Interactive, Browser-Based Graphics to Visualize Complex Data in Education of Biomedical Sciences for Veterinary Students

Abstract

In veterinary education, data from biomedical or natural sciences are mostly presented in the form of static or animated graphics with no or little amount of interactivity. These kinds of presentations are, however, often not sufficient to depict the complexity of the data or the presented topic. Interactive graphics, which allow to dynamically change data and related graphics, have rarely been considered as teaching tool in higher education of biomedical disciplines for veterinary education so far. In order to study the applicability and the usefulness of interactive graphics in biomedical disciplines for lecturers and students in veterinary education, three different courses from biomedical disciplines were exemplarily implemented as interactive graphics and evaluated in a pilot study by a survey amongst lecturers and students of our university. The interactive graphics were built using the Shiny environment, a web-based application framework for the statistic software R. The survey amongst lecturers and students was based on questionnaires covering questions on the handling and usefulness of the digital teaching tools. In total, n = 327 students and n = 5 lecturers participated in the evaluation study which revealed that the interactive graphics are easy to handle for lecturers and students, and that they can increase the motivation for either teaching or learning. In total, 71% of the students affirmed that interactive graphics led to an increased interest for the presented contents and 76% expressed the wish to get taught more topics with interactive graphics. We also provide a workflow that can be used as a guideline to develop interactive graphics.

THER: Integrative Web Tool for Tumor Hypoxia Exploration and Research

“…Notably, THER only explores the effect of direct oxygen status on tumor cells and does not yet address factors that indirectly affect oxygen status (e.g., different altitude levels and HIF-1α expression levels). In addition, THER has some shortcomings: 1) The sample size of the dataset is limited, so there is a risk that the error distribution may deviate from the normal distribution (42). 2) The number of datasets included for some cancer types or cell lines is small.…”

HPVTIMER: A shiny web application for tumor immune estimation in human papillomavirus‐associated cancers

“…Users can freely conduct all analyses on the HPVTIMER website ( http://www.hpvtimer.com/ ) without registration or login. HPVTIMER was constructed using the R package shiny [ 36 ], whereas server‐side and interactive data processing was performed with an R script (version 4.0.2, https://www.r-project.org/ ). HPVTIMER utilizes several third‐party tools, such as limma [ 37 ], meta [ 38 ], IOBR [ 39 ], clusterProfiler [ 40 ], and Pathview [ 41 ] (Table S3 ).…”