ArticleBriefings in bioinformatics2024
NIGMS Sandbox: a learning platform toward democratizing cloud computing for biomedical research.
Article in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Artificial intelligence for comprehensive DNA methylation analysis: overview, challenges, and future directions.Briefings in bioinformatics · 2025Review
- CloudATAC: a cloud-based framework for ATAC-Seq data analysis.Briefings in bioinformatics · 2024Article
- Cloud-based introduction to BASH programming for biologists.Briefings in bioinformatics · 2024Article
- CCPA: cloud-based, self-learning modules for consensus pathway analysis using GO, KEGG and Reactome.Briefings in bioinformatics · 2024Article
- Transcriptomics and epigenetic data integration learning module on Google Cloud.Briefings in bioinformatics · 2024Article
- Whole-genome bisulfite sequencing data analysis learning module on Google Cloud Platform.Briefings in bioinformatics · 2024Article
- A cloud-based learning module for biomarker discovery.Briefings in bioinformatics · 2024Article
- Identifying and training deep learning neural networks on biomedical-related datasets.Briefings in bioinformatics · 2024Article
- Understanding proteome quantification in an interactive learning module on Google Cloud Platform.Briefings in bioinformatics · 2024Article
- Reusable tutorials for using cloud-based computing environments for the analysis of bacterial gene expression data from bulk RNA sequencing.Briefings in bioinformatics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Biomedical data are growing exponentially in both volume and levels of complexity, due to the rapid advancement of technologies and research methodologies. Analyzing these large datasets, referred to collectively as "big data," has become an integral component of research that guides experimentation-driven discovery and a new engine of discovery itself as it uncovers previously unknown connections through mining of existing data. To fully realize the potential of big data, biomedical researchers need access to high-performance-computing (HPC) resources. However, supporting on-premises infrastructure that keeps up with these consistently expanding research needs presents persistent financial and staffing challenges, even for well-resourced institutions. For other institutions, including primarily undergraduate institutions and minority serving institutions, that educate a large portion of the future workforce in the USA, this challenge presents an insurmountable barrier. Therefore, new approaches are needed to provide broad and equitable access to HPC resources to biomedical researchers and students who will advance biomedical research in the future.
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.