scholarly journals linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser

2021 ◽  
Vol 17 (11) ◽  
pp. e1009503
Author(s):  
Johannes Waschke ◽  
Mario Hlawitschka ◽  
Kerim Anlas ◽  
Vikas Trivedi ◽  
Ingo Roeder ◽  
...  
Keyword(s):  
Large Scale ◽  
Trajectory Data ◽  
Web Browser ◽  
Web Based ◽  
Python Script ◽  
Complex Trajectory ◽  
Edge Bundling ◽  
Interactive Visualisation

In biology, we are often confronted with information-rich, large-scale trajectory data, but exploring and communicating patterns in such data can be a cumbersome task. Ideally, the data should be wrapped with an interactive visualisation in one concise packet that makes it straightforward to create and test hypotheses collaboratively. To address these challenges, we have developed a tool, linus, which makes the process of exploring and sharing 3D trajectories as easy as browsing a website. We provide a python script that reads trajectory data, enriches them with additional features such as edge bundling or custom axes, and generates an interactive web-based visualisation that can be shared online. linus facilitates the collaborative discovery of patterns in complex trajectory data.

scholarly journals linus: Conveniently explore, share and present large-scale biological trajectory data from a web browser.

2020 ◽  
Author(s):  
Johannes Waschke ◽  
Mario Hlawitschka ◽  
Kerim Anlas ◽  
Vikas Trivedi ◽  
Ingo Roeder ◽  
...  
Keyword(s):  
Large Scale ◽  
Trajectory Data ◽  
Web Browser ◽  
Web Based ◽  
Python Script ◽  
Complex Trajectory ◽  
Edge Bundling ◽  
Interactive Visualisation

In biology, we are often confronted with information-rich, large-scale trajectory data, but exploring and communicating patterns in such data is often a cumbersome task. Ideally, the data should be wrapped with an interactive visualisation in one concise package that makes it straightforward to create and test hypotheses collaboratively. To address these challenges, we have developed a tool, linus, which makes the process of exploring and sharing 3D trajectories as easy as browsing a website. We provide a python script that reads trajectory data and enriches them with additional features, such as edge bundling or custom axes and generates an interactive web-based visualisation that can be shared offline and online. The goal of linus is to facilitate the collaborative discovery of patterns in complex trajectory data.

scholarly journals MonaGO: a novel Gene Ontology enrichment analysis visualisation system

2020 ◽  
Author(s):  
Ziyin Xin ◽  
Yujun Cai ◽  
Louis T. Dang ◽  
Hannah M.S. Burke ◽  
Jerico Revote ◽  
...  
Keyword(s):  
Gene Ontology ◽  
Enrichment Analysis ◽  
Web Browser ◽  
Web Based ◽  
Single Output ◽  
Go Enrichment ◽  
Unbiased Manner ◽  
High Resolution Images ◽  
Interactive Visualisation ◽  
Go Terms

AbstractMonaGO is a novel web-based visualisation system that provides an intuitive, interactive and responsive interface for performing gene ontology (GO) enrichment analysis and visualising the results. MonaGO combines dynamic clustering and interactive visualisation as well as customisation options to assist biologists in obtaining meaningful representation of overrepresented GO terms, producing simplified outputs in an unbiased manner. MonaGO supports gene lists as well as GO terms as inputs. Visualisation results can be exported as high-resolution images or restored in new sessions, allowing reproducibility of the analysis. An extensive comparison between MonaGO and 11 state-of-the-art GO enrichment visualisation tools based on 9 features revealed that MonaGO is the only platform that simultaneously allows interactive visualisation within one single output page, directly accessible through a web browser with customisable display options. In summary, MonaGO will facilitate the interpretation of GO analysis and will assist the biologists into the representation of the results.

Evol2Circos: A Web-Based Tool for Genome Synteny and Collinearity Analysis and its Visualization in Fishes

2020 ◽  
Vol 111 (5) ◽  
pp. 486-490
Author(s):  
Manmohan Pandey ◽  
Basdeo Kushwaha ◽  
Ravindra Kumar ◽  
Prachi Srivastava ◽  
Suman Saroj ◽  
...  
Keyword(s):  
Large Scale ◽  
Software Tool ◽  
Web Browser ◽  
Web Based ◽  
Specific Data ◽  
Sequencing Technologies ◽  
Assembly Algorithms ◽  
User Friendly ◽  
Research Domains ◽  
Generation Sequencing

Abstract The advent of high throughput next-generation sequencing technologies and improved assembly algorithms have resulted in the accumulation of voluminous genomic data in public domains. These technologies have opened up entries for large scale comparative genome studies, especially the identification of conserved syntenic blocks among species, facilitating studies of the evolutionary importance of the conservation and variation in genomic organization. Synteny construction and visualization require computational and bioinformatics skills to prepare input files for the synteny analysis pipeline. The syntenic information for fishes is still in a juvenile stage and is scattered among different research domains. Here, we present a web-based tool “Evol2Circos” to provide a user-friendly graphical user interface (GUI) to analyze user-specific data for synteny construction and visualization, and to facilitate the browsing of syntenic information of different fishes using the Circos, bar, dual, and dot plots. The information generated from the tool can also be used for further downstream analyses. Evol2Circos software tool is tested under Ubuntu Linux. The web-browser, source code, documentation, user manual, example dataset and scripts are available online at 203.190.147.148/evole2circos/

scholarly journals Hydrology@Home: a distributed volunteer computing framework for hydrological research and applications

2019 ◽  
Vol 22 (2) ◽  
pp. 235-248 ◽  
Author(s):  
Ramil Agliamzanov ◽  
Muhammed Sit ◽  
Ibrahim Demir
Keyword(s):  
Large Scale ◽  
Forecasting Model ◽  
Volunteer Computing ◽  
Web Browser ◽  
Web Based ◽  
User Adoption ◽  
Radio Signals ◽  
Computing Framework ◽  
Hydrological Applications

Abstract Web-based distributed volunteer computing enables scientists to constitute platforms that can be used for computational tasks by using potentially millions of computers connected to the internet. It is a widely used approach for many scientific projects, including the analysis of radio signals for signs of extraterrestrial intelligence and determining the mechanisms of protein folding. User adoption and clients' dependence on the desktop software present challenges in volunteer computing projects. This study presents a web-based volunteer computing framework for hydrological applications that requires only a web browser to participate in distributed computing projects. The framework provides distribution and scaling capabilities for projects with user bases of thousands of volunteers. As a case study, we tested and evaluated the proposed framework with a large-scale hydrological flood forecasting model.

Using Web-based Testing for Large-Scale Assessment

2013 ◽  
Author(s):  
Laura S. Hamilton ◽  
Stephen P. Klein ◽  
William Lorie
Keyword(s):  
Large Scale ◽  
Web Based ◽  
Large Scale Assessment ◽  
Scale Assessment

Impact of COVID-19 on Nuclear Medicine in Germany, Austria and Switzerland: An International Survey in April 2020

2020 ◽  
Vol 59 (04) ◽  
pp. 294-299 ◽  
Author(s):  
Lutz S. Freudenberg ◽  
Ulf Dittmer ◽  
Ken Herrmann
Keyword(s):  
Nuclear Medicine ◽  
Health Systems ◽  
Personal Protective Equipment ◽  
Large Scale ◽  
Diagnostic Procedures ◽  
Protective Equipment ◽  
Current Crisis ◽  
Web Based ◽  
Public Versus Private ◽  
The Impact

Abstract Introduction Preparations of health systems to accommodate large number of severely ill COVID-19 patients in March/April 2020 has a significant impact on nuclear medicine departments. Materials and Methods A web-based questionnaire was designed to differentiate the impact of the pandemic on inpatient and outpatient nuclear medicine operations and on public versus private health systems, respectively. Questions were addressing the following issues: impact on nuclear medicine diagnostics and therapy, use of recommendations, personal protective equipment, and organizational adaptations. The survey was available for 6 days and closed on April 20, 2020. Results 113 complete responses were recorded. Nearly all participants (97 %) report a decline of nuclear medicine diagnostic procedures. The mean reduction in the last three weeks for PET/CT, scintigraphies of bone, myocardium, lung thyroid, sentinel lymph-node are –14.4 %, –47.2 %, –47.5 %, –40.7 %, –58.4 %, and –25.2 % respectively. Furthermore, 76 % of the participants report a reduction in therapies especially for benign thyroid disease (-41.8 %) and radiosynoviorthesis (–53.8 %) while tumor therapies remained mainly stable. 48 % of the participants report a shortage of personal protective equipment. Conclusions Nuclear medicine services are notably reduced 3 weeks after the SARS-CoV-2 pandemic reached Germany, Austria and Switzerland on a large scale. We must be aware that the current crisis will also have a significant economic impact on the healthcare system. As the survey cannot adapt to daily dynamic changes in priorities, it serves as a first snapshot requiring follow-up studies and comparisons with other countries and regions.

scholarly journals Age impairs mnemonic discrimination of objects more than scenes: A web-based, large-scale approach across the lifespan

Cortex ◽  
2021 ◽  
Vol 137 ◽  
pp. 138-148
Author(s):  
Jeremie Güsten ◽  
Gabriel Ziegler ◽  
Emrah Düzel ◽  
David Berron
Keyword(s):  
Large Scale ◽  
Web Based

scholarly journals Mining Vehicle Trajectories to Discover Individual Significant Places: Case Study using Floating Car Data in the Paris Region

2021 ◽  
pp. 036119812199550
Author(s):  
Danyang Sun ◽  
Fabien Leurent ◽  
Xiaoyan Xie
Keyword(s):  
Large Scale ◽  
City Planning ◽  
Human Mobility ◽  
Work Place ◽  
Trajectory Data ◽  
Floating Car Data ◽  
Vehicle Trajectories ◽  
Activity Types ◽  
Paris Region

In this study we discovered significant places in individual mobility by exploring vehicle trajectories from floating car data. The objective was to detect the geo-locations of significant places and further identify their functional types. Vehicle trajectories were first segmented into meaningful trips to recover corresponding stay points. A customized density-based clustering approach was implemented to cluster stay points into places and determine the significant ones for each individual vehicle. Next, a two-level hierarchy method was developed to identify the place types, which firstly identified the activity types by mixture model clustering on stay characteristics, and secondly discovered the place types by assessing their profiles of activity composition and frequentation. An applicational case study was conducted in the Paris region. As a result, five types of significant places were identified, including home place, work place, and three other types of secondary places. The results of the proposed method were compared with those from a commonly used rule-based identification, and showed a highly consistent matching on place recognition for the same vehicles. Overall, this study provides a large-scale instance of the study of human mobility anchors by mining passive trajectory data without prior knowledge. Such mined information can further help to understand human mobility regularities and facilitate city planning.

Sign in / Sign up

Export Citation Format

Share Document