Project purpose

The concept of this visualization component is to create summaries of information regarding biological data and ideally serve as a multiprupose tool for data with similar complex structure.

The above pie chart attempts to act as a filter in complicated data structures containing multiple data types (in our case diseases, protein-targets, shared-phenotypes, drugs). And also provide a simple but effective way of analysis.

In the initial state the visualization provides an overview of the differnet data types existing in a data structure.

Once a pie piece is clicked the user sees all the underlying data of a specific type.

The home breadcrumb is used to go back to the initial state.

Depending on the data values, different distance from the center will be allocated. This way with an instant look, the user will get a first perception of the data points with the highest values as well have an immediate estimation of the data distribution.

The five rings intentionally seperate the data into 5 equal pieces depending on their values. By clicking on the bull rings, the clicked one expands to the maximum, acting as a filter and thus focusing on the piece of the selected distribution.

Lastly the user may click in a specific data-point or label to learn more about an individual object through a small versatile tooltip which will pop up.

The github repository of the web component is located here with analytical instructions on its use while it has already been uploaded in the npm and biojs registries accordingly.

Experiments & future plans

During the gsoc we experimented with graphs trying to find intuitive ways to analyze relationships among data. The result of this process led to the implementation of some prorotypes. One of the future goals of is to combine the two ideas and create graphs where the nodes are somewhat of a more complex entity rather than bubble nodes.

One potential scenario would be to the pieChart instead of multiple nodes would, something that would greatly reduce the complexity of heavy loaded graphs. Although in primitive state for the purpose of this evaluation they were put in this repository temporarily.

Project pages and downloads

The VizTargetDiseases web component is available with detailed instructions, documetation and examples, from the following sources:

Experiments (network) are also available:

Thank note

I would like to thank my mentors Luca Fumis & Miguel Pignatelli for their support and valuable contribution throughout this summer despite their heavy workload and inviting me in the E.B.I. for a User Experience session. I am grateful to the Biojs community for the the great responsivenes and collaborative spirit as well for the rich educational material and their trust which permitted me to contribute to the open-source community which in the future I would like to contribute further since I find this process extremely educational and creative. Last but not least I would like to thank the organization of GSOC that gives the opportunity and the necessary resources to students to contribute to projects they are passionate about, develop their skills further and contribute to the open-source community.

It's been a wonderful summer.