Brain Disease Neuroscience – Influencing clinical diagnoses and treatments
by data mining analysis- and modelling-driven neuroscience
27 November – 3 December 2017
The availability of clinical, genomic, proteomic and neuroimaging data sets combined with recent advances in ICT, data mining and computational modelling makes it possible to uncover unique biological signatures of disease from multi-level descriptions of the brain. Medicine of the future will capitalise on these biological signatures of diseases for faster diagnosis, more accurate prognosis and leverage the discovery of mechanistic pathways for new types of drugs, novel treatments and ultimately personalised medicine.
The programme of the 5th HBP School combined lectures and practical sessions. In small groups, students worked on week-long projects. Throughout the school, participants were encouraged to introduce new ideas and suggest original experimental techniques. Speakers were available throughout the week to go into details of concepts, provide deeper insights, answer questions or help with specific group requests.
The school started on Monday, 27 November 2017, with registration and a welcome programme and ended the evening of Saturday, 2 December. Sunday, 3 December was departure day.
Application for the 5th HBP School was open to the whole student community and early post-docs. 30 participants were selected in a competitive application process based on an academic decision by the Scientific Committee.
Participants were required to submit an abstract on their current research with their application.
Applications from young female investigators were highly encouraged.
Application is closed.
Seven travel grants were available upon request (European students only - residence).
Travel grant requests had to be sent to email@example.com prior to the application deadline.
HBP Education Programme Office:
Theresa Rass | MUI
Florent Gaillard | CHUV
Ferath Kherif | CHUV
Egidio D'Angelo | UNIPV
Alain Destexhe | CNRS
Bogdan Draganski | CHUV
Viktor Jirsa | AMU
Mira Marcus-Kalish | TAU
Marcello Massimini | UMIL
Francesco Pavone | LENS