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Hubs are ubiquitous network elements with high connectivity. One of the common observations about hub proteins is their preferential attachment leading to scale-free network topology. Here we examine the question: does rich protein always get richer, or can it get poor too? To answer this question, we compared similar and well-annotated hub proteins in six(More)
SUMMARY Analysis of high throughput metabolomics experiments is a resource-intensive process that includes pre-processing, pre-treatment and post-processing at each level of experimental hierarchy. We developed an interactive user-friendly online software called Metabolite Data Analysis Tool (MetDAT) for mass spectrometry data. It offers a pipeline of tools(More)
The aim of metabolomics is to identify, measure, and interpret complex time-related concentration, activity, and flux of metabolites in cells, tissues, and biofluids. We have used a metabolomics approach to study the biochemical phenotype of mammalian cells which will help in the development of a panel of early stage biomarkers of heat stress tolerance and(More)
SUMMARY Data processing, analysis and visualization (datPAV) is an exploratory tool that allows experimentalist to quickly assess the general characteristics of the data. This platform-independent software is designed as a generic tool to process and visualize data matrices. This tool explores organization of the data, detect errors and support basic(More)
Multivariate calibration problems often involve the identification of a meaningful subset of variables, from a vast number of variables for better prediction of output variables. A new graph theoretic method based on partial correlations (variable interaction network-VIN) is proposed. Many well studied representative calibration datasets spanning different(More)
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