scholarly journals iMicrobe: Tools and data-driven discovery platform for the microbiome sciences

GigaScience ◽  
2019 ◽  
Vol 8 (7) ◽  
Author(s):  
Ken Youens-Clark ◽  
Matt Bomhoff ◽  
Alise J Ponsero ◽  
Elisha M Wood-Charlson ◽  
Joshua Lynch ◽  
...  

Abstract Background Scientists have amassed a wealth of microbiome datasets, making it possible to study microbes in biotic and abiotic systems on a population or planetary scale; however, this potential has not been fully realized given that the tools, datasets, and computation are available in diverse repositories and locations. To address this challenge, we developed iMicrobe.us, a community-driven microbiome data marketplace and tool exchange for users to integrate their own data and tools with those from the broader community. Findings The iMicrobe platform brings together analysis tools and microbiome datasets by leveraging National Science Foundation–supported cyberinfrastructure and computing resources from CyVerse, Agave, and XSEDE. The primary purpose of iMicrobe is to provide users with a freely available, web-based platform to (1) maintain and share project data, metadata, and analysis products, (2) search for related public datasets, and (3) use and publish bioinformatics tools that run on highly scalable computing resources. Analysis tools are implemented in containers that encapsulate complex software dependencies and run on freely available XSEDE resources via the Agave API, which can retrieve datasets from the CyVerse Data Store or any web-accessible location (e.g., FTP, HTTP). Conclusions iMicrobe promotes data integration, sharing, and community-driven tool development by making open source data and tools accessible to the research community in a web-based platform.

2019 ◽  
Vol 214 ◽  
pp. 07016 ◽  
Author(s):  
Tian Yan ◽  
Shan Zeng ◽  
Mengyao Qi ◽  
Qingbao Hu ◽  
Fazhi Qi

To improve hardware utilization and save manpower in system maintenance, most of the web services in IHEP have been migrated to a private cloud build upon OpenStack. However, cyber security attacks becomes a serious threats to the cloud progressively. Therefore, a cyber security detection and monitoring system is deployed for this cloud platform. This system collects various security related logs as data sources, and processes them in a framework composed of open source data store, analysis and visualization tools. With this system, security incidents and events can be handled in time and rapid response can be taken to protect cloud platform against cyber security threats.


2020 ◽  
Vol 178 ◽  
pp. 105822 ◽  
Author(s):  
Lucian Simionesei ◽  
Tiago B. Ramos ◽  
Jorge Palma ◽  
Ana R. Oliveira ◽  
Ramiro Neves

2018 ◽  
Vol 80 (6) ◽  
pp. 457-461
Author(s):  
Carlos A. Morales-Ramirez ◽  
Pearlyn Y. Pang

Open-source data are information provided free online. It is gaining popularity in science research, especially for modeling species distribution. MaxEnt is an open-source software that models using presence-only data and environmental variables. These variables can also be found online and are generally free. Using all of these open-source data and tools makes species distribution modeling (SDM) more accessible. With the rapid changes our planet is undergoing, SDM helps understand future habitat suitability for species. Due to increasing interest in biogeographic research, SDM has increased for marine species, which were previously not commonly found in this modeling. Here we provide examples of where to obtain the data and how the modeling can be performed and taught.


2018 ◽  
Vol 231 ◽  
pp. 1100-1108 ◽  
Author(s):  
Alaa Alhamwi ◽  
Wided Medjroubi ◽  
Thomas Vogt ◽  
Carsten Agert

Aerospace ◽  
2020 ◽  
Vol 7 (11) ◽  
pp. 158
Author(s):  
Andrew Weinert

As unmanned aerial systems (UASs) increasingly integrate into the US national airspace system, there is an increasing need to characterize how commercial and recreational UASs may encounter each other. To inform the development and evaluation of safety critical technologies, we demonstrate a methodology to analytically calculate all potential relative geometries between different UAS operations performing inspection missions. This method is based on a previously demonstrated technique that leverages open source geospatial information to generate representative unmanned aircraft trajectories. Using open source data and parallel processing techniques, we performed trillions of calculations to estimate the relative horizontal distance between geospatial points across sixteen locations.


Sign in / Sign up

Export Citation Format

Share Document