Cloud computing: Applications in biological research and future prospects

2012 ◽  
Author(s):  
Kiran Menon ◽  
Kamalapriya Anala ◽  
S.D. Gokhale Trupti ◽  
Neeru Sood
Keyword(s):  
Cloud Computing ◽  
Biological Research ◽  
Future Prospects

A Review of Cloud Computing Bioinformatics Solutions for Next-Gen Sequencing Data Analysis and Research

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Konstantinos Krampis ◽  
Claudia Wultsch
Keyword(s):  
Cloud Computing ◽  
Data Analysis ◽  
Large Scale ◽  
Storage Capacity ◽  
Biological Research ◽  
Sequencing Data ◽  
Computing Services ◽  
Informatics Infrastructure ◽  
And Storage ◽  
Sequencing Data Analysis

Abstract Research in biology has entered a digital era, where next-generation sequencing instruments generate multiple terabytes of data but are equipped with minimal computational and storage capacity that is not sufficient for large-scale, post-sequencing data analysis. Therefore, scientific value cannot be obtained from investment in a sequencing instrument, unless it is also combined with a significant expense for informatics infrastructure. An alternative option for laboratories is to outsource their informatics infrastructure, by leasing computational cycles and storage capacity from cloud computing services. Development of cloud-based bioinformatics tool suites can provide users with access to pre-configured software and on-demand computing resources for genomic data analysis, while at the same time lower the barrier for working with sequencing datasets, leading to broader adoption of genomic technologies for basic biological research. We conclude that along with the democratization of genome sequencing through the availability of lowcost, bench-top sequencers, cloud computing can in turn democratize access to computational capacity and informatics infrastructures required for sequencing data analysis.

Trust and Reliability Management in Large-Scale Cloud Computing Environments

2021 ◽  
pp. 66-89
Author(s):  
Punit Gupta
Keyword(s):  
Cloud Computing ◽  
Trust Management ◽  
Large Scale ◽  
Cloud Environment ◽  
Future Prospects ◽  
Distributed Environment ◽  
Reliability Management ◽  
Trust Models ◽  
Management Techniques ◽  
Computing Environments

Trust is a firm belief over a person or a thing in distributed environment based on its feedback on review based on its performance by others. Similarly, in cloud, trust models play an important role in solving various open challenges in cloud environment. This chapter showcases all such issues that can be solved by trust management techniques. This work discourses various trust management models and its categorization. The work discourses existing work using trust models from the field of grid computing, cloud computing, and web services because all these domains are sub child of each other. The work provides an abstract view over all trust models and find the suitable one for cloud and its future prospects.

Experimental Determination of the Effective Resolution Limit in Thick Specimens at High Voltages

1975 ◽  
Vol 33 ◽  
pp. 664-665
Author(s):  
Mircea Fotino
Keyword(s):  
Experimental Approach ◽  
Chromatic Aberration ◽  
Resolving Power ◽  
Biological Research ◽  
Specimen Thickness ◽  
Resolution Limit ◽  
High Voltage Electron Microscopy ◽  
Voltage Electron ◽  
Resolution Level

The use of thick specimens (0.5 μm to 5.0 μm or more) is one of the most resourceful applications of high-voltage electron microscopy in biological research. However, the energy loss experienced by the electron beam in the specimen results in chromatic aberration and thus in a deterioration of the effective resolving power. This sets a limit to the maximum usable specimen thickness when investigating structures requiring a certain resolution level.An experimental approach is here described in which the deterioration of the resolving power as a function of specimen thickness is determined. In a manner similar to the Rayleigh criterion in which two image points are considered resolved at the resolution limit when their profiles overlap such that the minimum of one coincides with the maximum of the other, the resolution attainable in thick sections can be measured by the distance from minimum to maximum (or, equivalently, from 10% to 90% maximum) of the broadened profile of a well-defined step-like object placed on the specimen.

Some problems and solutions in electron energy loss spectroscopy of cryosections

1993 ◽  
Vol 51 ◽  
pp. 566-567
Author(s):  
Zhifeng Shao ◽  
Ruoya Ho ◽  
Andrew P. Somlyo
Keyword(s):  
High Resolution ◽  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
Biological Research ◽  
Specimen Thickness ◽  
Elemental Distribution ◽  
Electron Dose ◽  
Simple Assumption ◽  
Electron Energy Loss

Electron energy loss spectroscopy (EELS) has been a powerful tool for high resolution studies of elemental distribution, as well as electronic structure, in thin samples. Its foundation for biological research has been laid out nearly two decades ago, and in the subsequent years it has been subjected to rigorous, but by no means extensive research. In particular, some problems unique to EELS of biological samples, have not been fully resolved. In this article we present a brief summary of recent methodological developments, related to biological applications of EELS, in our laboratory. The main purpose of this work was to maximize the signal to noise ratio (S/N) for trace elemental analysis at a minimum dose, in order to reduce the electron dose and/or time required for the acquisition of high resolution elemental maps of radiation sensitive biological materials.Based on the simple assumption of Poisson distribution of independently scattered electrons, it had been generally assumed that the optimum specimen thickness, at which the S/N is a maximum, must be the total inelastic mean free path of the beam electron in the sample.

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