SVDMAN provides a new means for using microarray data to develop hypotheses for gene associations and provides a measure of confidence in the hypotheses, thus extending current SVD research in the area of global gene expression analysis.     

Incorporation of tumor shape into an assessment of spatial heterogeneity for human sarcomas imaged with FDG-PET

We have been exploring techniques for evaluation of fluoro-deoxyglucose (FDG) utilization characteristics in human sarcomas measured with positron emission tomography. In previous work, a measure of spatial heterogeneity based on evaluating the deviation of the FDG utilization distribution within the tumor region from a unimodal elliptically contoured spatial pattern was developed. This measure was shown to be a strong prognostic indicator of time to death. The present work explores a more general measure of heterogeneity which incorporates tumor boundary information. The approach relies on the use of a non-parametric representation for the tumor boundary surface. A set of 179 sarcoma patients with follow-up are evaluated with this technique. The results are analyzed to obtain empirical insight into the factors explaining elliptical heterogeneity. In terms of patient survival, the incorporation of the more sophisticated measure of spatial heterogeneity shows some potential improvement in the prediction risk. Further data will enable us to obtain a clearer empirical understanding of the role of the surface information in the measurement of tumor heterogeneity.     

The development of culturally-sensitive measures for research on ageing

Attempts to import existing measures developed in other countries when constructing research instruments for use with older people can result in several problems including inappropriate wording, unsuitable response sets, and insufficient attention to cultural nuances. This paper addresses such problems by discussing a mixed methods approach to measurement development (i.e. both qualitative and quantitative) that incorporates input from the aging adults for whom the measure is intended. To test this approach, a step-by step process to the development of a culturally-grounded measure for older Thai people is described. Using focus groups and in-depth interviews, the process begins with an identification of the culturally meaningful domains of the construct under study. Next, input is gathered from other studies; a preliminary quantitative measure is developed; the measure is reviewed by a panel of experts; and then it is pilot-tested. Cognitive interviews are utilized when pilot-testing of the items detects problems with measurement construction or interview methods. When these problems are remedied, the measure is incorporated into a large-scale survey and tested for its psychometric qualities. In addition to providing a template for culturally-sensitive measurement development in gerontology, this paper also highlights issues that researchers should consider when attempting to develop measures and provides suggestions for how to address such issues.