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Meeting your bioinformatics needs
From one-off services to long-term collaborative support
Our approach: collaborative, independent and reliable
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Biostatistics & bioinformatics analysis
Biostatistics and bioinformatics analysis
Making sense of life science data

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:

  1. molecular imaging analysis;
  2. de novo assembly of sequencing data;
  3. genome comparative data analysis;
  4. targeted, exome and whole genome sequencing analysis;
  5. metagenomic data analysis;
  6. pathway and transcriptional regulatory network analysis (functional analysis);
  7. omics analysis;
  8. data integration;
  9. data visualization;
  10. gene prediction and annotation;
  11. machine learning.

The analysis service you are looking for is not listed? Please get in touch with us, as we might be able with other specific needs.

Case study: Fostering precision medicine through multi-omics data integration
→ Your challenge: Integrating and translating multi-omics big data into functional insights requires specific expertise.
→ Our solution: Through our innovative multi-omics analysis expertise, we combine powerful data integration to help you improve prevention, early detection and prediction, monitor progression, and design personalized treatments. For instance, we used innovative multi-omics analysis integrating lipidomics, transcriptomics and clinical data to identify potential biomarkers of Type 2 diabetes.
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Case study: Environmental metabolic foot printing to characterize the environmental impact of (bio)pesticides
→ Your 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 (follow-up of a PhD thesis).

Case study: Whole genome sequencing analysis to characterize fungal pathogens in different environments
→ Your 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.

In practice:

Development of an integrative solution for the phenotypic analysis of tumors powered by automated multiplex staining, image analysis and machine learning. With Lunaphore and the Geneva University Hospitals (HUG), as part of an Innosuisse.

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Development of a method for interpreting gene expression data with metabolic models which has helped to identify key genes in obesity-related inflammation in adipose tissue

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Integrative analysis of mouse and human lipidomics data which led to the discovery of novel lipid biomarker candidates for Type 2 diabetes. IMIDIA pan-European project.

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Transcript assembly and functional characterization of heart specific lncRNAs in collaboration with the University of Lausanne Medical School.

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Transcriptomics data analysis from muscle biopsies in a human clinical trial investigating the effect of dietary supplementation with Urolithin A, a pomegranate metabolite, on muscle function. In conjunction with EPFL and its spin-off, Amazentis.

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Data management
Data stewardship and management
Organizing data for long-term reuse

We assist you by:

  1. defining and implementing your Data Management Plans (DMP) for research proposals and funding applications;
  2. reaching data interoperability targets, from local to international scales, within academic or regulated environments;
  3. extracting, reformatting and migrating patient-related data between systems in clinical set-ups, to ensure data consistency and query traceability;
  4. ensuring the long-term management and storage of biological data.

Case study: Making your data FAIR to let you focus on what you do best: research and discovery
→ Your challenge: Increasing the reliability in data analysis, and the innovation potential through well annotated data and reproducibility. Companies, universities, funders, datasets managers, and publishers are increasingly expecting data to be FAIR.
→ Our solution: Whatever biological or biomedical data you have, we have a proven expertise in making them FAIR and packaging them in a publication-ready way. This is what we do as part of a number of endeavours, such as several Innovative Medicines Initiative projects on diabetes, cancer, arthritis, as well as others projects dealing with multiple -omics or data from diverse biological origin (e.g. plants, bacteria, fungi).
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Case study: Harmonizing your datasets to advance healthcare
→ Your challenge: Internal resources are lacking to standardize multiple datasets in order to aggregate them.
→ Our solution: We organize large databases containing routine health information, clinical trial or research datasets to enable you to merge them with public datasets.

Case study: Supporting the identification of anti-infective and pro-metabolic natural products 
→ Your challenge: Integrate large volumes of heterogenous in silico and chemo-biological data to enable their sharing between partners and subsequent data analysis.
→ Our solution: We build an RDF database that integrates and centralizes data from all partners, and allows data management and sharing following FAIR principles. We enable access of all partners to the resulting database through the development of a user-friendly web page. This is what we are doing as part of a Sinergia project led by the University of Geneva and the ETH Zurich for instance, with the creation and mining of a library of more than 15,500 plants to find new molecules to treat tuberculosis infection as well as obesity and their associated co-morbidities.

In practice:

Acting as a Data Coordination Centre in European public-private partnerships to fight disease :

  1. Set-up of a federated data analysis system across multiple countries to enable access to large patient cohorts while addressing legal, ethical and FAIR principles (read more and watch the video).
  2. Set-up of a database of ~100 pooled clinical trials as part of the IMI Hypo-RESOLVE consortium. The work has involved setting up ETL (extract, transform, load) pipeline for feeding trial data into a secure Oracle database and the creation of a virtual analysis environment accessible via remote desktop and secured by 2 factor authentication.

Implementing semantic and technical interoperability within the Swiss Personalized Health Network (SPHN) initiative, aiming to make data from consenting patients available securely to researchers from across Switzerland’s hospitals and universities.

Making the human protein interaction dataset curated by ENYO Pharma easily accessible to all and FAIR, through data integration into the open data resource neXtProt.

Secure services for sensitive data
Sensitive data sharing
Enabling research on human data

Biomedical research, and in particular personalized health research, relies on a critical mass of heterogenous sensitive data from patients or clinical trials spread across institutions and sometimes countries. We draw on our extensive experience in large European public-private consortia and national initiatives to enable the secure sharing of interoperable data.

Case study: Enabling “Sharing without sharing” of sensitive health data in biomedical research
→ Your challenge: Making sensitive patient data accessible for biomedical research in accordance with specific regulatory frameworks.
→ Our solution: We help you achieve greater value in your health research projects by analysing sensitive data collaboratively and safely using our innovative federated database for remote analysis. This approach enables researchers to access data without physically sharing it.
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In practice:

Set up of a federated database for biomarker discovery in type 2 diabetes (T2D) as part of the pan-European RHAPSODY consortium. In this database, 10 observational clinical cohorts with a combined total of 50K patients were standardized, harmonized and made available for statistical analysis. We developed data mining and statistical tools in an analysis package for researchers to use within the consortium.

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Secure data management platform for tumour exome sequencing and imaging data as part of the pan-European IMMUcan consortium which we co-lead.

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Swiss Pathogen Surveillance Platform: we have developed the Swiss Pathogen Surveillance Platform to enable national near real-time sharing of pathogen whole genome sequences and their associated clinical/epidemiological metadata for surveillance of outbreaks. In particular, standardization, curation and sharing of national SARS-CoV-2 genomic data for surveillance and Open Science databases access
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Hundreds of clinical trials transferred and hosted onto a secure central server, in the context of the Hypo-RESOLVE pan-European project – supported by the Innovative Medicines Initiative (IMI) and including 23 leading academic experts, pharmaceutical and device manufacturers, as well as patients’ organizations – to find better solutions to alleviate the burden and consequences of hypoglycaemia, a common and serious complication of diabetes.

Secure Data Processing Platform: set-up by SIB as part of the nationwide secure infrastructure enabling the exchange of biomedical data between health institutions across Switzerland and researchers. This infrastructure has been set up as part of our BioMedIT Project in the context of the national initiative for personalized health, SPHN.

Secure services for sensitive data
Knowledge representation
Bringing more meaning to data

Get novel and faster insights by accessing the big picture of the available data, through intuitive queries across interconnected datasets. Make your data more useful through rich semantics. Boost its visibility by following best practice standards for data interoperability, sharing and publication. Our expertise in knowledge graphs, ontology engineering and software development acts as an accelerator for data preparation, integration and FAIRification.

Case study: Connecting data silos across groups and countries in today’s pharmaceutical and crop protection industries
→ Your challenge: Homogenizing data access and meaning in corporations and multisite organizations without modifying or replicating the original data sources are important requirements to accelerate the discovery process.
→ Our solution: A federated data integration architecture within an industrial setup, that relies on an ontology-based data access method.
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Case study: From plants to digital libraries of chemical compounds
→ Your challenge: Going from physical objects (e.g., plants in a botanical garden) to digital resources by applying best practices for data sharing and (re)use. Define relevant metadata, ontologies and cross-references to existing relevant resources.
→ Our solution: We help you to define proper metadata and ontologies, and to interlink your digital objects with most relevant and authoritative resources related to the field. We are for instance bringing this expertise to the Digital Botanical Gardens Initiative, to digitalize chemical and biological diversity.
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Case study: Leveraging knowledge graphs to enable AI-based predictions
→ Your challenge: Making your dataset available for semantic search interfaces and for integration into Artificial Intelligence (AI) models to derive new insights.
→ Our solution: We support you in making your datasets available as interoperable knowledge graphs through public SPARQL endpoints. We also assist you in federating and integrating datasets with existing knowledge graphs, for example using graph neural networks to predict new connections from the original data. We recently deployed one such model leveraging RDF data from the leading Open Science resources STRING (protein-protein interactions) and OMA (orthology), developed by SIB.
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Software engineering & tailoring
Software development
Developing engaging and customized tools

Our experts harmonize and optimize internal data handling processes through the customization and development of analysis pipelines or software tools. This includes multi-site data processing tracking pipeline, diagnostic tools and more. Our teams also contribute to some of the world-leading Open Science databases and tools for life sciences which can be adapted to your in-house needs.

Case study: Clinical software development
→ Your challenge: Robust and user-friendly software is required for data collection in routine laboratory activities. Your analytical processes may be relying on a range of disconnected tools developed over the years, that slow down your research. But creating a complete software solution for collecting, processing, analysing and visualizing your data may not be your core business.
→ Our solution: With our agile, iterative and collaborative approach, we can build a proof of concept with a powerful prototype, before embarking on a full-scale development project.
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In practice:

Oncobench ®: together with the Geneva University Hospitals, we launched a user-friendly platform that streamlines and automates the analysis of patient tumour DNA for cancer diagnosis, while ensuring the privacy of the patient’s data. Read about the latest key development of the platform.

Melanie: our commercial off-the-shelf software for the analysis of 2D electrophoresis gel and blot images, supporting the discovery of protein biomarkers, monitoring the adaptation of organisms to their environment, development of diagnostic tests, quality control of food samples, and development of HCP ELISA tests (choice and validation of immunoassay reagents).

Expert biocuration
Expert biocuration
Generating high-quality, up-to-date annotations

Our biocuration experts excel in the art of generating and representing knowledge from a growing body of publications and on various data types including proteomics, lipidomics and transcriptomics. This includes help with setting up expert-¬annotated resources for a wide range of applications, such as understanding protein function, facilitating clinical interpretation of cancer variants or enabling biomarker discovery. Read more

In practice:

Our Swiss-Prot team provides the manually annotated section of UniProt, the world-leading protein information resource (together with EMBL-EBI and PIR) accessed by thousands of users every day.

The Swiss Variant Interpretation Platform aims to harmonize the interpretation of genetic variants across Swiss hospitals, and will combine clinical data from hospital partners with publicly available information from international projects (e.g. ClinVar, CIViC) and published literature, sourced by expert biocurators.

The SwissLipids knowledgebase is a comprehensive library of over 500,000 lipid structures enriched with expert-curated information on lipid metabolism, protein interactions and occurrence in organelles, cells, tissues and organs.

Boosting bioinformatics skills

Our comprehensive – and constantly evolving – course portfolio provides hands-on experience of the most up-to-date bioinformatics techniques and resources, including clinical applications for researchers or healthcare professionals. We offer about 100 course-days per year. Gain high-quality introductory and advanced data science expertise in specific area. Our course portfolio can be tailored to meet the needs of your company as private courses, offered on-site or online: find out more about our specific offer for companies.

Case study: Develop programming and data analysis skills in your team
→ Your challenge: Onboarding a group of employees with mixed skills levels in R programming language and RNA-seq data analysis, and on a tight schedule.
→ Our solution: We adapt courses to create a training path adjusted to your schedule constraints and team-specific needs.

In practice:

Certificate of Advanced Studies (CAS) in Personalized Molecular Oncology: First of its kind in Switzerland the CAS aims to establish a common language between the wide range of professionals involved in the personalized oncology process, from biologists and bioinformaticians to pathologists and clinicians. It is co-organized by SIB and the University Hospitals of Basel and Lausanne.

SIB was commissioned by the Food and Agriculture Organization of the United Nations (FAO) and the International Atomic Energy Agency (IAEA) joint programme to produce two e-learning modules, accessible via the dedicated website Viral Zone

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About SIB
The SIB Swiss Institute of Bioinformatics is an academic not-for-profit organization whose mission is to lead and coordinate the field of bioinformatics in Switzerland. Its data science experts join forces to advance biological and medical research and enhance health.
Quartier Sorge - Batiment Amphipole
1015 Lausanne / Switzerland
Tel: +41 21 692 40 50
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