The Bak-Sneppen Model on Scale-Free Networks

We investigate by numerical simulations and analytical calculations the Bak-Sneppen model for biological evolution in scale-free networks. By using large scale numerical simulations, we study the avalanche size distribution and the activity time behavior at nodes with different connectivities. We argue the absence of a critical barrier and its associated critical behavior for infinite size systems. These findings are supported by a single site mean-field analytic treatment of the model.Comment: 5 pages and 3 eps figures. Final version appeared in Europhys. Let

Intermittent exploration on a scale-free network

We study an intermittent random walk on a random network of scale-free degree distribution. The walk is a combination of simple random walks of duration $t_w$ and random long-range jumps. While the time the walker needs to cover all the nodes increases with $t_w$, the corresponding time for the edges displays a non monotonic behavior with a minimum for some nontrivial value of $t_w$. This is a heterogeneity-induced effect that is not observed in homogeneous small-world networks. The optimal $t_w$ increases with the degree of assortativity in the network. Depending on the nature of degree correlations and the elapsed time the walker finds an over/under-estimate of the degree distribution exponent.Comment: 12 pages, 3 figures, 1 table, published versio

Multi-population GWA mapping via multi-task regularized regression

Motivation: Population heterogeneity through admixing of different founder populations can produce spurious associations in genome- wide association studies that are linked to the population structure rather than the phenotype. Since samples from the same population generally co-evolve, different populations may or may not share the same genetic underpinnings for the seemingly common phenotype. Our goal is to develop a unified framework for detecting causal genetic markers through a joint association analysis of multiple populations

Automatic Annotation of Spatial Expression Patterns via Sparse Bayesian Factor Models

Advances in reporters for gene expression have made it possible to document and quantify expression patterns in 2D–4D. In contrast to microarrays, which provide data for many genes but averaged and/or at low resolution, images reveal the high spatial dynamics of gene expression. Developing computational methods to compare, annotate, and model gene expression based on images is imperative, considering that available data are rapidly increasing. We have developed a sparse Bayesian factor analysis model in which the observed expression diversity of among a large set of high-dimensional images is modeled by a small number of hidden common factors. We apply this approach on embryonic expression patterns from a Drosophila RNA in situ image database, and show that the automatically inferred factors provide for a meaningful decomposition and represent common co-regulation or biological functions. The low-dimensional set of factor mixing weights is further used as features by a classifier to annotate expression patterns with functional categories. On human-curated annotations, our sparse approach reaches similar or better classification of expression patterns at different developmental stages, when compared to other automatic image annotation methods using thousands of hard-to-interpret features. Our study therefore outlines a general framework for large microscopy data sets, in which both the generative model itself, as well as its application for analysis tasks such as automated annotation, can provide insight into biological questions

HEMORHEOLOGICAL CHANGES AT MENOPAUSE

Hemorheological profile of a group of menopausal female subjects have been studied. Parameters such as whole blood viscosity, plasma viscosity, hematocrit, red cell rigidity and biochemical values such as plasma fibrinogen, proteins are evaluated. Females in premenopausal phase are taken as controls. Menopausal women showed significantly high whole blood viscosity, plasma viscosity and red cell rigidity. There was no significant rise in hematocrit and plasma fibrinogen. The results suggest that the menopausal phase plays important role in altering the rheology of blood. This change in rheology can be a potential risk factor in the development of ischaemic heart diseases

PLATINUM(II) COMPLEXES OF N,N'-DICYCLOPENTYLETHYLENEDIAMINE

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Platinum(II) Complexes of N,N' – Dicyclopentylethylenediamine

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