Add to ORKGComputational biology applications typically favor a local, cluster-based, integrated computational platform. We present a lessons learned report for scaling up a metagenomics application that had outgrown the available local cluster hardware.. In our example, removing a number of assumptions linked to tight integration allowed us to expand beyond one administrative domain, increase the number and type of machines available for the application, and improve the scaling properties of the application. The assumptions made in designing the computational client make it well suited for deployment as a virtual machine inside a cloud. This paper discusses the decision process and describes the suitability of deploying various bioinformatics computa...
High-throughput experiments enable researchers to explore complex multifactorial diseases through la...
With the continued exponential expansion of publicly available genomic data and access to low-cost, ...
The widespread popularity of genomic applications is threatened by the "bioinformatics bottleneck" r...
Abstract—Cutting-edge sequencing systems produce data at a prodigious rate; and the analysis of thes...
In this paper, we explore the benefits of automatically determining the degree of parallelism used t...
BACKGROUND: Analyzing high throughput genomics data is a complex and compute intensive task, general...
Genomic data analysis in evolutionary biology is becoming so computationally intensive that analysis...
Analyzing high throughput genomics data is a complex and compute intensive task, generally requiring...
The increasing availability and decreasing cost of high-throughput sequencing has transformed academ...
Cloud-based service computing has started to change the way how research in science, in particular b...
Ever since high-throughput DNA sequencing became economically feasible, the amount of biological dat...
Background As large genomics and phenotypic datasets are becoming more common, it is increasingly di...
Recently, research processes in Life sciences have evolved at a rapid pace. This evolution, mainly d...
Next-generation sequencing (NGS) technologies have made it possible to rapidly sequence the human ge...
As part of the Cambrian explosion of omics data, metagenomics brings to the table a specific, defini...
High-throughput experiments enable researchers to explore complex multifactorial diseases through la...
With the continued exponential expansion of publicly available genomic data and access to low-cost, ...
The widespread popularity of genomic applications is threatened by the "bioinformatics bottleneck" r...
Abstract—Cutting-edge sequencing systems produce data at a prodigious rate; and the analysis of thes...
In this paper, we explore the benefits of automatically determining the degree of parallelism used t...
BACKGROUND: Analyzing high throughput genomics data is a complex and compute intensive task, general...
Genomic data analysis in evolutionary biology is becoming so computationally intensive that analysis...
Analyzing high throughput genomics data is a complex and compute intensive task, generally requiring...
The increasing availability and decreasing cost of high-throughput sequencing has transformed academ...
Cloud-based service computing has started to change the way how research in science, in particular b...
Ever since high-throughput DNA sequencing became economically feasible, the amount of biological dat...
Background As large genomics and phenotypic datasets are becoming more common, it is increasingly di...
Recently, research processes in Life sciences have evolved at a rapid pace. This evolution, mainly d...
Next-generation sequencing (NGS) technologies have made it possible to rapidly sequence the human ge...
As part of the Cambrian explosion of omics data, metagenomics brings to the table a specific, defini...
High-throughput experiments enable researchers to explore complex multifactorial diseases through la...
With the continued exponential expansion of publicly available genomic data and access to low-cost, ...
The widespread popularity of genomic applications is threatened by the "bioinformatics bottleneck" r...