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The perfect neuroimaging-genetics-computation storm: collision of petabytes of data, millions of hardware devices and thousands of software tools
2013
Brain Imaging and Behavior
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These are implemented as graphical workflow protocols in the context of analyzing imaging (sMRI, fMRI, DTI), phenotypic (demographic, clinical), and genetic (SNP) data. ...
In this paper, we demonstrate several advanced computational neuroimaging and genetics case-studies, and end-to-end pipeline solutions. ...
Some of the data processed in this study was partly funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904). ...
doi:10.1007/s11682-013-9248-x
pmid:23975276
pmcid:PMC3933453
fatcat:4ghlkgwe4vbo3jndkg56nz3r7y
Neurological imaging: statistics behind the pictures
2011
Imaging in Medicine
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The diverse phenotypes and significant normal and pathological brain variability demand reliable and efficient statistical methodologies to model, analyze and interpret raw neurological images and derived ...
This greatly facilitates the processes of algorithm development, mathematical modeling and testing of novel computational techniques for analyzing multimodal neuroimaging data. ...
protocols, incorporating modern Grid and Cloud computing infrastructures, and supports the engagement of multidisciplinary investigators in such translational studies. ...
doi:10.2217/iim.11.37
pmid:22180753
pmcid:PMC3237637
fatcat:ftwdvp25mjgxliasbaduaylkdm
Large-scale analysis of neuroimaging data on commercial clouds with content-aware resource allocation strategies
2014
The international journal of high performance computing applications
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as "mouse brain phenotyping". ...
In this paper we use a commercial cloud platform for brain neuroimaging and analysis. ...
ACKNOWLEDGEMENTS The authors would like to thank Alberto Galbusera for assistance with data collection and PiCloud Inc., particularly Ken Elkabany, for providing technical assistance. ...
doi:10.1177/1094342013519483
fatcat:qtchpzss2fhjtikjjfebg5kjmu
Neuropathophysiology, Genetic Profile, and Clinical Manifestation of Mucolipidosis IV—A Review and Case Series
2020
International Journal of Molecular Sciences
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This review aims to outline the pathophysiology and genetic defects of this condition with a focus on the genotype–phenotype correlation amongst cases published in the literature. ...
The authors will present their own clinical observations and long-term outcomes in adult MLIV cases. ...
cerebellar disease in the MLIV mouse model (but has not yet been tested in humans) [5] Molecular analysis is the most effective diagnostic test, because it allows determination of the cause of the disease ...
doi:10.3390/ijms21124564
pmid:32604955
pmcid:PMC7348969
fatcat:zevuz4sxd5aq5d345k7tgqxixi
OpenNeuro: An open resource for sharing of neuroimaging data
[article]
2021
bioRxiv
pre-print
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The sharing of research data is essential to ensure reproducibility and maximize the impact of public investments in scientific research. ...
The impact of the shared data is evident in a growing number of published reuses, currently totalling more than 150 publications. ...
The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. ...
doi:10.1101/2021.06.28.450168
fatcat:oeaxuspnubdydmj5fyfgych7dy
Automated Landmarking via Multiple Templates
[article]
2022
bioRxiv
pre-print
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Geometric morphometrics based on landmark data has been increasingly used in biomedical and biological researchers for quantifying complex phenotypes. ...
This K-means method uses an approximation of the total morphological variation in the dataset to suggest samples within the population to be used as landmark templates. ...
In our sample, this leads reference point clouds with 791 and 674 points for mouse and ape datasets respectively. 3) For each point in the reference point cloud, the point closest to the target model is ...
doi:10.1101/2022.01.04.474967
fatcat:3n6rspio4bfcpf7vzandrj3ql4
RIKEN MetaDatabase
2018
International Journal on Semantic Web and Information Systems (IJSWIS)
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The platform was released in April 2015, and 113 databases, including mammalian, plant, bioresource and image databases, with 26 ontologies have been published using this platform as of January 2017. ...
Recently, the number and heterogeneity of life science datasets published on the Web have increased significantly. ...
be generated in the RIKEN Cloud Service. ...
doi:10.4018/ijswis.2018010106
fatcat:o3bx674wtrgplb23tumhj3c7ia
Graphical neuroimaging informatics: Application to Alzheimer's disease
2013
Brain Imaging and Behavior
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In this article, we illustrate the utility of INVIZIAN for simultaneous exploration and mining a large collection of extracted cortical surface data arising in clinical neuroimaging studies of patients ...
Users can fluidly interact with an entire collection of cortical surfaces using only their mouse. ...
Acknowledgments The authors wish to thank the faculty and staff of the Institute of Neuroimaging and Informatics of the University of Southern California and the Laboratory of Neuro Imaging (LONI) at the ...
doi:10.1007/s11682-013-9273-9
pmid:24203652
pmcid:PMC4012008
fatcat:ws5vsn5sizb53kkzdspyri3vru
Neuropathology of brain and spinal malformations in a case of monosomy 1p36
2013
Acta Neuropathologica Communications
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Neuroimaging studies suggest that monosomy 1p36 is associated with brain malformations including polymicrogyria and nodular heterotopia, but the histopathology of these lesions is unknown. ...
Neuroimaging studies suggest that monosomy 1p36 is associated with brain malformations including polymicrogyria and nodular heterotopia, but the histopathology of these lesions is unknown. ...
Table 1 1 Genes related to development and function of nervous system within region of 1p36.21-1p36.33 deletion Symbol Description
Locus
Site
Mouse
ortholog
Human diseases
Null mouse phenotype ...
doi:10.1186/2051-5960-1-45
pmid:24252393
pmcid:PMC3893467
fatcat:yuat54ahgbe5zdcufirfurprta
Cerebrovascular Disease Knowledge Portal
2018
Stroke
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Acknowledgments We would like to recognize all members of the technical teams at the Broad Institute and American Heart Association Institute for Cardiovascular Precision Medicine. ...
Commands contained in these scripts are submitted to the cloud computing system, where they are executed in parallel using the appropriate kernels. ...
Once access to the data is granted, users are able to analyze data in the secure cloud-based computational workspace provided by the PMP. ...
doi:10.1161/strokeaha.117.018922
pmid:29335331
pmcid:PMC5780219
fatcat:psk5tf3wbbe7bpm5ejym5z2ujm
Common variants of NRXN1, LRP1B and RORA are associated with increased ventricular volumes in psychosis - GWAS findings from the B-SNIP deep phenotyping study
[article]
2017
bioRxiv
pre-print
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This is the first report of common genetic variants associated with these intermediate phenotypes. ...
Significant associations were observed with two cerebrospinal fluid volumes: the temporal horn of left lateral ventricle was associated with NRXN1, and the volume of the cavum septum pellucidum was associated ...
The Bionimbus PDC allows users authorized by NIH to compute over human genomic data in a secure compliant fashion. The Bionimbus PDC is part of the OSDC ecosystem. ...
doi:10.1101/175489
fatcat:u6me2ksb5felzczmvj7u75ppdq
Affective, neurocognitive and psychosocial disorders associated with traumatic brain injury and post-traumatic epilepsy
2018
Neurobiology of Disease
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To drive the field forward towards improved treatment strategies, it is imperative that both seizures and neurobehavioral outcomes are assessed in parallel after TBI, both in patient populations and preclinical ...
Clinical studies in this arena are often challenged by the confounding effects of anti-seizure medications, while preclinical studies have rarely examined an adequately extended time course to fully capture ...
Acknowledgements The authors acknowledge funding from the National Institutes of HealthRFA-NS-16-012 -Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) project; the National Health ...
doi:10.1016/j.nbd.2018.07.018
pmid:30059725
pmcid:PMC6348140
fatcat:fafdxefm3zc35k6grbvkd3owyy
A web-based brain atlas of the vervet monkey, Chlorocebus aethiops
2011
NeuroImage
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The averaged MRI atlas is also available as a volume in Neuroimaging Informatics Technology Initiative format. ...
Despite the extended time period since their divergence, the major sulcal and subcortical landmarks in vervets are highly conserved relative to those described in macaques. ...
Acquisition of the cryomacrotome data was supported in part by the United States Department of Energy contract DE-FC03-87-ER60615. ...
doi:10.1016/j.neuroimage.2010.09.070
pmid:20923706
pmcid:PMC3008312
fatcat:lunvhd3yrbca5prht7viu76nga
NCI Workshop Report: Clinical and Computational Requirements for Correlating Imaging Phenotypes with Genomics Signatures
2014
Translational Oncology
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goals in cancer research. ...
The first workshop focused on clinical and scientific requirements, exploring our knowledge of phenotypic characteristics of cancer biological properties to determine whether the field is sufficiently ...
This newer approach to integrated cross-species testing, termed coclinical trials, involves concurrent assessment of novel drug combinations in mouse and human-in-mouse models of tumors, and in patients ...
doi:10.1016/j.tranon.2014.07.007
pmid:25389451
pmcid:PMC4225695
fatcat:mmc4hxums5b2ppttzd37ffsoxi
Fragile X Syndrome: A Model of Gene-Brain-Behavior Relationships
2001
Molecular Genetics and Metabolism
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The larger head height is likely related to the larger brains seen by neuroimaging in patients with FXS compared to controls (57-59). ...
Early studies of the knockout mouse suggested an enhanced number of dendritic connections that have also been seen in three humans with FXS (23,24,26). ...
Background Genes Influence the Phenotype The knockout mouse models brought our attention to the influence of background gene effects on the fragile X phenotype. ...
doi:10.1006/mgme.2001.3225
pmid:11592806
fatcat:sq7h4p55tndwrnltcczmcnxq7a
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