scholarly journals Single view vs. multiple views scatterplots

2019 ◽  
Vol 9 (2) ◽  
pp. 1426
Author(s):  
Federico Manuri ◽  
Andrea Sanna ◽  
Fabrizio Lamberti
Keyword(s):  
Web Application ◽  
Visual Representations ◽  
Use Case ◽  
Multiple Views ◽  
Single View ◽  
Visualization Tools ◽  
New Challenges ◽  
Web App ◽  
Visualization Techniques ◽  
Scatterplot Matrix

<span lang="EN-US">Among all the available visualization tools, the scatterplot has been deeply analyzed through the years and many researchers investigated how to improve this tool to face new challenges. The scatterplot visualization diagram is considered one of the most functional among the variety of data visual representations, due to its relative simplicity compared to other multivariable visualization techniques. Even so, one of the most significant and unsolved challenge in data visualization consists in effectively displaying datasets with many attributes or dimensions, such as multidimensional or multivariate ones. The focus of this research is to compare the single view and the multiple views visualization paradigms for displaying multivariable dataset using scatterplots. A multivariable scatterplot has been developed as a web application to provide the single view tool, whereas for the multiple views visualization, the ScatterDice web app has been slightly modified and adopted as a traditional, yet interactive, scatterplot matrix. Finally, a taxonomy of tasks for visualization tools has been chosen to define the use case and the tests to compare the two paradigms.</span>

eMap: A Web Application for Identifying and Visualizing Electron or Hole Hopping Pathways in Proteins

2019 ◽  
Author(s):  
Ruslan N. Tazhigulov ◽  
James R. Gayvert ◽  
Melissa Wei ◽  
Ksenia B. Bravaya
Keyword(s):  
Web Application ◽  
Shortest Paths ◽  
Coarse Grained ◽  
Decay Parameter ◽  
Electron Hole ◽  
Web Based ◽  
Aromatic Amino Acid Residue ◽  
Pathways Model ◽  
Visualization Tools ◽  
Effective Decay

<p>eMap is a web-based platform for identifying and visualizing electron or hole transfer pathways in proteins based on their crystal structures. The underlying model can be viewed as a coarse-grained version of the Pathways model, where each tunneling step between hopping sites represented by electron transfer active (ETA) moieties is described with one effective decay parameter that describes protein-mediated tunneling. ETA moieties include aromatic amino acid residue side chains and aromatic fragments of cofactors that are automatically detected, and, in addition, electron/hole residing sites that can be specified by the users. The software searches for the shortest paths connecting the user-specified electron/hole source to either all surface-exposed ETA residues or to the user-specified target. The identified pathways are ranked based on their length. The pathways are visualized in 2D as a graph, in which each node represents an ETA site, and in 3D using available protein visualization tools. Here, we present the capability and user interface of eMap 1.0, which is available at https://emap.bu.edu.</p>

STM3: a chemistry visualization platform

2005 ◽  
Vol 220 (5/6) ◽  
Author(s):  
Mario Valle
Keyword(s):  
User Interface ◽  
New Technologies ◽  
Software Platform ◽  
Visualization Tools ◽  
Visualization Techniques

AbstractTo support CSCS research users we built STM3, a software platform on which advanced chemistry visualization techniques can be integrated. Its main goal is not to replace existing tools, but to provide functionalities not covered by them. STM3’s unusual characteristic among chemistry visualization tools is its ability to combine chemistry and general visualization techniques in the same view. STM3 is built on top of a proven visualization environment (AVS/Express) that lets CSCS’s visualization staff concentrate its efforts on developing new technologies rather than investing time on graphical and user interface implementation issues.

scholarly journals KnetMaps: a BioJS component to visualize biological knowledge networks

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1651 ◽  
Author(s):  
Ajit Singh ◽  
Christopher J. Rawlings ◽  
Keywan Hassani-Pak
Keyword(s):  
Information Overload ◽  
Interactive Visualization ◽  
Knowledge Networks ◽  
Biological Knowledge ◽  
Single View ◽  
Touch Gestures ◽  
Rich Data ◽  
Effective Visualization ◽  
Visualization Techniques ◽  
Link Component

KnetMaps is a BioJS component for the interactive visualization of biological knowledge networks. It is well suited for applications that need to visualise complementary, connected and content-rich data in a single view in order to help users to traverse pathways linking entities of interest, for example to go from genotype to phenotype. KnetMaps loads data in JSON format, visualizes the structure and content of knowledge networks using lightweight JavaScript libraries, and supports interactive touch gestures. KnetMaps uses effective visualization techniques to prevent information overload and to allow researchers to progressively build their knowledge.

Visualizing Sixteen Years of Data About Portuguese Leisure-Cultural Activities

2012 ◽  
Vol 3 (2) ◽  
pp. 8-22
Author(s):  
Clarissa Rodrigues ◽  
Elizabeth Carvalho
Keyword(s):  
Data Visualization ◽  
Visual Cues ◽  
Leisure Time ◽  
Visual Representations ◽  
End User ◽  
Cultural Activities ◽  
Interactive Data ◽  
Visualization Techniques ◽  
Visualization Application

This paper describes an interactive data visualization application that aims to show how the Portuguese people spent culturally their leisure time between 1994 and 2009. The leisure trend is displayed to the end-user through the use of different visualization techniques and visual cues. The authors developed the visual representations based on the use of simple and regular visual shapes that could be easily combined, interpreted, memorized and used. To better evaluate their results, the authors tested their prototype against a preselected group of subjects.

scholarly journals Data-Driven Intelligent Application for Youtube Video Popularity Analysis using Machine Learning and Statistics

2021 ◽  
Author(s):  
Wenxi Gao ◽  
Ishmael Rico ◽  
Yu Sun
Keyword(s):  
Machine Learning ◽  
Data Processing ◽  
Web Application ◽  
Data Driven ◽  
Accuracy Evaluation ◽  
Video Content ◽  
The Public ◽  
Left Behind ◽  
The World ◽  
Web App

People now prefer to follow trends. Since the time is moving, people can only keep themselves from being left behind if they keep up with the pace of time. There are a lot of websites for people to explore the world, but websites for those who show the public something new are uncommon. This paper proposes an web application to help YouTuber with recommending trending video content because they sometimes have trouble in thinking of the video topic. Our method to solve the problem is basically in four steps: YouTube scraping, data processing, prediction by SVM and the webpage. Users input their thoughts on our web app and computer will scrap the trending page of YouTube and process the data to do prediction. We did some experiments by using different data, and got the accuracy evaluation of our method. The results show that our method is feasible so people can use it to get their own recommendation.

scholarly journals Artificial Intelligence in Healthcare: Validating an AI Algorithm in Health Institutions in the COVID-19 Pandemic (a Use Case)

2021 ◽  
Author(s):  
Иван Андреевич Блохин ◽  
Сергей Павлович Морозов ◽  
Валерия Юрьевна Чернина ◽  
Анна Евгеньевна Андрейченко ◽  
Ислам Висханович Шахабов ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Predictive Value ◽  
Healthcare Access ◽  
Use Case ◽  
Public Health Action ◽  
Health Action ◽  
Automated Data Analysis ◽  
New Challenges ◽  
Health Institutions ◽  
Improve Access

The paper considers new challenges related to public health. Action is needed to improve access to healthcare while maintaining its quality. The introduction of AI-based automated data analysis systems can be a solution to that. The present study seeks to assess the use of AI in outpatient care to detect pathological changes in the lungs typical of a coronavirus amidst the pandemic. The sample size was 600 patients. The results were statistically and analytically processed. The sensitivity attained 94%; the specificity, accuracy and the area under the ROC curve were 77%, 83%, and 87%, respectively. The negative predictive value was 97%; the positive predictive value was 66%. The data obtained show that the algorithm separates the CT scan results having no abnormalities in the lungs. The authors conclude that the usage of AI technologies helped to improve diagnostic accuracy during the COVID-19 pandemic. Artificial intelligence algorithms can also work with patients in non-pandemic times, thus improving healthcare access.

scholarly journals Pixel: a content management platform for quantitative omics data

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6623 ◽  
Author(s):  
Thomas Denecker ◽  
William Durand ◽  
Julien Maupetit ◽  
Charles Hébert ◽  
Jean-Michel Camadro ◽  
...  
Keyword(s):  
Web Application ◽  
Content Management ◽  
Biological Information ◽  
Functional Tests ◽  
Single Experiment ◽  
Code Coverage ◽  
Development Platform ◽  
Management Platform ◽  
Strategic Position ◽  
Web App

Background In biology, high-throughput experimental technologies, also referred as “omics” technologies, are increasingly used in research laboratories. Several thousands of gene expression measurements can be obtained in a single experiment. Researchers are routinely facing the challenge to annotate, store, explore and mine all the biological information they have at their disposal. We present here the Pixel web application (Pixel Web App), an original content management platform to help people involved in a multi-omics biological project. Methods The Pixel Web App is built with open source technologies and hosted on the collaborative development platform GitHub (https://github.com/Candihub/pixel). It is written in Python using the Django framework and stores all the data in a PostgreSQL database. It is developed in the open and licensed under the BSD 3-clause license. The Pixel Web App is also heavily tested with both unit and functional tests, a strong code coverage and continuous integration provided by CircleCI. To ease the development and the deployment of the Pixel Web App, Docker and Docker Compose are used to bundle the application as well as its dependencies. Results The Pixel Web App offers researchers an intuitive way to annotate, store, explore and mine their multi-omics results. It can be installed on a personal computer or on a server to fit the needs of many users. In addition, anyone can enhance the application to better suit their needs, either by contributing directly on GitHub (encouraged) or by extending Pixel on their own. The Pixel Web App does not provide any computational programs to analyze the data. Still, it helps to rapidly explore and mine existing results and holds a strategic position in the management of research data.

scholarly journals Visualisation of Perception of Experiential Activities in Business and Administration and Economy

2021 ◽  
Vol 7 (1) ◽  
pp. 283-292
Author(s):  
Rosaura Fernández-Pascual ◽  
Ana Marín Jiménez ◽  
María Pilar Fernández- Sánchez
Keyword(s):  
Experiential Learning ◽  
Information Visualization ◽  
Qualitative Studies ◽  
Underlying Structure ◽  
Creative Commons ◽  
Word Analysis ◽  
Visualization Tools ◽  
Visualization Techniques ◽  
The University ◽  
Structure Of Knowledge

This paper explores how to incorporate information visualization tools into qualitative studies to represent the underlying structure of knowledge. Information visualization plays a key role in many areas such as decision-making, data mining, market studies, or knowledge management. A case of experiential learning was developed for Quantitative Techniques in Business and Administration and Economy Degrees at the University of Granada, Spain. The goal is to analyze the opinion of students (n = 227) on the development of the activity through information visualization techniques. The gathered information was subjected to a categorization process to unify and homogenize the responses. After a term-clumping process, a co-word analysis using the VosViewer software is used to analyze the relationships among terms and provide the network maps. Results display the main associations and clusters of terms used when assessing the experiential activity, using qualitative techniques. In conclusion, the strengths of data visualization enabling a better understanding of data for qualitative studies are established. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

scholarly journals E-commerce Web App in Azure Cloud: Considerations, Components of Implementation and Schematic Design

2021 ◽  
Vol 14 (4) ◽  
pp. 32
Author(s):  
Rasha Al-Mahrouqi ◽  
Khalsa Al Siyabi ◽  
Amani Al Nabhani ◽  
Salma Al-Hashemi ◽  
Shoukath Ali Muhammed
Keyword(s):  
Web Application ◽  
Transition Period ◽  
Cost Effective ◽  
Development Project ◽  
Cloud Services ◽  
Application Development ◽  
Careful Planning ◽  
Digital Strategy ◽  
Web App ◽  
Schematic Design

Consumers shifted their spending to the web due to the coronavirus (Covid-19) outbreak. Businesses and organizations that once mapped digital strategy with careful planning over a transition period, now forced to scale their initiatives in a matter of days. In this regard, we are motivated by the need to develop a scalable, highly available, resilient, secure, and cost-effective e-commerce web application for demonstrating how cloud services can be leveraged for implementing such applications. This paper is a part of the aforementioned web application development project, titled &ldquo;A cloud-based e-commerce storefront prototype for SMEs in Oman&rdquo;. In this paper, we discuss the system considerations, components of implementation, and the schematic design of the proposed software solution. This paper provides meaningful guidelines for companies that want to adopt cloud-based E-commerce web application to bring their products and services online without much upfront cost or initial investment.

scholarly journals COVIDrugNet: a network-based web tool to investigate the drugs currently in clinical trial to contrast COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Luca Menestrina ◽  
Chiara Cabrelle ◽  
Maurizio Recanatini
Keyword(s):  
Clinical Trial ◽  
Web Application ◽  
Drug Target ◽  
Unmet Need ◽  
Target System ◽  
Holistic View ◽  
Online Tool ◽  
Clinical Drug Research ◽  
Web App ◽  
Clinical Drug

AbstractThe COVID-19 pandemic poses a huge problem of public health that requires the implementation of all available means to contrast it, and drugs are one of them. In this context, we observed an unmet need of depicting the continuously evolving scenario of the ongoing drug clinical trials through an easy-to-use, freely accessible online tool. Starting from this consideration, we developed COVIDrugNet (http://compmedchem.unibo.it/covidrugnet), a web application that allows users to capture a holistic view and keep up to date on how the clinical drug research is responding to the SARS-CoV-2 infection. Here, we describe the web app and show through some examples how one can explore the whole landscape of medicines in clinical trial for the treatment of COVID-19 and try to probe the consistency of the current approaches with the available biological and pharmacological evidence. We conclude that careful analyses of the COVID-19 drug-target system based on COVIDrugNet can help to understand the biological implications of the proposed drug options, and eventually improve the search for more effective therapies.

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