We manage, integrate and analyse all kinds of life science data from different technologies to enable discoveries, from biomarkers to drug repurposing. Here are some of our specific areas of expertise:
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molecular imaging analysis
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de novo assembly of sequencing data
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targeted, exome and whole genome sequencing analysis
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genome comparative data analysis
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metagenomic data analysis
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pathway and transcriptional regulatory network analysis (functional analysis)
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omics analysis
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data integration
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data visualization
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gene prediction and annotation
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machine learning
Fostering precision medicine through multi-omics data integration
The challenge
Translating multi-omics big data into functional insights to allow prevention, early detection and prediction of diseases, monitor their progression, and design personalized treatments.
Our solution
We conduct powerful data integration through our innovative multi-omics analysis expertise. For instance, in the Rhapsody European project, we integrated lipidomics, transcriptomics and clinical data to identify potential biomarkers of Type 2 diabetes.
Environmental metabolic foot printing to characterize the environmental impact of (bio)pesticides
The challenge
Estimate the resilience time of exogenous metabolites in soil treated with a pesticide, synthetic or derived from natural materials.
Our solution
We perform model kinetics of liquid chromatography-mass spectrometry (LC-MS) features from untargeted metabolomics data to predict the dissipation of those coming from the treatment. For instance, we collaborate with the University of Perpignan (France) to follow the fate of a soil treated with a plant extract.
Whole genome sequencing analysis to characterize fungal pathogens in different environments
The challenge
Identify the genomic heterogeneity among multiple micro-organisms.
Our solution
We perform de novo genome assembly, gene annotation, and variant detection on different isolates of fungal species with whole genome sequencing data. We are collaborating with the Lausanne University Hospital (CHUV) for studies on Candida species.
