ArticlePLoS computational biology2011
Biomedical cloud computing with Amazon Web Services.
Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
44 citing papers in PubMed.
- MS-PyCloud: A Cloud Computing-Based Pipeline for Proteomic and Glycoproteomic Data Analyses.Analytical chemistry · 2024Article
- Article
- Evaluation of Circulating MicroRNAs and Adipokines in Breast Cancer Survivors with Arm Lymphedema.International journal of molecular sciences · 2022Article
- Immunophenotyping assessment in a COVID-19 cohort (IMPACC): A prospective longitudinal study.Science immunology · 2021Article
- Prolonged hospital length of stay in pediatric trauma: a model for targeted interventions.Pediatric research · 2021Article
- Cloud Computing Enabled Big Multi-Omics Data Analytics.Bioinformatics and biology insights · 2021Review
- HealtheDataLab - a cloud computing solution for data science and advanced analytics in healthcare with application to predicting multi-center pediatric readmissions.BMC medical informatics and decision making · 2020Article
- Cloud computing applications for biomedical science: A perspective.PLoS computational biology · 2018Article
- Development of a Cloud Computing-Based Pier Type Port Structure Stability Evaluation Platform Using Fiber Bragg Grating Sensors.Sensors (Basel, Switzerland) · 2018Article
- Eleven quick tips for architecting biomedical informatics workflows with cloud computing.PLoS computational biology · 2018Article
- A new paradigm for the scientific enterprise: nurturing the ecosystem.F1000Research · 2018Article
- Big Data Analytics for Genomic Medicine.International journal of molecular sciences · 2017Review
- MC-GenomeKey: a multicloud system for the detection and annotation of genomic variants.BMC bioinformatics · 2017Article
- Automating NEURON Simulation Deployment in Cloud Resources.Neuroinformatics · 2017Article
- Running Neuroimaging Applications on Amazon Web Services: How, When, and at What Cost?Frontiers in neuroinformatics · 2017Article
- A cloud-based workflow to quantify transcript-expression levels in public cancer compendia.Scientific reports · 2016Article
- A Primer on Infectious Disease Bacterial Genomics.Clinical microbiology reviews · 2016Review
- Novel bioinformatic developments for exome sequencing.Human genetics · 2016Review
- cl-dash: rapid configuration and deployment of Hadoop clusters for bioinformatics research in the cloud.Bioinformatics (Oxford, England) · 2016Article
- Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform.BMC bioinformatics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
In this overview to biomedical computing in the cloud, we discussed two primary ways to use the cloud (a single instance or cluster), provided a detailed example using NGS mapping, and highlighted the associated costs. While many users new to the cloud may assume that entry is as straightforward as uploading an application and selecting an instance type and storage options, we illustrated that there is substantial up-front effort required before an application can make full use of the cloud's vast resources. Our intention was to provide a set of best practices and to illustrate how those apply to a typical application pipeline for biomedical informatics, but also general enough for extrapolation to other types of computational problems. Our mapping example was intended to illustrate how to develop a scalable project and not to compare and contrast alignment algorithms for read mapping and genome assembly. Indeed, with a newer aligner such as Bowtie, it is possible to map the entire African genome using one m2.2xlarge instance in 48 hours for a total cost of approximately $48 in computation time. In our example, we were not concerned with data transfer rates, which are heavily influenced by the amount of available bandwidth, connection latency, and network availability. When transferring large amounts of data to the cloud, bandwidth limitations can be a major bottleneck, and in some cases it is more efficient to simply mail a storage device containing the data to AWS (http://aws.amazon.com/importexport/). More information about cloud computing, detailed cost analysis, and security can be found in references.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.