7733753
A geometric approach to determine association and coherence of the activation times of cell-cycling genes under differing experimental conditions
Differing arresting agents and protocols can be used to synchronize cells in cultures to specific phases of the cell when studying cell-cycle gene expressions. Often, data derived from individual experiments are analyzed separately, since no appropriate statistical methodology is available at the moment to analyze the data from all such experiments simultaneously. The focus of this paper is to determine the association and coherence of the relative activation times of cell-cycling genes under different experimental conditions. Using a circular-circular regression model, we define two parameters, a rotation parameter for the angular difference between cells' arresting times (phases) in two cell-cycle experiments, and an association parameter to describe the correspondence between the cycle times of maximal expression (phase angles) for a set of genes studied in two experiments. Further, we propose a procedure to assess coherence across multiple experiments, i.e. to what extent the circular ordering of the phase angles of genes is maintained across multiple experiments. Coherence of genes across experiments suggests that functionally these genes tend to respond in a stereotypically sequenced way under different experimental conditions. Our proposed methodology is illustrated by applying it to a HeLa cell-cycle gene-expression data.
18721223
Phase analysis of circadian-related genes in two tissues
BackgroundRecent circadian clock studies using gene expression microarray in two different tissues of mouse have revealed not all circadian-related genes are synchronized in phase or peak expression times across tissues in vivo. Instead, some circadian-related genes may be delayed by 4–8 hrs in peak expression in one tissue relative to the other. These interesting biological observations prompt a statistical question regarding how to distinguish the synchronized genes from genes that are systematically lagged in phase/peak expression time across two tissues.ResultsWe propose a set of techniques from circular statistics to analyze phase angles of circadian-related genes in two tissues. We first estimate the phases of a cycling gene separately in each tissue, which are then used to estimate the paired angular difference of the phase angles of the gene in the two tissues. These differences are modeled as a mixture of two von Mises distributions which enables us to cluster genes into two groups; one group having synchronized transcripts with the same phase in the two tissues, the other containing transcripts with a discrepancy in phase between the two tissues. For each cluster of genes we assess the association of phases across the tissue types using circular-circular regression. We also develop a bootstrap methodology based on a circular-circular regression model to evaluate the improvement in fit provided by allowing two components versus a one-component von-Mises model.ConclusionWe applied our proposed methodologies to the circadian-related genes common to heart and liver tissues in Storch et al. [2], and found that an estimated 80% of circadian-related transcripts common to heart and liver tissues were synchronized in phase, and the other 20% of transcripts were lagged about 8 hours in liver relative to heart. The bootstrap p-value for being one cluster is 0.063, which suggests the possibility of two clusters. Our methodologies can be extended to analyze peak expression times of circadian-related genes across more than two tissues, for example, kidney, heart, liver, and the suprachiasmatic nuclei (SCN) of the hypothalamus.
6586245
Reconstructing XML Subtrees from Relational Storage of XML documents
Numerous researchers have proposed to use relational databases to store and query XML documents. One important component of such systems is the XML subtree reconstruction, which reconstructs the subtrees rooted at the matching nodes of an XML query and returns them to the user as the query result. Existing reconstruction algorithms either do not support recursive XML view schema, or require expensive nested queries or joins of multiple relations. In this paper, we propose an efficient XML subtree reconstruction algorithm, Reconstruct, which overcomes these limitations and uses an efficient stack-based structural join algorithm to recover all the parent-child relationships between elements. One salient advantage of this algorithm is that it employs the inlining feature of the inlining-based storage of XML documents, which is known as one of the best relational XML storage schemes. Both our algorithmic analysis and experimental study show that Reconstruct is efficient and scalable.
36089150
Hamiltonicity and circular distance two labellings
Abstract A k -circular distance two labelling (or k -c-labelling) of a graph G is a vertex-labelling such that the circular difference ( mod k ) of the labels is at least two for adjacent vertices, and at least one for vertices at distance two. Given G , denote σ(G) the minimum k for which there exists a k -c-labelling of G . Suppose G has n vertices, we prove σ(G)⩽n if G c is Hamiltonian; and σ(G)=n+p v (G c ) otherwise, where p v (G) is the path covering number of G . We give exact values of σ(G) for some families of graphs such that G c is Hamiltonian, and discuss injective k -c-labellings especially for joins and unions of graphs.
7771298
Robust stability of a class of nonlinear time-varying discrete systems
This paper studies the problem of robust absolute stability of a class of nonlinear discrete-time systems with time-varying matrix uncertainties of polyhedral type and multiple time-varying sector nonlinearities. By using the variational method and the Lyapunov Second Method, criteria for robust absolute stability are obtained in different forms for the given class of systems. Specifically, we determine the parametric class of Lyapunov functions which defines the necessary and sufficient conditions of robust absolute stability. We apply these Lyapunov functions to derive an algebraic criterion for robust absolute stability in the form of solvability conditions of a set of matrix equations.
10993158
Efficient and Distributed Access Control for Sensor Networks
Sensor networks are often used to sense the physical world and provide observations for various uses. In hostile environments, it is critical to control the network access to ensure the integrity, availability, and at times confidentiality of the sensor data. This paper develops efficient methods for distributed access control in sensor networks. The paper starts with a baseline approach, which provides a more flexible and efficient way to enforce access control when compared with previous solutions. This paper then extends the baseline approach to enable privilege delegation, which allows a user to delegate its privilege to other users without using a trusted server, and broadcast query, which allows a user to access the network at a large scale efficiently. The privilege delegation and broadcast query are very useful in practice; none of the current solutions can achieve these two properties.
163750
Query Decomposition: A Multiple Neighborhood Approach to Relevance Feedback Processing in Content-based Image Retrieval
Today’s Content-Based Image Retrieval (CBIR) techniques are based on the "k-nearest neighbors" (k- NN) model. They retrieve images from a single neighborhood using low-level visual features. In this model, semantically similar images are assumed to be clustered in the high-dimensional feature space. Unfortunately, no visual-based feature vector is sufficient to facilitate perfect semantic clustering; and semantically similar images with different appearances are always clustered into distinct neighborhoods in the feature space. Confinement of the search results to a single neighborhood is an inherent limitation of the k-NN techniques. In this paper we consider a new image retrieval paradigm — the Query Decomposition model - that facilitates retrieval of semantically similar images from multiple neighborhoods in the feature space. The retrieval results are the k most similar images from different relevant clusters. We introduce a prototype, and present experimental results to illustrate the effectiveness and efficiency of this new approach to content-based image retrieval.