Science in the cloud (SIC): A use case in MRI connectomics.

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BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods.Container-Based Clinical Solutions for Portable and Reproducible Image Analysis.A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data.

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Science in the cloud (SIC): A use case in MRI connectomics.

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2017 nî lūn-bûn

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Science in the cloud (SIC): A use case in MRI connectomics.

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Science in the cloud (SIC): A use case in MRI connectomics.

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Science in the cloud (SIC): A use case in MRI connectomics.

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Science in the cloud (SIC): A use case in MRI connectomics.

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Brian Wandell

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Dean Kleissas

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Joshua T Vogelstein

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Martin Wiener

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R Jacob Vogelstein

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Randal Burns

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Russel A Poldrack

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William Gray Roncal

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Neuroimaging study designs, computational analyses and data provenance using the LONI pipeline

Making big data open: data sharing in neuroimaging

Reproducible Research in Computational Science

Bringing your tools to CyVerse Discovery Environment using Docker

The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments

Enhanced reproducibility of SADI web service workflows with Galaxy and Docker

Data integration: Combined imaging and electrophysiology data in the cloud

Bioboxes: standardised containers for interchangeable bioinformatics software

An open science resource for establishing reliability and reproducibility in functional connectomics

CBRAIN: a web-based, distributed computing platform for collaborative neuroimaging research

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Science in the cloud (SIC): A use case in MRI connectomics.

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P2860

P2860

Science in the cloud (SIC): A use case in MRI connectomics.

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