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Tag: biostatistics

  • A new study unravels why partners often share similar traits

    From education to blood pressure, partners in couples often tend to present striking trait similarities. For the first time, the reasons for this are teased apart by SIB’s Zoltán Kutalik and his team.

  • Andreas Ziegler's group

    What we do Cardio-CARE is involved in the pre-processing, quality control and data analysis of high throughput Omics data. Other core competencies include the planning, conduct, and analysis of clinical studies, such as randomized controlled...

  • Raphael Gottardo's group

    What we do The Translational Data Science (TDS) group focuses on developing novel computational tools, statistical methods and machine learning algorithms for the analysis of high-throughput and high-dimensional datasets generated by novel assay...

  • The viral genomics pipeline V-pipe under the spotlight

    From SARS-CoV-2 monitoring to HIV antiviral drug resistance detection, the SIB Resource V-pipe orchestrates several software packages to detect the genomic diversity of a virus population in a sample or individual. 

  • Frédéric Schütz's group

    What we do The Biostatistics platform of the Faculty of Biology and Medicine at UNIL acts as a main entry point for questions related to biostatistics and data analysis. The platform delivers services which cover the entire scientific process...

  • Christian Panse's group

    What we do The responsibility of the proteome informatics at the FGCZ is to evaluate and provide services to the mass spectrometry scientists at our center, ranging from sample annotation, data archiving, processing, analysis, visualization up to...

  • Detecting the environment-genetics interplay for obesity-related traits

    A new open-source method allows to accurately estimate how much of our genome makes us susceptible to environmental risk factors, which in turn predispose us to certain pathologies. The study describing the method, led by the SIB Group of Zoltán...

  • Human ancestors impacted biodiversity much earlier than previously thought

    Human-driven biodiversity declines started much earlier than previously thought: this is what a recent study led by researchers from Switzerland, Sweden and the UK points to. Using fossil records spanning millions of years, the team disentangled...

  • SHAPEIT4: an algorithm for large-scale genomic analysis

    Researchers from UNIL, UNIGE and SIB provide the researchers’ community with an extremely powerful computer tool to facilitate the interpretation of the genome’s Big Data

  • Olivier Delaneau's group

    What we do Our group is interested in the regulatory machinery controlling gene expression. We investigate it by analyzing population scale multi-omics data sets (e.g. genomics, transcriptomics, epigenomics, proteomics) in which we use genetic...

  • Meet the past SIB Awards Laureates – Zoltán Kutalik

    In 2019, the SIB Bioinformatics Awards will be presented for the 10th time, providing a great occasion to reach out to past laureates and ask them where they are now in their career. In this interview, we met with Zoltán Kutalik, recipient of the...

  • Daniel Wegmann's group

    What we do We develop statistical and computational methods to answer biological questions from big data, from genomic sequence data to images. Our work is motivated by both the wealth of biological data currently being generated, as well as by...

  • Daniel Stekhoven's group

    What we do We are the NEXUS Personalized Health Technologies at the ETH Zurich. Our unit offers highly customizable bioinformatics, biostatistics and software engineering services for projects in the field of biomedical research and development....

  • Torsten Schwede - Thierry Sengstag's group

    What we do sciCORE is a center of competence in scientific computing located at the University of Basel. Over 240 research groups and facilities in the fields of bioinformatics, computational chemistry, physics, biology, medicine, and economics...

  • Mark Robinson's group

    What we do In the Statistical Bioinformatics Group, we develop robust data analysis solutions, including new or improved methods, for the analysis of genome-scale data. We develop statistical methods for interpreting data from high-throughput...

  • Tanja Stadler's group

    What we do In the Computational Evolution Group, we develop phylogenetic tools in order to understand evolutionary processes. Using our phylogenetic methods, we aim to improve our understanding of past evolutionary and population dynamic processes...

  • Hubert Rehrauer's group

    What we do We are dedicated to the processing, analysis and interpretation of next-generation sequencing data. We interact closely with research groups, and provide tailored comprehensive bioinformatics solutions. Additionally, we provide standard...

  • Christian Mazza's group

    What we do Mathematical modelling is becoming more and more instrumental in life sciences; the data complexity and the high number of interacting components, from molecules to animals, render intuitive reasoning very difficult. The idea consists...

  • Zoltán Kutalik's group

    What we do In the Statistical Genetics Group, we are interested in the development of statistical methodologies in order to decipher the genetic architecture of complex human traits related to obesity. To do this, we efficiently combine...

  • Robert Ivanek's group

    What we do Our group is located in the Department of Biomedicine (DBM) at the University of Basel. We collaborate with scientists from DBM on projects covering a broad spectrum of research topics, from cellular differentiation and evolutionary...

  • Jérôme Goudet's group

    What we do Our group’s interest is focused on understanding how the interplay of population structure, trait architecture and selection can be disentangled. To this end, we use different approaches, from theory and the development of statistical...

  • Luciano Cascione's group

    What we do The Bioinformatics Core Unit (BCU) supports the research groups at the Institute of Oncology Research (IOR) with computational and statistical services. We focus our research interests on the genetics and biology of cancer with a major...

  • Giovanni Ciriello's group

    What we do The Computational Systems Oncology lab integrates algorithmic design, numerical modelling, and molecular biology approaches to address relevant questions in cancer biology and therapeutics. We explore single and combinations of genetic...

  • Rémy Bruggmann's group

    What we do In the Interfaculty Bioinformatics Unit of the University of Bern (IBU), we provide services and expertise to assist researchers of the three “Life-Science” Faculties and Insel hospital in data analysis and project planning for...

  • Sven Bergmann's group

    What we do We develop concepts and algorithmic tools for the analysis of large-scale biological and clinical data. We participate in many genome-wide association studies (GWAS) for human traits and have a particular interest in the integration of...

  • Niko Beerenwinkel's group

    What we do The Computational Biology Group is involved in research and teaching in the areas of computational biology, biostatistics, and systems biology. We aim at supporting the rational design of medical interventions in complex and rapidly...

  • Katja Baerenfaller'group

    What we do In the Molecular Allergology group we are aiming to unravel the molecular basis of allergic diseases, antigen presentation, immunotherapies, immunotolerance and tolerance breakage with a combination of functional genomics techniques,...

Courses:

  • First Steps with R in Life Sciences

    This 2-day course will introduce participants to R syntax, the Rstudio environment, and to the use of R to explore and interpret data.

  • Introduction to Statistics with Python

    This 2-day course for life science researchers introduces statistics, statistical concepts and their application to a variety of problems using Python.

  • Enrichment Analysis

    This 1 day course will cover Gene Set Enrichment Analysis to identify groups of genes, alternative enrichment tools, and also GO enrichment analysis.