Virtual Environment for Next Generation Sequencing Analysis

Next Generation Sequencing technology, on the one hand, allows a more accurate analysis, and, on the other hand, increases the amount of data to process. A new protocol for sequencing the messenger RNA in a cell, known as RNA- Seq, generates millions of short sequence fragments in a single run. These fragments, or reads, can be used to measure levels of gene expression and to identify novel splice variants of genes. The proposed solution is a distributed architecture consisting of a Grid Environment and a Virtual Grid Environment, in order to reduce processing time by making the system scalable and flexibl

A Cloud Infrastructure for Optimization of a Massive Parallel Sequencing Workflow

Massive Parallel Sequencing is a term used to describe several revolutionary approaches to DNA sequencing, the so-called Next Generation Sequencing technologies. These technologies generate millions of short sequence fragments in a single run and can be used to measure levels of gene expression and to identify novel splice variants of genes allowing more accurate analysis. The proposed solution provides novelty on two fields, firstly an optimization of the read mapping algorithm has been designed, in order to parallelize processes, secondly an implementation of an architecture that consists of a Grid platform, composed of physical nodes, a Virtual platform, composed of virtual nodes set up on demand, and a scheduler that allows to integrate the two platform

Optimizing Splicing Junction Detection in Next Generation Sequencing Data on a Virtual-GRID Infrastructure

The new protocol for sequencing the messenger RNA in a cell, named RNA-seq produce millions of short sequence fragments. Next Generation Sequencing technology allows more accurate analysis but increase needs in term of computational resources. This paper describes the optimization of a RNA-seq analysis pipeline devoted to splicing variants detection, aimed at reducing computation time and providing a multi-user/multisample environment. This work brings two main contributions. First, we optimized a well-known algorithm called TopHat by parallelizing some sequential mapping steps. Second, we designed and implemented a hybrid virtual GRID infrastructure allowing to efficiently execute multiple instances of TopHat running on different samples or on behalf of different users, thus optimizing the overall execution time and enabling a flexible multi-user environmen

On the Unruh effect in de Sitter space

We give an interpretation of the temperature in de Sitter universe in terms of a dynamical Unruh effect associated with the Hubble sphere. As with the quantum noise perceived by a uniformly accelerated observer in static space-times, observers endowed with a proper motion can in principle detect the effect. In particular, we study a "Kodama observer" as a two-field Unruh detector for which we show the effect is approximately thermal. We also estimate the back-reaction of the emitted radiation and find trajectories associated with the Kodama vector fields are stable.Comment: 8 pages; corrected typos; sections structure revise

Better than bench top. High speed antioxidant screening via the cupric reducing antioxidant capacity reagent and reaction flow chromatography

This study is based upon a recently established method for quantification of the antioxidant capacity of natural samples via a HPLC separation and a hyphenated selective detection (post-column derivatization with cupric reducing antioxidant capacity reagent) technique. This protocol demonstrated the main improvements to transform the quantitative protocol into a high-speed qualitative automated assay to screen samples for their potential total antioxidant capacity, typically performed via manual mixing of the sample and derivatisation and measured on a 96 well plate reader/bench top UV–Vis spectrophotometer. This approach with automated mixing is a more informative alternative for total antioxidant capacity as the antioxidant peaks are profiled for each sample within four minutes. This antioxidant profile may be used for routine analysis of raw materials and/or a guide for targeted approaches for structure elucidation for laboratories interested in early drug discovery, natural product research and the search of alternative antioxidant additives in consumer goods/therapeutics. This technique could also be used to monitor the stability, alteration or adulteration of manufactured goods containing antioxidants.Fil: Suktham, Thirada. University of Western Sydney; AustraliaFil: Jones, Andrew. University of Western Sydney; AustraliaFil: Acquaviva, Agustín. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Química. Grupo Cromatografía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Dennis, Gary R.. University of Western Sydney; AustraliaFil: Shalliker, R. Andrew. University of Western Sydney; AustraliaFil: Soliven, Arianne. University of Western Sydney; Australia. Universidad de la República; Urugua

Virtual Environment for Next Generation Sequencing Analysis

Next Generation Sequencing technology, on the one hand, allows a more accurate analysis, and, on the other hand, increases the amount of data to process. A new protocol for sequencing the messenger RNA in a cell, known as RNA- Seq, generates millions of short sequence fragments in a single run. These fragments, or reads, can be used to measure levels of gene expression and to identify novel splice variants of genes. The proposed solution is a distributed architecture consisting of a Grid Environment and a Virtual Grid Environment, in order to reduce processing time by making the system scalable and flexibl

Optimizing Splicing Junction Detection in Next Generation Sequencing Data on a Virtual-GRID Infrastructure

The new protocol for sequencing the messenger RNA in a cell, named RNA-seq produce millions of short sequence fragments. Next Generation Sequencing technology allows more accurate analysis but increase needs in term of computational resources. This paper describes the optimization of a RNA-seq analysis pipeline devoted to splicing variants detection, aimed at reducing computation time and providing a multi-user/multisample environment. This work brings two main contributions. First, we optimized a well-known algorithm called TopHat by parallelizing some sequential mapping steps. Second, we designed and implemented a hybrid virtual GRID infrastructure allowing to efficiently execute multiple instances of TopHat running on different samples or on behalf of different users, thus optimizing the overall execution time and enabling a flexible multi-user environment