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BACKGROUND The landscape of biological and biomedical research is being changed rapidly with the invention of microarrays which enables simultaneous view on the transcription levels of a huge number of genes across different experimental conditions or time points. Using microarray data sets, clustering algorithms have been actively utilized in order to(More)
We demonstrate the effect of consumers' lay theories of self-control on goal-directed behavior as evidenced by New Year's and other resolutions. Across three studies, we find that individuals who believe that self-control is a malleable but inherently limited (vs. unlimited) resource tend to set fewer resolutions. Using respondents' own idiographic(More)
This research examines how the visual perspectives that people take to appraise an event, that is, whether they view themselves as actors in the situation or observers of it, influence the intensities of the emotions they experience. We predict that in a situation that elicits emotions, greater attention to the self (if using an observer's perspective)(More)
MOTIVATION Recent advancements in microarray technology allows simultaneous monitoring of the expression levels of a large number of genes over different time points. Clustering is an important tool for analyzing such microarray data, typical properties of which are its inherent uncertainty, noise and imprecision. In this article, a two-stage clustering(More)
—An important approach for unsupervised landcover classification in remote sensing images is the clustering of pixels in the spectral domain into several fuzzy partitions. In this paper, a multiobjective optimization algorithm is utilized to tackle the problem of fuzzy partitioning where a number of fuzzy cluster validity indexes are simultaneously(More)
With the advancement of microarray technology, it is now possible to study the expression profiles of thousands of genes across different experimental conditions or tissue samples simultaneously. Microarray cancer datasets, organized as samples versus genes fashion, are being used for classification of tissue samples into benign and malignant or their(More)
Protein-protein interaction network-based study of viral pathogenesis has been gaining popularity among computational biologists in recent days. In the present study we attempt to investigate the possible pathways of hepatitis-C virus (HCV) infection by integrating the HCV-human interaction network, human protein interactome and human genetic disease(More)
—The problem of unsupervised classification of a satellite image in a number of homogeneous regions can be viewed as the task of clustering the pixels in the intensity space. This paper proposes a novel approach that combines a recently proposed mul-tiobjective fuzzy clustering scheme with support vector machine (SVM) classifier to yield improved solutions.(More)
Biclustering methods are used to identify a subset of genes that are co-regulated in a subset of experimental conditions in microarray gene expression data. Many biclustering algorithms rely on optimizing mean squared residue to discover biclusters from a gene expression dataset. Recently it has been proved that mean squared residue is only good in(More)
Consumers often search the Internet for agent advice when making decisions about products and services. Existing research on this topic suggests that past opinion agreement between the consumer and an agent is an important cue in consumers' acceptance of current agent advice. In this article, we report the results of two experiments which show that(More)