The F101G was assisted by three computer scientists to develop three new applications to facilitate research in the field of rare diseases (GEMS pilot project) and to make available to the general public the results of a bioinformatics tool using artificial intelligence (GEMVAP). This successful collaboration was organised by the mic.brussels (Microsoft/Brussels Capital Region), which selects the best profiles each year from Brussels' IT schools to participate in its innovation programme. Thibault You-Hout, Dylan Bricar And Geoffrey Dielman explain their work with the F101G.

Thibault You-Hout: "Consent App"

"I worked on the development of a web-based informed consent application to facilitate participation in scientific research in the field of rare diseases. The GEMS study on Marfan syndrome served as a pilot project. The Consent App allows patients/participants to ensure that they understand the objectives of the studies they are invited to join, and thus to give genuine informed consent. It also saves rare disease researchers valuable time that can be spent on research rather than on administrative tasks".

Dylan Bricar: "Pheno App"

"In order to feed the 'Genomic Cloud'' of the F101G, I participated in the design of a conditional questionnaire web app in which the participant in a scientific study can fill in his phenotypic information (set of apparent characteristics of an individual). The participant's answers dynamically redirect him to other questions until the end of the question tree. Another aspect of my work has been the creation of a portal through which users can at any time view and modify their personal information as well as that from the conditional questionnaire, manage their consents and also have access to scientific publications related to the research in which they are participating".

Geoffrey Dielman: "GEMVAP Live"

"In collaboration with the F101G, I developed an application for consulting the results of the artificial intelligence tool called GEMVAP created in the framework of the Genome4Brussels. GEMVAP is an essential bioinformatics and algorithmic research tool on the FBN1 gene (the gene on which the mutations causing Marfan syndrome are found) and aims to compare different predictions of the deleterious effects of FBN1 gene variants. Once these predictions have been compared, the App refines them by cross-checking results from different sources and classifies them as 'pathogenic, non-pathogenic or unknown' mutations. The 'GEMVAP Live' App aims to build and maintain a database containing all GEMVAP predictions and their displays in a user-friendly and educational interface for a non-scientific audience with an awareness of Marfan syndrome.