The SIB Swiss Institute of Bioinformatics is an internationally recognized non-profit organization dedicated to biological and biomedical data science. It is present in the main academic institutions of Switzerland and leads numerous national and international projects with a major impact on life science research and health. SIB federates the Swiss bioinformatics community, comprising 88 groups with 900 members, including 190 employees, spread over 28 institutional partners across Switzerland. For 25 years, the SIB has contributed to keeping Switzerland at the forefront of innovation by fostering progress in biological research and enhancing health.
Vital-IT, a highly qualified team of 30 people and one of SIB’s competence centres, provides bioinformatics collaborative support for life science projects in Switzerland and abroad through collaborations with academic and industry partners. Thanks to its diverse expertise in computational biology, data management and software engineering, the team helps finding custom-made solutions to answer complex biological questions including biomedical & omics data. Partners benefit from Vital-IT’s commitment to advancing science effectively and independently.
We strive to establish partnerships: even for one-off collaborations, we seek to deeply understand the data and the objectives of the project we work on. Our partners appreciate our reliability, commitment, and team spirit. The group’s track record spans biomedical research projects of different sizes – from punctual help to long-term European projects.
Our flexibility and independence allow us to tailor efficient solutions and propose advisory services to each situation. For example, a collaboration can be customized to include our partner’s own ontologies, provide support to validate internal approaches or integrate large and complex amounts of data of various types and origins.
We train both beginners and experts in bioinformatics methods, languages, and best practices.
As associated partner within the ENDOTARGET project, SIB-Vital-IT is leading Work Package 5 – “Data management, multi-omics modelling and AI”.
At first, clinical, genomic, metabolomic, metagenomic and lifestyle data will be extracted from population cohorts and the quality of the data will be checked and assessed. Together with UTARTU, NEC and clinicians in WP1, we will define a common set of desired variables and data types to be prepared for subsequent analysis.
We will then perform a series of analyses to find which data types and features, when combined, are mostly predictive of an outcome, e.g., health to disease transition or quality of life. Other analyses will focus on determining risk prediction scores and other predictive risk factors.
Other tasks from WP5 include the use of AI models to find biomarkers and novel intervention strategies, which will help us to develop a RDPT-Rheumatic disease web-based prediction tool for clinicians.
SIB-Vital-IT is also leading task 1.4 “Microbiota associated with systemic endotoxemia” of Work Package 1.
In close collaboration with HUS and ETHZ, we will perform a focused analysis, generating statistical models correlating composition of microbiota, systemic endotoxemia (SE), measures of intestinal permeability, and their association with age and risk of developing Rheumatoid arthritis, Spondylarthritis, and osteoarthritis. These models will be used to identify key characteristics of microbiota associated with SE. Bacterial genome sequencing data from pure cultures will be assembled and scanned using comparative genomics to identify operons associated with inflammatory lipopolysaccharides (LPS) production. Such operons could be directly amplified for diagnostic purposes instead of using standard 16S barcoding, as they are likely to correlate better with pro-inflammatory activity.
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