ReviewBioMed research international2013
Translational biomedical informatics in the cloud: present and future.
Review in BioMed research international, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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
23 citing papers in PubMed.
- Will it run?-A proof of concept for smoke testing decentralized data analytics experiments.Frontiers in medicine · 2023Article
- A Review of the Role and Challenges of Big Data in Healthcare Informatics and Analytics.Computational intelligence and neuroscience · 2022Review
- Health Informatics: Engaging Modern Healthcare Units: A Brief Overview.Frontiers in public health · 2022Review
- Data-driven translational prostate cancer research: from biomarker discovery to clinical decision.Journal of translational medicine · 2020Review
- Towards a European health research and innovation cloud (HRIC).Genome medicine · 2020Article
- Translational Informatics for Parkinson's Disease: from Big Biomedical Data to Small Actionable Alterations.Genomics, proteomics & bioinformatics · 2019Review
- Preference of cancer patients and family members regarding delivery of bad news and differences in clinical practice among medical staff.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2019Article
- Data-driving methods: More than merely trendy buzzwords?Annals of intensive care · 2018Review
- Parallel MapReduce: Maximizing Cloud Resource Utilization and Performance Improvement Using Parallel Execution Strategies.BioMed research international · 2018Article
- Making sense of big data in health research: Towards an EU action plan.Genome medicine · 2016Article
- Big Data Application in Biomedical Research and Health Care: A Literature Review.Biomedical informatics insights · 2016Review
- Blood-borne biomarkers and bioindicators for linking exposure to health effects in environmental health science.Journal of toxicology and environmental health. Part B, Critical reviews · 2016Review
- From Molecules to Patients: The Clinical Applications of Translational Bioinformatics.Yearbook of medical informatics · 2015Article
- New bioinformatic tool for quick identification of functionally relevant endogenous retroviral inserts in human genome.Cell cycle (Georgetown, Tex.) · 2015Article
- Toward a Literature-Driven Definition of Big Data in Healthcare.BioMed research international · 2015Review
- High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis.Genes · 2014Article
- Genomic sequencing: assessing the health care system, policy, and big-data implications.Health affairs (Project Hope) · 2014Article
- Identification of candidate miRNA biomarkers from miRNA regulatory network with application to prostate cancer.Journal of translational medicine · 2014Article
- A novel feature selection strategy for enhanced biomedical event extraction using the Turku system.BioMed research international · 2014Article
- Stem cell systems informatics for advanced clinical biodiagnostics: tracing molecular signatures from bench to bedside.Croatian medical journal · 2013Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Next generation sequencing and other high-throughput experimental techniques of recent decades have driven the exponential growth in publicly available molecular and clinical data. This information explosion has prepared the ground for the development of translational bioinformatics. The scale and dimensionality of data, however, pose obvious challenges in data mining, storage, and integration. In this paper we demonstrated the utility and promise of cloud computing for tackling the big data problems. We also outline our vision that cloud computing could be an enabling tool to facilitate translational bioinformatics research.
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.