Apr 05, 2016: TI Design students: Biological Networks for everyone, with web-ANIMO!

April 05, 2016Biological Networks for everyone, with web-ANIMO!
Room: HB 2FTI Design students
12:30-13:30

This is a presentation by students working on a TI design project with the following description:

The branch of computer science known as systems biology studies the processes occurring inside living beings by means of mathematical models. Those models are then analyzed with computers, allowing expert biologists to investigate the complex dynamics of the modelled systems.

Unfortunately, mathematical models are typically out of the comfort zone of most biologists: they have studied biology, not mathematics or computer science!

We want to help biologists acquire more familiarity with the powerful tools of systems biology without requiring them to learn several books of new theories and formalisms. For this reason, we have developed ANIMO (Analysis of Networks with Interactive Modeling), a tool that hides the complexity of formal models behind a user-friendly interface, and is designed to be used directly by biologists.

Over the past few years, ANIMO has grown from an embryonal prototype to a complex and powerful modeling tool. However, because of its software dependencies, ANIMO's installation process is not as smooth as we would like it to be. The need to install multiple tools (and support the process on different platforms) makes it more difficult to reach most of the users ANIMO is aimed at. A good idea to make software more accessible is to “put it on the web”: nowadays, even complex softwares are made available as web-apps and smartphone apps, reaching many more users and helping them to efficiently perform useful tasks.

The aim of this design project is to develop a user-friendly web interface for ANIMO, to make it usable by biologists on any platform, from desktop computers to smartphones. This will make the full power of formal methods available for a much larger public, allowing biologists to efficiently design, share and collaborate on systems biology models.