In this new era of large scale data analysis as well as rapid developments in the sequencing and analysis of the human genome, there is a need to take a multidisciplinary approach. If you are interested in genomics, big data analysis and digital health including personalized medicine, then this program is perfect for you. You will be interacting with a wide range of people and disciplines to advance personalized health and basic understanding of the variability of human biology.
Genomics and genetics is transforming with advances of sequencing technologies. It also transforms the healthcare, from assessing human genetics, to tracking microbial outbreak or antibiotic resistance, and associating microbiomes with diseases. These big data challenge our computational techniques as well as our evolutionary models to interpret the genetic diversity.
At the core of the development of digital health, biomedical informatics plays a key role in the implementation, integration and evaluation of innovative digital methods and tools. The HI5lab (Health Informatics for Innovation, Integration, Implementation and Impact) aims at connecting these multiple dimensions with the ultimate ambition to demonstrate the impact of eHealth on the health of individuals and populations. The HI5lab is located at Campus Biotech, connected to the various expertise domains such as global health, medical information science, citizen cyberscience, bioinformatics, affective and cognitive sciences. It is also connected to global actors such as WHO, ITU, various UN agencies and NGOs from the International Geneva.
Data, algorithms and knowledge for human’s health. Digitalization is a major change in our society and applies to the whole life science ecosystem. The “Medical Information Science” group is working on the phenotypic side. Working with very heterogeneous sources of multimodal data - personal health records, such as sensors, captors and activities, patients-related data, such as computerized patient records, behavior and lifestyle - environment, exposition factors - the living ecosystems - regulatory frameworks - knowledge sources in order to build actionable data pipelines that can be used to connect with *omics. The activities of the group focus on semantics, data interpretability tools such as natural language processing. People work with symbolic, rule-based and probabilistic instrument
We have a strong interest in population genomics and genetics of complex traits. We are using various methodologies to understand the role of genetic variation in phenotypic variation. We also aim to understand what fraction of genetic variation is harbored within functional elements of the human genome and develop methodologies for their efficient identification. Our main focus is on genome-wide analysis of gene expression variation and cellular phenotypes and association with nucleotide variation with a focus on disease susceptibility. We attempt to detect functional genetic variation in regulatory elements and subsequently use regulatory variation and accurately measured gene expression variation to bridge the genotype with disease phenotypes in association studies.
We are a diverse group of scientists of different experience and backgrounds, with a shared focus on understanding how spatial, environmental and health data can be combined to provide insights into disease mechanisms and etiologies.