ArticlePloS one2010
Neuroimaging study designs, computational analyses and data provenance using the LONI pipeline.
Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers.
What it found
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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.
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Who cites it
88 citing papers in PubMed.
- Centralized Review of Alzheimer's Disease and Related Dementias Biomedical Repositories and Computational Methods.Bioengineering (Basel, Switzerland) · 2026Review
- Brain structure and allelic associations in Alzheimer's disease.CNS neuroscience & therapeutics · 2023Article
- NeuroBridge ontology: computable provenance metadata to give the long tail of neuroimaging data a FAIR chance for secondary use.Frontiers in neuroinformatics · 2023Article
- Longitudinal manganese-enhanced magnetic resonance imaging of neural projections and activity.NMR in biomedicine · 2022Review
- Data sharing and privacy issues in neuroimaging research: Opportunities, obstacles, challenges, and monsters under the bed.Human brain mapping · 2022Review
- Three-dimensional self-attention conditional GAN with spectral normalization for multimodal neuroimaging synthesis.Magnetic resonance in medicine · 2021Article
- Global and Regional Changes in Perivascular Space in Idiopathic and Familial Parkinson's Disease.Movement disorders : official journal of the Movement Disorder Society · 2021Article
- Neuroimaging PheWAS (Phenome-Wide Association Study): A Free Cloud-Computing Platform for Big-Data, Brain-Wide Imaging Association Studies.Neuroinformatics · 2021Article
- Volumetric distribution of perivascular space in relation to mild cognitive impairment.Neurobiology of aging · 2021Article
- Precision Medicine in Neonates: A Tailored Approach to Neonatal Brain Injury.Frontiers in pediatrics · 2021Review
- Article
- Imputation Strategy for Reliable Regional MRI Morphological Measurements.Neuroinformatics · 2020Article
- Modernizing the Methods and Analytics Curricula for Health Science Doctoral Programs.Frontiers in public health · 2020Article
- Small Animal Multivariate Brain Analysis (SAMBA) - a High Throughput Pipeline with a Validation Framework.Neuroinformatics · 2019Article
- A Distributed Computing Platform for fMRI Big Data Analytics.IEEE transactions on big data · 2019Article
- Predictive Big Data Analytics using the UK Biobank Data.Scientific reports · 2019Article
- Big data sharing and analysis to advance research in post-traumatic epilepsy.Neurobiology of disease · 2019Review
- Harmonization of pipeline for preclinical multicenter MRI biomarker discovery in a rat model of post-traumatic epileptogenesis.Epilepsy research · 2019Article
- Blood-brain barrier breakdown is an early biomarker of human cognitive dysfunction.Nature medicine · 2019Article
- A Serverless Tool for Platform Agnostic Computational Experiment Management.Frontiers in neuroinformatics · 2019Article
28 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
Modern computational neuroscience employs diverse software tools and multidisciplinary expertise to analyze heterogeneous brain data. The classical problems of gathering meaningful data, fitting specific models, and discovering appropriate analysis and visualization tools give way to a new class of computational challenges--management of large and incongruous data, integration and interoperability of computational resources, and data provenance. We designed, implemented and validated a new paradigm for addressing these challenges in the neuroimaging field. Our solution is based on the LONI Pipeline environment [3], [4], a graphical workflow environment for constructing and executing complex data processing protocols. We developed study-design, database and visual language programming functionalities within the LONI Pipeline that enable the construction of complete, elaborate and robust graphical workflows for analyzing neuroimaging and other data. These workflows facilitate open sharing and communication of data and metadata, concrete processing protocols, result validation, and study replication among different investigators and research groups. The LONI Pipeline features include distributed grid-enabled infrastructure, virtualized execution environment, efficient integration, data provenance, validation and distribution of new computational tools, automated data format conversion, and an intuitive graphical user interface. We demonstrate the new LONI Pipeline features using large scale neuroimaging studies based on data from the International Consortium for Brain Mapping [5] and the Alzheimer's Disease Neuroimaging Initiative [6]. User guides, forums, instructions and downloads of the LONI Pipeline environment are available at http://pipeline.loni.ucla.edu.
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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.