Experiences from scaling scale Science Gateway operations

Marru, Suresh; Piece, Marlon; Abeysinghe, Eroma; Pamidighantam, Sudhakar; Christie, Marcus; Wannipurage, Dimuthu

doi:10.1145/3332186.3333159

Cited by 4 publications

(3 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Commands for submitting this simulation to NSG are included in the repository. Further, the model is also available at the Cybershuttle site (https://neuroscience.cybershuttle.org) [34], which allows for tracking simulations and parameter sweeps.…”

Section: Softwarementioning

confidence: 99%

Python/NEURON code for simulating biophysically realistic thalamocortical dynamics during sleep

Fink,

Sanda,

Bayer

et al. 2024

Preprint

View full text Add to dashboard Cite

Understanding the function of sleep and its associated neural rhythms is an important goal in neuroscience. While many theoretical models of neural dynamics during sleep exist, few include the effects of neuromodulators on sleep oscillations and describe transitions between sleep and wake states or different sleep stages. Here, we started with a C++-based thalamocortical network model that describes characteristic thalamic and cortical oscillations specific to sleep. This model, which includes a biophysically realistic description of intrinsic and synaptic channels, allows for testing the effects of different neuromodulators, intrinsic cell properties, and synaptic connectivity on neural dynamics during sleep. We present a complete reimplementation of this previously-published sleep model in the standardized NEURON/Python framework, making it more accessible to the wider scientific community.

show abstract

Section: Softwarementioning

confidence: 99%

Python/NEURON code for simulating biophysically realistic thalamocortical dynamics during sleep

Fink,

Sanda,

Bayer

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The Science Gateway Platform (SciGaP) is an important CI gateway to advance scientific discovery that minimizes the net operating cost of Science Gateways [9]. The SciGaP project's goal is to develop a robust platform with the ability to provide generic middleware functionalities and features required by the science gateways.…”

Section: Related Workmentioning

confidence: 99%

“…The paper provides various examples of Science Gateways being operated through multi-tenanted SciGaP Infrastructure for different field of sciences. Some of them includes SEAGrid, Ultrascan, PGA, InterACTWEL, Next GEN Thermo DB, Prostate Cancer Prediction [9]. The Dynaswap project uses similar ideas for multi-tenanted infrastructure for deploying new VMs and still allowing users to share data, workflow and resources between each other.…”

Section: Related Workmentioning

confidence: 99%

Enabling Secure and Effective Biomedical Data Sharing through Cyberinfrastructure Gateways

Goyal¹,

Purkayastha²,

Phillips³

et al. 2020

Preprint

View full text Add to dashboard Cite

Scientific cyberinfrastructures promise solutions to computational challenges with rich resources; they embrace collaborative workflows in which users can access and share scientific data and computing resources to perform research and education tasks, which catalyze scientific discovery. The Dynaswap project reports on developing a coherently integrated and trustworthy holistic secure workflow protection architecture for cyberinfrastructures which can be used on virtual machines deployed through cyberinfrastructure (CI) services such as JetStream. This service creates a user-friendly cloud environment designed to give researchers access to interactive computing and data analysis resources on demand. The Dynaswap cybersecurity architecture supports roles, role hierarchies, and data hierarchies, as well as dynamic changes of roles and hierarchical relations within the scientific infrastructure. Dynaswap combines existing cutting-edge security frameworks (including an Authentication Authorization-Accounting framework, Multi-Factor Authentication, Secure Digital Provenance, and Blockchain) with advanced security tools (e.g., Biometric-Capsule, Cryptography-based Hierarchical Access Control, and Dual-level Key Management). The security technologies have been developed and integrated with the Open Medical Record System for enhanced security purposes and delivering a secure scientific infrastructure, which allows researchers, educators, practitioners, and students to remotely access and share sensitive data, computing resources, and workflows with flexibility and convenience while also having the highest security and privacy protection. The CI is being validated in life-science research environments and in the education settings of Health Informatics.

show abstract