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Fastr specifications

Information


Unique identifier OMICS_22278
Name Fastr
Software type Framework/Library
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Python
License Apache License version 2.0
Computer skills Advanced
Stability Stable
Maintained Yes

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Versioning


No version available

Documentation


Maintainer


  • person_outline Hakim Achterberg

Additional information


http://fastr.readthedocs.io/en/stable/

Publication for Fastr

Fastr citations

 (14)
library_books

Synchronization of intrinsic 0.1‐Hz blood‐oxygen‐level‐dependent oscillations in amygdala and prefrontal cortex in subjects with increased state anxiety

2018
PMCID: 5887876
PMID: 29368814
DOI: 10.1111/ejn.13845

[…] attached to the subject using a respiration belt. the sampling rate used was 400 hz. the fmri plug‐in for eeglab (niazy et al., ) was used to detect ecg beat‐to‐beat complexes. within this tool, the fastr algorithm (for removal of gradient‐induced artifacts) and the beat‐to‐beat detection algorithm were used in succession, resulting in beat‐to‐beat (rri) interval time courses. […]

library_books

Reproducible Large Scale Neuroimaging Studies with the OpenMOLE Workflow Management System

2017
Front Neuroinform
PMCID: 5361107
PMID: 28381997
DOI: 10.3389/fninf.2017.00021

[…] ; peng, ). this is of tremendous importance to enable reproducibility and thorough peer-reviewing of scientific results., finally, we have recently noted another effort developed in python: fastr (achterberg et al., ). it is designed around a plugin system that enables connecting to different data sources or execution environments. at the moment, execution environments […]

library_books

Accessible Neurobehavioral Anger Related Markers for Vulnerability to Post Traumatic Stress Symptoms in a Population of Male Soldiers

2017
PMCID: 5339223
PMID: 28326027
DOI: 10.3389/fnbeh.2017.00038

[…] bipolar ag/agcl electrodes were attached to the right and left side of the chest. preprocessing of the ecg signal and rr interval analysis was performed as described in raz et al. (). briefly, fastr algorithm (niazy et al., ) implemented in fmrib plug-in for eeglab (delorme and makeig, ) was used for mr gradients artifacts removal. r peaks were detected using the fmrib plug-in and manually […]

library_books

Distinction between Neural and Vascular BOLD Oscillations and Intertwined Heart Rate Oscillations at 0.1 Hz in the Resting State and during Movement

2017
PLoS One
PMCID: 5215612
PMID: 28052074
DOI: 10.1371/journal.pone.0168097

[…] on the thorax, standard channels (siemens standard, lead 1) were used. the sampling rate was 400 hz. the fmrib plug-in for eeglab was used for qrs (heart beat) detection []. within this tool, the fastr algorithm (for removal of gradient-induced artifacts) and the qrs detection algorithm were used in succession, resulting in beat-to-beat interval (rri) time courses. […]

library_books

A Review of Computational Methods for Finding Non Coding RNA Genes

2016
Genes
PMCID: 5192489
PMID: 27918472
DOI: 10.3390/genes7120113

[…] and single nucleotide substitution matrices for rna sequences. the web-based tool rnaloss [] was developed to provide information about the distribution of locally optimal secondary structures., fastr [] was applied to the discovery of riboswitches, a class of rna domains, which regulate metabolite synthesis. given an rna sequence with known secondary structure, fastr efficiently computes […]

library_books

Comparison of the Fluid Resuscitation Rate with and without External Pressure Using Two Intraosseous Infusion Systems for Adult Emergencies, the CITRIN (Comparison of InTRaosseous infusion systems in emergency medicINe) Study

2015
PLoS One
PMCID: 4668027
PMID: 26630579
DOI: 10.1371/journal.pone.0143726

[…] or other medical emergencies. the aim of this study, using body donors, was to compare a semi-automatic (ez-io®) device at two insertion sites and a sternal intraosseous infusion device (fastr™)., twenty-seven medical students being inexperienced first-time users were randomized into three groups using ez-io and fastr. the following data were evaluated: attempts required […]


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Fastr institution(s)
Biomedical Imaging Group Rotterdam, Departments of Medical Informatics and Radiology, Erasmus MC, Rotterdam, Netherlands; Imaging Science & Technology, Faculty of Applied Sciences, Delft University of Technology, Delft, Netherlands
Fastr funding source(s)
Supported by The Heart Brain Connection Consortium, the Netherlands Cardiovascular Research Initiative (CVON2012-06), Population Imaging Infrastructuur in Medical Delta, the European Regional Development Fund (Kansen voor West) and co-financed by the province of South-Holland; and BBMRI-NL2.0

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