Biological data visualization

• The Johns Hopikins University GitHubGitHub repository and web-based dashboard to visualize and track SARS-CoV-2 cases

BioJavaScript (BioJSBioJS) is a free software library created by scientists at the Genome Analysis Center (TGAC) which has been rebranded to Earlham Institute (EI).

In public health a number of tools are used to analyze and visualize complex data for infectious disease control including geographical information systems (GIS), molecular epidemiology and social network analysis.

• Los Alamos National Laboratory
• Eng-DE4Bios by The Engineering Group is a biosurveillance system that geolocates COVID-19 infected people and identifies clusters at risk
• BlueDot
• The Johns Hopikins University GitHub repository and web-based dashboard to visualize and track SARS-CoV-2 cases
• Healthmap
• Zoe
• Metabiota
• GISAID
• Nextstrain
• Worldometer

BioVis Explorer (https://biovis.lnu.se/) is a freely available interactive web-based tool that provides a review of current visualization approaches and to address the challenge of enabling more researchers to learn more about the methods available, how they differ and which methods should be used for which tasks. BioVis Explorer allows the investigation of visualization methods by filtering for types and properties of data as well as associations with related visualization methods. BioVis Explorer is maintained by the ISOVIS group, headed by Professor Andreas Kerren at Linnaeus University.

BioJavaScript (BioJS) is a free software library created by scientists at the Genome Analysis Center (TGAC) which has been rebranded to Earlham Institute (EI).

BioVis meetings are held through the Intelligent Systems for Molecular Biology (ISMB) meetings of the International Society for Computational Biology (ISCB) and the Institute of Electrical and Electronics Engineers (IEEE VIS) to educate, inspire and engage visualization researchers, bioinformatics and biology researchers in biological data visualization problems.

BioVis Explorer (https://biovis.lnu.se/) is a freely available interactive web-based tool that provides a review of current visualization approaches and to address the challenge of enabling more researchers to learn more about the methods available, how they differ and which methods should be used for which tasks. BioVis Explorer allows the investigation of visualization methods by filtering for types and properties of data as well as associations with related visualization methods. BioVis Explorer is maintained by the ISOVIS group, headed by Professor Andreas Kerren at Linnaeus University.

• BioVis meetings are held through the Intelligent Systems for Molecular Biology (ISMB) meetings of the International Society for Computational Biology (ISCB) and the Institute of Electrical and Electronics Engineers (IEEE VIS) to educate, inspire and engage visualization researchers, bioinformatics and biology researchers in biological data visualization problems.
• VIZBI is an international conference bringing together researchers developing and using computational visualisation in biological research and includes medical illustrators, graphic designers, graphic artists

• Caleydo includes researchers at JKU Linz, the University of Utah, and Harvard Medical School and produces open source software and publications

• Caleydo includes researchers at JKU Linz, the University of Utah, and Harvard Medical SchoolHarvard Medical School

Visualization tools for biological data emerged to analyze large, unstructured data sets often referred to as ‘big data‘big data’. Challenges in biological data visualization of big data include volume of data, variety of formats and determining the validity of the data.

Circos is a free software package licensed under GPL for visualizing data and information in a circular layout. Circos was initially designed for visualizing genomic data but has been used to create images for a variety of publications. Circos was created by Martin Krzywinski at the Michael Smith Genome Sciences Center, Vancouver.

Data visualization research goes beyond statistical graphics and works to understand links between visualization and human perception. Techniques in data visualization have been developed across fields such as psychology, color theory, statistics and computer science. Using bioinformatics visualization techniques researchers are able to gain insight into their data that is not obvious from descriptive statistics.

Data visualization research goes beyond statistical graphics and works to understand links between visualization and human perception. Techniques in data visualization have been developed across fields such as psychology, color theory, statistics and computer science. Using bioinformatics visualization techniques researchers are able to gain insight into their data that is not obvious from descriptive statistics.

Visualization tools for biological data emerged to analyze large, unstructured data sets often referred to as ‘big data’. Challenges in biological data visualization of big data include volume of data, variety of formats and determining the validity of the data.

Information visualization techniques are used in bioinformatics to visualize a large amount of information and facilitate analysis and data mining. Information visualization techniques are computerized methods for selection, transformation and representation of data in a visual form to facilitate human interaction for the purpose of exploring and understanding data. These techniques take advantage of the large bandwidth of human vision and the innate ability to discern patterns within visual fields in order to manage and analyze large amounts of biological information.

Data visualization research goes beyond statistical graphics and works to understand links between visualization and human perception. Techniques in data visualization have been developed across fields such as psychology, color theory, statistics and computer science. Using bioinformatics visualization techniques researchers are able to gain insight into their data that is not obvious from descriptive statistics.

Visualization tools for biological data emerged to analyze large, unstructured data sets often referred to as ‘big data’. Challenges in biological data visualization of big data include volume of data, variety of formats and determining the validity of the data.

BioVis Explorer (https://biovis.lnu.se/) is a freely available interactive web-based tool that provides a review of current visualization approaches and to address the challenge of enabling more researchers to learn more about the methods available, how they differ and which methods should be used for which tasks. BioVis Explorer allows the investigation of visualization methods by filtering for types and properties of data as well as associations with related visualization methods. BioVis Explorer is maintained by the ISOVIS group, headed by Professor Andreas Kerren at Linnaeus University.

BioVis meetings are held through the Intelligent Systems for Molecular Biology (ISMB) meetings of the International Society for Computational Biology (ISCB) and the Institute of Electrical and Electronics Engineers (IEEE VIS) to educate, inspire and engage visualization researchers, bioinformatics and biology researchers in biological data visualization problems.

The Biological Visualisation Network (BiVi) is a central resource for information on bio-visualisation, supplemented with annual meetings for networking and educational purposes. BiVi is focused on emerging trends and challenges in visualisation of biological data.

• Caleydo includes researchers at JKU Linz, the University of Utah, and Harvard Medical School