ArticleJournal of the American Medical Informatics Association : JAMIA2015
Big biomedical data as the key resource for discovery science.
Article in Journal of the American Medical Informatics Association : JAMIA, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 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
34 citing papers in PubMed.
- Translational bioinformatics and data science for biomarker discovery in mental health: an analytical review.Briefings in bioinformatics · 2024Review
- Predicting the Recurrence of Common Bile Duct Stones After ERCP Treatment with Automated Machine Learning Algorithms.Digestive diseases and sciences · 2023Article
- Neuroimaging PheWAS (Phenome-Wide Association Study): A Free Cloud-Computing Platform for Big-Data, Brain-Wide Imaging Association Studies.Neuroinformatics · 2021Article
- Identification of Liver Cancer Stem Cell Stemness Markers Using a Comparative Analysis of Public Data Sets.Stem cells and cloning : advances and applications · 2021Article
- Systemic Fairness for Sharing Health Data: Perspectives From Swiss Stakeholders.Frontiers in public health · 2021Article
- Thought Leader Comparisons of Risks in Precision Medicine Research.Ethics & human research · 2020Article
- Restructured society and environment: A review on potential technological strategies to control the COVID-19 pandemic.The Science of the total environment · 2020Review
- Imputation Strategy for Reliable Regional MRI Morphological Measurements.Neuroinformatics · 2020Article
- Functional Neuroimaging in the New Era of Big Data.Genomics, proteomics & bioinformatics · 2019Review
- Data and knowledge management in translational research: implementation of the eTRIKS platform for the IMI OncoTrack consortium.BMC bioinformatics · 2019Article
- Personalized medicine in breast cancer: pharmacogenomics approaches.Pharmacogenomics and personalized medicine · 2019Review
- Article
- The role of ethics in data governance of large neuro-ICT projects.Journal of the American Medical Informatics Association : JAMIA · 2018Review
- Neuroanatomical morphometric characterization of sex differences in youth using statistical learning.NeuroImage · 2018Article
- Highly Reproducible Automated Proteomics Sample Preparation Workflow for Quantitative Mass Spectrometry.Journal of proteome research · 2018Article
- Big Data Science Training Program at a Minority Serving Institution: Processes and Initial Outcomes.Californian journal of health promotion · 2018Article
- Exploring completeness in clinical data research networks with DQe-c.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Neurodegeneration research: Advances in clinical translational neuroscience infrastructure and methods.Alzheimer's & dementia (New York, N. Y.) · 2018Article
- A generic method for improving the spatial interoperability of medical and ecological databases.International journal of health geographics · 2017Article
- Connectome imaging for mapping human brain pathways.Molecular psychiatry · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
Modern biomedical data collection is generating exponentially more data in a multitude of formats. This flood of complex data poses significant opportunities to discover and understand the critical interplay among such diverse domains as genomics, proteomics, metabolomics, and phenomics, including imaging, biometrics, and clinical data. The Big Data for Discovery Science Center is taking an "-ome to home" approach to discover linkages between these disparate data sources by mining existing databases of proteomic and genomic data, brain images, and clinical assessments. In support of this work, the authors developed new technological capabilities that make it easy for researchers to manage, aggregate, manipulate, integrate, and model large amounts of distributed data. Guided by biological domain expertise, the Center's computational resources and software will reveal relationships and patterns, aiding researchers in identifying biomarkers for the most confounding conditions and diseases, such as Parkinson's and Alzheimer's.
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.