A Genome-Scale Metabolic Reconstruction of Mycoplasma genitalium, iPS189

With a genome size of ∼580 kb and approximately 480 protein coding regions, Mycoplasma genitalium is one of the smallest known self-replicating organisms and, additionally, has extremely fastidious nutrient requirements. The reduced genomic content of M. genitalium has led researchers to suggest that the molecular assembly contained in this organism may be a close approximation to the minimal set of genes required for bacterial growth. Here, we introduce a systematic approach for the construction and curation of a genome-scale in silico metabolic model for M. genitalium. Key challenges included estimation of biomass composition, handling of enzymes with broad specificities, and the lack of a defined medium. Computational tools were subsequently employed to identify and resolve connectivity gaps in the model as well as growth prediction inconsistencies with gene essentiality experimental data. The curated model, M. genitalium iPS189 (262 reactions, 274 metabolites), is 87% accurate in recapitulating in vivo gene essentiality results for M. genitalium. Approaches and tools described herein provide a roadmap for the automated construction of in silico metabolic models of other organisms

Social Network Analysis of the Short Message Service

Abstract—In this paper, we analyze patterns in the Short Message Service (SMS) behavior of customers in a large telecom service provider network. Toward this, we construct SMS Graphs, which are graphs induced by people exchanging SMSs, from the SMS Call Detail Records of the concerned service provider. These patterns are modeled by a weighted graph G(V, E, W), in which the vertices represent the customers, and the edges and weights characterize the SMS transactions. We analyze properties of this graph, such as the distribution of component sizes, cliques, and vertex degrees. It is our belief that this study should enable the telecom operators to utilize the social behavior of their customers to design better service plans, and generate optimum incentives

Radiological Risk Assessment due to Radon and Thoron in the Dwellings of Peddamula Village, Nalgonda District, Telangana, India

467-471Radon and thoron are significant contributors for radiological risk in indoors and are originating from decay chain of uranium and thorium, which are prevalent in the environment. These concentrations in indoors depends on the presence of uranium and thorium concentration, and lifestyle of the habitants. The village “Peddamula” is located in the neighbourhood area of proposed mining for exploration of uranium. The estimated concentration of radon and thoron is found in the range 14- 448 Bq.m-3 with an average value of 120 ± 82 Bq.m-3 (GM 100Bq.m-3), and vary from 7 to 452 Bq.m-3with an average value of 154 ± 111 Bq.m-3 (GM 112Bq.m-3), respectively. Computed the contribution to the effective dose per annum from, radon 3.02 mSv.y-1 and thoron is 4.32mSv.y-1. In this paper the seasonal variation and distribution of 222Rn and 220Rn levels in the dwellings of the study area will be discussed

An Adaptive Irregularly Spaced Fourier Method for

In this paper we introduce a grid free irregularly sampled Fourier approach for accurately predicting rigid body protein-protein docking sites. Of the many docking approaches, grid based Fast Fourier Transform (FFT) approaches have been shown to produce by far the fastest, correlation profiles of complex protein-protein interactions over the six dimensional search space. However, these uniform sampling methods still possess high time complexity, and in particular, are highly memory intensive for predicting large protein-protein docking sites. By taking advantage of an irregularly and adaptively sampled, smooth particle representation of molecular shape, in combination with the use of irregularly spaced FFT transforms, we eliminate an explicit uniform grid. We are able to produce efficiently, highly compressed, but accurate, docking correlation profiles