Genomics & Health Informatics

The mass generation of high-content genomic, imaging and digital data has brought rapid advances in our understanding of cell biology and human diseases, and offers promising avenues for the field of precision medicine. A major obstacle revolves around delivering meaningful information from these data, requiring the deployment of a variety of methods such as statistics, machine learning and data visualization in tight collaboration with clinicians.

The Genomics & Health Informatics Group was created in 2019 to develop statistical and machine-learning methods to integrate genomic, clinical, and imaging data. The group aims to accelerate the diagnosis and improve the understanding and treatment of complex diseases such as neuro-degenerative disorders in collaboration with clinical neuroscientists. The group has expertise in genomics, bioinformatics, RNA biology, neuroscience, data science, and data visualization.

The current lines of research include:

1) the integration of longitudinal cellular imaging with genomic data to study how molecular biology shapes cellular morphology in neuro-degenerative diseases;

2) the development of machine learning methods to integrate longitudinal digital data with genomics to study how individual differences in motor and cognitive behaviors emerge and how such differences may confer vulnerability to neurodegenerative diseases.

In collaborating with clinicians and expert laboratories in molecular neuroscience and bioengineering, the group has access to unique high quality data including longitudinal RNA-sequencing (Patani laboratory, Francis Crick Institute, London) and time-lapse cellular imaging (Serio lab, Kings College, London) from motor neuron cultures obtained from healthy and sick donors.

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Current Group Members

LUISIER, Raphaëlle
(Research Scientist)
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VERZAT, Colombine
(Research Intern)
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