SAMPRA: Scalable Analysis, Management, Protection of Research Artifacts

Author(s):  
Patrick G. Bridges ◽  
Zeinab Akhavan ◽  
Jonathan Wheeler ◽  
Hussein Al-Azzawi ◽  
Orlando Albillar ◽  
...  
Keyword(s):  
Author(s):  
Yang Zheng ◽  
Maryam Kamgarpour ◽  
Aivar Sootla ◽  
Antonis Papachristodoulou

2014 ◽  
Vol 1 (3) ◽  
pp. 191-194
Author(s):  
Srecko Joksimovic ◽  
Dragan Gasevic ◽  
Marek Hatala

Teaching and learning in networked setting has attained a significant amount of attention recently. The central topic of networked learning research is human-human and human-information interactions that occur within a networked learning environment. The nature of these interactions is highly complex and usually requires a multi-dimensional approach in analyzing their effects. Therefore, the main goal of this research is the development of a theoretical model that allows for a comprehensive and scalable analysis of how and why learners engage into collaboration in networked communities. The proposed research method, anticipated research outcomes and contributions to the learning analytics field are discussed.


2017 ◽  
Vol 124 ◽  
pp. 26-45 ◽  
Author(s):  
E.T. Filipov ◽  
K. Liu ◽  
T. Tachi ◽  
M. Schenk ◽  
G.H. Paulino
Keyword(s):  

Optica ◽  
2019 ◽  
Vol 6 (1) ◽  
pp. 19 ◽  
Author(s):  
Daniel Pérez ◽  
Jose Capmany
Keyword(s):  

2020 ◽  
Author(s):  
Fabio González-Arias ◽  
Tyler Reddy ◽  
John E. Stone ◽  
Jodi A. Hadden-Perilla ◽  
Juan R. Perilla

AbstractEnveloped viruses infect host cells via fusion of their viral envelope with the plasma membrane. Upon cell entry, viruses gain access to all the macromolecular machinery necessary to replicate, assemble, and bud their progeny from the infected cell. By employing molecular dynamics simulations to characterize the dynamical and chemical-physical properties of viral envelopes, researchers can gain insights into key determinants of viral infection and propagation. Here, the Frontera supercomputer is leveraged for large-scale analysis of authentic viral envelopes, whose lipid compositions are complex and realistic. VMD with support for MPI is employed on the massive parallel computer to overcome previous computational limitations and enable investigation into virus biology at an unprecedented scale. The modeling and analysis techniques applied to authentic viral envelopes at two levels of particle resolution are broadly applicable to the study of other viruses, including the novel coronavirus that causes COVID-19. A framework for carrying out scalable analysis of multi-million particle MD simulation trajectories on Frontera is presented, expanding the the utility of the machine in humanity’s ongoing fight against infectious disease.


2015 ◽  
Author(s):  
Abhinav Nellore ◽  
Leonardo Collado-Torres ◽  
Andrew E Jaffe ◽  
José Alquicira-Hernández ◽  
Jacob Pritt ◽  
...  

RNA sequencing (RNA-seq) experiments now span hundreds to thousands of samples. Current spliced alignment software is designed to analyze each sample separately. Consequently, no information is gained from analyzing multiple samples together, and it is difficult to reproduce the exact analysis without access to original computing resources. We describe Rail-RNA, a cloud-enabled spliced aligner that analyzes many samples at once. Rail-RNA eliminates redundant work across samples, making it more efficient as samples are added. For many samples, Rail-RNA is more accurate than annotation-assisted aligners. We use Rail-RNA to align 667 RNA-seq samples from the GEUVADIS project on Amazon Web Services in under 16 hours for US$0.91 per sample. Rail-RNA produces alignments and base-resolution bigWig coverage files, ready for use with downstream packages for reproducible statistical analysis. We identify expressed regions in the GEUVADIS samples and show that both annotated and unannotated (novel) expressed regions exhibit consistent patterns of variation across populations and with respect to known confounders. Rail-RNA is open-source software available at http://rail.bio.


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