Quantitative Biology Center

QBiC TechTalk Episodes

The QBiC tech-talks focus on technical aspects in quantitative biology. They are providing insights in innovative technologies, methods and applications in life science. Experts with an intensive research background and/or are have their focus on services in quantitative biology will present the modern fields in quantitative biology.


  • Dr. Evangelina López de Maturana and Dr. Sergio Sabroso, 31.05.2022, 16:00-17:00, Online via Zoom and
    Youtube, “Integration of multi-omics and non-omics data: AI approaches and challenges

    Abstract:During the last years, a plethora of cancer-specific data generated by high-throughput biotechnological platforms along with clinico-pathological information are being generated and available on-line, facilitating the investigation of cancer biology or classification of patients, among other aims. However, the majority of the studies have used unimodal approaches, missing the opportunity of integrating data of different nature.

    Motivations for data integration include extracting knowledge for various purposes by exploiting the complementary nature of multimodal data, obtaining a more unified and global view of the systems and improving decision-making. However, integrating multimodal data is a challenging task because the data generation processes may be heterogenous, there may be numerous underlying processes depending on unavailable variables and the sparsity of most medical datasets.
    In this webinar, we will discuss modern machine learning techniques to integrate omics (genomics, transcriptomics, radiomics and pathomics) and non-omics (demographical and clinico-pathological) data to improve PC patient diagnosis, prognosis stratification and treatment response dealing with the aforementioned challenges.

  • Prof. Dr. Giovanni Maglia, 22.03.2022, 16:00-17:00, Online via Zoom and
    Youtube, “Single-molecule nanopore proteomics

    Proteins form the basis for life. To understand these biological processes and their (dys)regulation in health and disease it is critical to decode the cellular language of proteins. However, it is now becoming evident that resolving the proteome remains an enormous challenge in biology that might only be solved by developing new technologies capable of single-molecule protein analysis.

    Biological nanopores are single-molecule sensors that are now used to sequence DNA at the single-molecule level. Protein analysis, however, has been challenged by the heterogeneous structure and non-uniform charge of proteins, which complicates their electrophoretic capture and translocation by nanopores. Here, I will show our recent efforts in designing new nanopores to control the unfolded translocation of proteins across a nanopore, and how to engineer nanopores to capture and characterize single proteins or peptides. These nanopores have application in the identification of protein isoforms, and will provide unique tools for single-molecule proteomic analysis.

  • Lorenz Lamm, 20.09.2022, 16:00-17:00, Online via Zoom and
    Youtube, “MemBrain: A deep learning-aided pipeline for detection of membrane proteins in Cryo-electron tomograms

    Cryo-electron tomography (cryo-ET) enables 3D visualization of the native cellular environment at sub-nanometer resolution. However, cryo-electron tomograms suffer from low signal-to-noise ratios and anisotropic resolution, which makes subsequent image analysis challenging. In particular, the detection of membrane-embedded proteins is a problem still lacking satisfactory solutions: Classical computer vision approaches, like template matching or PySeg either require manual guidance, or can struggle detecting the embedded proteins at all.

    MemBrain is a deep learning-aided pipeline that automatically detects membrane-bound protein complexes in cryo-electron tomograms. To simplify the detection task, MemBrain samples subvolumes along a segmented membrane and aligns them. Thus, while other state-of-the-art DL approaches – e.g., DeepFinder – require large annotated tomogram regions, MemBrain is very annotation-efficient and gives good results with already a single annotated membrane. In addition to protein positions, MemBrain can also estimate particle orientations for certain particle shapes, which is beyond the capabilities of other DL methods for Cryo-ET.


  • Prof. Joakim Lundeberg, 23.09.2021, 16:00-17:00, Online via Zoom and
    Youtube, "Exploring the spatial omics landscape in normal tissues and disease"

    The cell is a fundamental unit of life, yet we know surprisingly little about them. Specific types of cells exist in every organ, and serve specialized functions defined by the specific genes and proteins active in each cell type. Comprehensive maps of molecularly defined human cell types are underway through the Human Cell Atlas (https://www.humancellatlas.org) effort using primarily single cell RNA sequencing as foundation. The technologies to assemble spatial tissue maps of transcription that will describe and define the cellular basis of health and disease is less well clear. We have developed and established the Spatial Transcriptomics technology (aka Visium), in which tissue imaging is merged with spatial RNA sequencing and resolved by computational means. Spatial Transcriptomics technology was the first method to provide unbiased whole transcriptome analysis with spatial information from tissue using barcoded array surfaces and has since the initial publication been used in multiple biological systems in health and disease. Data from our ongoing projects will be presented together with description of future drivers of spatial technologies.

  • Dr. Malte Luecken, 09.09.2021, 16:00-17:00, Online via Zoom and
    Youtube, "Integrating diverse single-cell datasets: a consistent view of the healthy human lung"

    The human cell atlas consortium has promoted the generation of single-cell atlases of healthy human tissues. Each generated dataset represents a particular view of a tissue with its own share of signal and bias. The true distribution of healthy tissue cells can only be approximated by combining the available datasets. However, complex batch effects between individual datasets complicate the generation of a joint representation of the data. Thus, data integration has been named as a "grand challenge" of single-cell research. In this talk, I will show how data integration methods can be used to generate a consistent representation of a healthy tissue using the human lung as an example. Building upon our benchmark of data integration methods, we have built the first version of the integrated human lung cell atlas. I will showcase how this atlas consolidates cellular identity, identifies areas of further research, and is a powerful tool for the analysis of new lung data by acting as a reference.

  • Dr. Venera Weinhardt, 06.05.2021, 16:00-17:00, Online via Zoom and Youtube, "Correlated light and soft x-ray microscopy of single cells"

    The structure of a cell is crucial to its identity, function and health. A great deal has been learned about how a cell's structure arises from light and electron microscopy. Yet despite advances of these imaging techniques for volumetric imaging, we still have only a limited ability to observe structural changes of individual whole cells at statistically significant sample sizes. Our group and other labs are attempting to overcome these limitations through the development of a single-cell 3D imaging technique – called soft x-ray tomography – which can examine intact cells without labelling or fixation, at high throughput and spatial resolution. As the most comprehensive view of a cell is unlikely to come from a single microscope, I will talk on advances of soft x-ray microscopy and the effort to combine it with cryogenic fluorescence microscopy to obtain physiological and morphological data that more accurately reflect the complexities of single cells.

  • Olga Botvinnik, PhD, 18.03.2021, 16:00-17:00, Online via Zoom and Youtube, "Single-cell transcriptomics for the 99.9% of species without reference genomes"

    Single-cell RNA-seq (scRNA-seq) is a powerful tool for cell type identification but is not readily applicable to organisms without well-annotated reference genomes. Of the approximately 10 million animal species predicted to exist on earth, >99.9% do not have any submitted genome assembly. To enable scRNA-seq for the vast majority of animals on the planet, here we introduce the concept of “k-mer homology,” implemented as the Nextflow pipeline kmermaid, to directly detect orthologous genes from transcriptomic data without the need for a reference genome. Underpinning kmermaid is the tool orpheum, a memory-efficient method for extracting high-confidence protein-coding sequences from RNA-seq data. To represent fragments of orthologous genes, k-long amino acid words or kaa-mers are subsampled from the protein sequences. To retain evolutionarily conserved biochemical properties, kaa-mers are converted into degenerate amino acid alphabets, representing each cell in a common feature space of amino acid words, allowing for direct comparison across millions of years of evolution. After validating kmermaid between human and mouse lung, we applied kmermaid to the Chinese horseshoe bat (Rhinolophus sinicus), where we detected granzymes and other immune genes not present in the bat genome assembly. By enabling analyses across divergent species’ transcriptomes in a genome-, gene annotation-, and orthology-agnostic manner, kmermaid and orpheum can identify cell type-specific sequences that may be missing from genome annotations and empower molecular cellular phenotyping for novel model organism species.

  • Dr. Radovan Bast, 28.10.2021, 16:00-17:00, Online via Zoom and
    Youtube, “Next steps to FAIRifying coding in an academic setting

    CodeRefinery is a project which supports students and researchers across all academic disciplines by advancing the FAIRness of research software and development practices so that they can collaboratively develop, review, discuss, test, share, and reuse their codes. This initiative teaches which software is needed but is often missed in a traditional university curriculum. Thus far, over 1500 researchers from the Nordic countries have been trained, and with the received follow-up funding, the plan is to turn this project into a sustainable organization reaching beyond the Nordics. During this presentation, he will touch upon the knowledge that was acquired as well as the focus of the collaborative co-teaching approach to reach 100 participants per event. Furthermore, the plans of the CodeRefinery project and its support will be discussed.


  • Dr. Gary Bader, 05.11.2020, 15:00-16:00, Online via Zoom and Youtube, "Systems biology from single cell genomics to network data integration"

    Topic 1 
    Single-cell RNA sequencing (scRNAseq) can map cell types, states and transitions during dynamic biological processes such as development and regeneration. Many trajectory inference methods have been developed to order cells by their progression through a dynamic process. However, when time series data is available, these methods do not consider the available time information when ordering cells and are instead designed to work only on a single scRNAseq data snapshot. We present Tempora, a novel cell trajectory inference method that orders cells using time information from time-series scRNAseq data. In performance comparison tests, Tempora accurately inferred developmental lineages in human skeletal myoblast differentiation and murine cerebral cortex development, beating state of the art methods. Tempora uses biological pathway information to help identify cell type relationships and can identifyimportant time-dependent pathways to help interpret the inferred trajectory. Our results demonstrate the utility of time information to supervise trajectory inference for scRNA-seq based analysis.
    Topic 2
    Biological networks have the power to map cellular function, but only when unified to overcome their individual limitations such as bias and noise. Unsupervised network integration addresses this, automatically weighting input information to obtain an accurate, unified result. However, existing unsupervised network integration methods do not adequately scale to the number of nodes and networks present in genome-scale data and do not handle frequently encountered data characteristics (e.g. partial network overlap). To address this, we have developed an unsupervised deep learning-based network integration algorithm that incorporates recent advances in reasoning over unstructured data – namely the Graph Convolutional Network (GCN) – that can effectively learn dependencies between physical, co-expression and genetic interaction network topologies. Our method, BIONIC (Biological Network Integration using Convolutions), produces high quality gene and protein features which capture and unify information across many diverse functional interaction networks. BIONIC learns features which contain substantially more functional information compared to existing approaches, linking genes and proteins that share co-complex, pathway and bioprocess relationships.
  • Dr. Kenneth Berendzen, 08.10.2020, 16:00-17:00, Online via Zoom and Youtube, "Using flow cytometry in plant science: advantages and limitations"

    Flow cytometry is a technique whereby cellular components and states can be measured directly in whole cells using fluorescence techniques. By nature, flow cytometry consists of multi-dimensional data which is traditionally broken down into two-dimensional bivariate plots. While flow cytometry has been applied to plant science since its inception, its use is still not as widespread as that in animal science. This talk aims at introducing flow cytometry and its applications routinely used in plant sciences.
  • Dr. Evangelia Petsalaki (EMBL-EBI, UK), 10.09.2020, 16:00-17:00, Online via Zoom and YouTube, "Integrative studies of context-specific signalling"

    Our group aims to understand and describe the organisation principles of cell signalling that allow the diverse and context-specific cell responses and phenotypes. It is well established that signalling responses happen through complex networks. However, most signalling research still uses linear pathways as the ground truth. Moreover, signalling responses are highly dependent on context, such as tissue type, genetic background etc and therefore these static pathways are not always suitable. There is also a high bias in the literature towards kinases and pathways for which reagents and prior knowledge is readily available. This leaves a huge dark space in our understanding of cell signalling and significantly hinders studies of its general principles. Data-driven methods to study cell signalling using phosphoproteomics have typically been developed on transcriptomics data. Due to fundamental differences of these data types, including the sparsity of phosphoproteomics, these methods perform poorly on signalling network inference. Finally, large-scale essentiality datasets that can shed light on the context in which different signalling-related genes and pathways are crucial have thus far been severely underused in largescale omics data integrative efforts, likely due to their inaccessibility to non-expert users.

    In this talk I will present two projects where we try to mitigate some of the above issues. For the first one I will present a method for data-driven machine-learning-based approach that takes advantage of global phosphoproteomics datasets to predict kinase regulatory networks, including their direction and sign of regulation. Our predicted kinase regulatory network is able to recapitulate known signalling pathways and agrees with orthogonal validation datasets. We were able to provide predictions for a large fraction of the understudied kinase space and found that kinase regulatory networks are denser than previously suspected.
    For the second one I will present CEN-tools, an integrative webserver and python package, that allows users to navigate the contexts of different gene essentialities. I will demonstrate examples of its use in discovering new gene-gene relationships and important putative signalling targets for different cancers.
  • Natalie Krieger, Sven zur Oven-Krockhaus, 04.06.2020, 16:00-17:00, Online via Zoom and YouTube, "Application of optical microscopy methods in plant biology"

    The visibility of organs, cells, subcellular structures, or even the subcellular localization of proteins is becoming more and more important in cell biology and can be achieved by the use of different microscopes and microscopy techniques. In contrast to mammalian cells, living plant cells possess subcellular structures causing strong autofluorescence background and make the spectral separation of the fluorophore of interest challenging.
    To analyze the variety of plant samples, there are, in addition to “common” widefield microscopes, three confocal laser scanning microscopes available at the Centre for Molecular Biology of Plants (ZMBP) at the University of Tübingen. These confocal laser scanning microscopes (CLSM) allow higher resolution not only of fixed but also of living cells. Equipped with add-ons, these CLSM allow a subset of spectro-microscopy techniques based on fluorescence to analyze the interaction behavior of proteins/molecules in living plants. Furthermore, the usage of deconvolution software and/or specialized detectors allow the visualization of samples beyond the resolution limit.
    In addition to these commercial instruments, a self-built microscope for special techniques is also available, which was designed and built in cooperation with the Institute for Theoretical and Physical Chemistry. On the one hand, this has the advantage that new or modified techniques can be quickly tested and evaluated, and on the other hand, the microscopy methods can be adapted to the specific requirements of plant samples.
    Our research with this instrument currently focuses on the use of so-called super-resolution techniques to visualize structures beyond the optical diffraction limit (200 nm). In particular, we are investigating the dynamics of receptor complexes in living plant membranes, which will be demonstrated with a few examples.
    The evaluation of the large data sets generated by super-resolution techniques and the optimization of measurement parameters can significantly benefit from the use of modern computational strategies, including deep-learning-based frameworks and machine learning. This synergy will likely play an increasingly important role not only here, but in all biomedical imaging procedures in the future.
  • Jerven Bolleman, 20.05.2020, 15:00-16:00, Online via Zoom and YouTube, "Interoperabilty in the sciences: it is in the semantics"

    FAIR you should have heard of it by now ;) Findable, Accessible, Interoperable and Reusable. Lofty goals, which sound grandiose, but are actually grounded in technical realities. The SIB Swiss Institute of Bioinformatics, as a confederation of independent research and service groups covering wide areas of interests, is always trying to meet those goals. The pragmatic bottom up choice by a number of SIB groups is to use RDF and SPARQL to achieve more Interoperable and Reusable data resources. RDF is a knowledge representation framework, while SPARQL is a graph query language that allows for federated querying. There will be a demonstration using Rhea, Hamap and UniProt as examples of how this plays out in practice. With a small hint on how these resources are interoperable with data sources outside of the life sciences such as the European Patent Office datasets.Many of the technologies we choose are great at answering certain questions, yet are extremely inflexible. Leading to high (re)development costs and too little data integration. This is not required and we can do better together. An example is SpOdgi, which takes a highly compressed Odgi genome variation graph and presents it as a SPARQL/rdf graph database in less than 900 lines of code. SpOdgi is used to link 1000+ SARS-CoV-2 genomes with UniProt, Bgee, Oma, Rhea, and  NeXtProt into one knowledge graph at https://covid-19-sparql.expasy.org/.

  • Dr. Benjamin Schubert, 06.02.2020, 16:00-17:00, Lecture hall: 7E02, Auf der Morgenstelle 16, 72076 Tübingen
    "Computer-aided Vaccine Design: How Algorithms can help during the Selection and Assembly of Epitope-based Vaccines"


  • Dr. Markus List, 12.12.2019, 16:00-17:00, Lecture hall: N2, Auf der Morgenstelle 16, 72076 Tübingen
    "Analysing large-scale epigenomic data"

    Large amounts of epigenomic data are publicly available, yet their retrieval for downstream analysis is a research bottleneck. Typically, users download huge files that span the entire genome, even if they are only interested in a small subset (e.g. promoter regions) or an aggregation thereof. Moreover, complex operations on genome-level data are not always feasible on a local computer due to resource limitations. The DeepBlue Epigenomic Data Server mitigates this issue by providing a powerful programmatic API that can be accessed by data analysts and software tool developers. To optimally support biomedical researchers, we also provide DeepBlueR, an extensively documented Bioconductor R package and present typical analysis work-flows. While a majority of DNA methylation based studies focus on average methylation levels, we also show that bisulfite sequencing data uniquely enables us to capture intra-sample DNA methylation heterogeneity.

  • Dr. Angel Angelov, 14.11.2019, 16:00-17:00, Lecture hall: N2, Auf der Morgenstelle 16, 72076 Tübingen
    "Basecaller accuracy in Nanopore sequencing"

    In Nanopore sequencing, basecalling is the computational process of translating raw electrical signal (squiggle) to nucleotide sequence. Basecalling is therefore a key factor determining usability and acceptance of Nanopore sequencing in the scientific community. Oxford Nanopore Technologies (ONT) have recently released a new basecalling algorithm (called flip-flop), which promised a much better read accuracy than the default one.
    In this talk, I will present a comparison of the basecalling accuracy of the default and the flip-flop algorithms, using a real-life bacterial genome sequencing dataset from our lab. The implications of using better basecallers on the accuracy of bacterial genome assemblies will be discussed, as well as the perspectives of using Nanopore-only data to obtain near-complete, error-free bacterial whole genome sequences.  

  • Prof. Dr. Chris-Carolin Schön, 24.01.2019, 16:15-17:15, Lecutre hall: 7E02, Auf der Morgenstelle 16, 72076 Tübingen
    "Accuracy of genomic prediction in structured plant populations"

    Most traits of importance in plant and livestock breeding are regulated by many genes and follow a quantitative distribution. The assessment of these quantitative traits in performance tests is costly and time consuming. Thus, prediction of the genetic potential of individuals from their DNA sequence is highly desirable.
    This talk will present advancements in genome-based prediction using genomic, phenotypic and genealogical data. Statistical models for prediction of genetic values and phenotypes will be introduced. I will discuss challenges arising from the high- dimensional nature of genomic information as well as from the large genetic diversity and genome complexity of maize. The effect of integrating knowledge on marker-trait associations from functional or QTL studies and the role of feature selection for improving prediction accuracy will be shown. Factors driving prediction accuracy besides ancestral relatedness will be presented for traits of different genetic architecture. How to make best use of the massive collections of genomic and phenotypic data not only for prediction of phenotypes but also to understand the genetic architecture of complex traits and genetic phenomena such as epistasis and pleiotropy will be discussed.


  • Dr. Phil Ewels, 08.03.2018, 16:00-17:00, Lecture hall: N2, Auf der Morgenstelle 16, 72076 Tübingen, “Standardising Swedish genomics analyses at SciLifeLab NGI”

    The SciLifeLab National Genomics Infrastructure is one of the largest sequencing facilities in Europe. We are an accredited facility providing library preparation, sequencing, basic analysis and quality control for Swedish research groups. Our sample throughput requires a highly automated and robust bioinformatics platform.
    In this talk I will describe how we handle data flow, analysis and quality control. I'll describe our work with tools such as Nextflow and MultiQC; some of our pipeline projects for Cancer analysis and RNA; and touch on some upcoming projects such as MegaQC and nf-core.

  • Holger Gantikow, 20.09.2018, 16:00-17:00, Seminar room D4A19, D-Bau, Auf der Morgenstelle 16, 72076 Tübingen, “Linux Containers for HPC - Container Technology/Engine Architecture 101”

    Container technology has not only spread in "normal" IT in recent years, but has also established itself as an important basic component in the field of High Performance Computing (HPC). However, here Docker is not the omnipresent solution, but there are a number of alternatives that can often be better integrated into existing HPC environments. The presentation will introduce which problems of HPC can be mitigated with containers and will refresh which technologies are based on containers.


  • Dr. Thomas Soddemann, 25.02.2016, 16:00-17:00, Lecture hall: N1, Auf der Morgenstelle 16, 72076 Tübingen, “Compute Intensive Applications: fast everywhere” (Fraunhofer Institute for Algorithms and Scientific Computing SCAI)

  • Dr. Dieter Beule, 03.03.2016, 16:00-17:00, Lecture hall: N1, Auf der Morgenstelle 16, 72076 Tübingen, "Tools Selection for Neo-Epitope Selection" (Berlin Institute of Health)

  • Prof. Dr. Frank Oliver Glöckner, 17.08.2016, 11:00-13:00, Lecture hall: N1, Auf der Morgenstelle 16, 72076 Tübingen, "The German Federation for Biological Data (GFBio): Services for Data Management and Long-term Archiving” (Head of the Microbial Genomics and Bioinformatics Research Group, Max Planck Institute for Marine Microbiology, Jacobs University Bremen gGmbH)


  • Prof. Guowang Xu, 09.04.2015, 16:00-17:00, Lecture hall: N1, Auf der Morgenstelle 16, 72076 Tübingen, "Liquid chromatography – mass spectrometry methods for lipidomics” (Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China)

  • Dr. Nico Pfeiffer, 30.06.2015, 16:00-17:00, Lecture hall: N1, Auf der Morgenstelle 16, 72076 Tübingen, “Machine Learning for Personalized Medicine: How to Integrate and Interpret Data from Different Molecular Measurements” (MPI für Informatik, Saarbrücken)

  • Dr. Anne Zeck, 12.11.2015, 16:00-17:00, Lecture hall: N1, Auf der Morgenstelle 16, 72076 Tübingen, "Mass spectrometry of intact proteins for quality control and biological function elucidation” (Natural and Medical Sciences Institute (NMI), Reutlingen)


  • Dr. Thomas Joos, 01.01.2014, 16:00-17:00, Lecture hall: N2, Auf der Morgenstelle 16, 72076 Tübingen, "Immunoassays in Multiplex for Biomarker Discovery and Validation” (Deputy Managing Director, NMI Natural and Medical Sciences Institute at the University of Tübingen)

  • Prof. Rainer Bischoff, 22.05.2014, 16:00-17:00, Lecture hall: N1, Auf der Morgenstelle 16, 72076 Tübingen, “Biomarker Discovery and Validation” (University of Groningen, Department of Pharmacy, Analytical Biochemistry, 9713 AV Groningen, The Netherlands)

  • Prof. Dr. Christoph Borchers, 15.08.2014, 16:00-17:00, NMI Reutlingen, Markwiesenstraße 55, 72770 Reutlingen, "MRM and iMALDI, two emerging mass spectrometric approaches for biomedical and clinical research“ (University of Victoria, BC, Canada)

  • Dr. Oliver Schilling, 11.12.2014, 16:00-17:00, Lecture hall: N1, Auf der Morgenstelle 16, 72076 Tübingen, "How to use proteomics to investigate protease substrates and specificity"
    & Dr. Lars Nilse, “Reliable Peptide Quantification” (Institute of Molecular Medicine and Cell Research, University of Freiburg)


  • Prof. Detlef Weigel, 18.04.2013, 16:00-17:00, Lecture hall: N1, Auf der Morgenstelle 16, 72076 Tübingen, "Next generation genetics enabled by high-throughput sequencing technologies" (Max-Planck-Institute for Developmental Biology, Tübingen)
  • Prof. Boris Macek, 25.04.2013, 16:00-17:00, Lecture hall: N1, Auf der Morgenstelle 16, 72076 Tübingen, "Global detection of kinase substrates using quantitative mass spectrometry-based proteomics" (Proteome Center Tübingen, University of Tübingen)

  • Prof. Peter Bauer, 02.05.2013, 16:00-17:00, Lecture hall: N2, Auf der Morgenstelle 16, 72076 Tübingen, “Next generation sequencing goes diagnostics" (Department of Medical Genetics, University of Tübingen)

  • Prof. Olaf Riess

  • Prof. Dr. Marius Ueffing, 06.06.2013, 16:00-17:00, Lecture hall: N2, Auf der Morgenstelle 16, 72076 Tübingen, "Molecular dissection and scaled integration of functional protein networks: analyzing the molecular basis of human vision” (Institute for Ophtalmic Research, University of Tübingen)

  • Dr. Marc Stahl, 04.07.2013, 16:00-17:00, Lecture hall: N1, Auf der Morgenstelle 16, 72076 Tübingen, "Metabolomics: What we can do – what we cannot do” (Center for Plant Molecular Biology, University of Tübingen)

  • Prof. Peter Martus, 25.07.2013, 16:00-17:00, Lecture hall: N1, Auf der Morgenstelle 16, 72076 Tübingen, “Multiple Imputation of Missing Values – strategies and pitfalls” (Institute for Clinical Epidemiology and Applied Biometry, University Hospital Tübingen)

  • Dr. Oliver Poetz, 24.10.2013, 16:00-17:00, Lecture hall: N1, Auf der Morgenstelle 16, 72076 Tübingen, "Trap & Measure: Immunoassays In Targeted and Non-Targeted Proteomics” (NMI Natural and Medical Sciences Institute at the University of Tübingen)

  • Dr. Dr. Saskia Biskup, 07.11.2013, 16:00-17:00, Lecture hall: N1, Auf der Morgenstelle 16, 72076 Tübingen, "Next generation sequencing in human genetic diagnostics” (CeGaT Tübingen)

Biomedical Data Science Symposium

10 Years Quantitative Biology Center

Join us for this exciting day of biomedical data science to celebrating QBiC’s 10 year anniversary. The event will showcase cutting edge research across many areas of biomedical data science, and provides an opportunity to get informed about the Quantitative Biology Center (QBiC), its achievements, as well as the vision for the future. The event targets the broad life science community to come together to discuss science and the center’s service portfolio.

08.07.2022, 10.15 a.m. - 03.30 p.m.

Gesundheitszentrum Tübingen
Tagungsräume 1 + 2
Hoppe-Seyler-Str. 6
72076 Tübingen

Please register here: 


The programme will feature invited speakers across several areas of data science, a QBiC poster session and of course a reception to celebrate the first ten years. We hope the event will give you lots of opportunities to network and engage with other attendees. Join us for some exciting discussions and to share your ideas with QBiC co-workers.

Tamas Madl (Sr. Healthcare BD & Data Scientist, Intl. Public Sector Healthcare, Amazon Web Services)
Chloé-Agathe Azencott (CBIO Mines Paris, Institut Curie)
Anne-Laure Boulesteix (The Institute for Medical Information Processing, Biometry, and Epidemiology, LMU Munich)
Cedric Notredame (Comparative Bioinformatics Group, Bioinformatics and Genomics Programme, Centre de Regulatió Genòmica (CRG))
Gene Myers (Max Planck Institute of Molecular Cell Biology and Genetics, Dresden)


Time      Speaker
10:15-10:30   Sven Nahnsen

Tamas Madl

Machine learning on high-dimensional biomedical data - learnings on scale, interpretability, and privacy


For reasons of health this talk

will not be held

Chloé-Agathe Azencott
Feature selection with regularization in high-dimensional genomics data
11:20-12:15   Anne-Laure Boulesteix
A replication crisis in methodological computational research?
12:15-12:55 Lunch break  

Bernd Engler

Welcome address

13:05-13:55   Cedric Notredame
Scaling up sequence analysis without losing your balance
13:55-14:45   Gene Myers
Hi-Fidelity Genomics: What have we been missing?
from 14:45 Poster session and reception




No upcoming workshops

QBiC Virtual Workshop November 2021

QBiC Virtual Workshop - "Bioinformatics in environmental and host-associated microbiome research"

The Workshop will comprise lectures and relevant applications in the field of "Bioinformatics in environmental and host-associated microbiome research”. Several distinguished guest speakers as well as experts from QBiC will share their research at various fronts in the field of environmental and host-associated microbiome research.

04.11.2021, 10-17:30 via Zoom
Please register here:
After doing so, you will receive the Zoom link in time for the event.


Sven Nahnsen (Director)
Daniel Straub (Research & Development in Data Science, Environmental omics)
Gisela Gabernet (Teamleader Research & Development in Data Science)

Daniel Huson (Algorithms in Bioinformatics, University of Tübingen)
Nicholas Youngblut (Microbial ecology of human gut methanogens, Max-Planck-Institute, Tübingen)
Kate Thompson & Sara Kleindienst (Microbial Ecology, University of Tübingen)
Shrikant Mantri (Translational genome mining, University of Tübingen)
Huang Lin (Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICH, NIH))
Greg Poore (Department of Bioengineering, University of California)

The Workshop will comprise lectures in the field of microbiome research, covering both environmental and host-associated applications. Several experts from Tübingen as well as selected international guest speakers will share their research at various fronts in the field of microbiome research.
The increasing size and complexity of generated data drives a rapid development in the field of microbiome research and opens up new avenues of applications. We will introduce sequencing methods in the field of meta-omics that are currently available at the Tübingen Life Science Campus and discuss computational methods, ranging from bestpractice pipelines for scalable and reproducible analyses to individual state-of-the-art analysis tools. We will show how these methods can be applied, what they can deliver and provide insights into future perspectives.


Time Speaker Topic
10:00-10:15 Sven Nahnsen

Introduction to the workshop (watch on Youtube)

10:15-11:00 Nicholas Youngblut Bioinformatics approaches for assessing gut microbiome diversity and host-microbe co-evolution (watch on Youtube or look into the slides)
11:00-11:35 Kate Thompson

Microbial Ecology through an ‘omics’ lens


Daniel Straub 

Best practice microbiome data analysis at QBiC (look into the slides)

12:10-13:30 Lunch  
13:30-14:00 Gisela Gabernet Reproducible NGS data analysis with Nextflow and nf-core (watch on Youtube or look into the slides)
14:00-14:40 Daniel Huson Analysis of long-read microbiome sequencing data (watch on Youtube or look into the slides)
14:40-15:00 Shrikant Mantri Recovering biosynthetic gene clusters from Tuebingen Strain Collection using TELL-Seq and Nanopore data (watch on Youtube)
15:00-16:00 Coffee break  
16:00-16:35 Huang Lin Differential abundance and correlation analysis of microbiome data: Challenges and some solutions (watch on Youtube or look into the slides)
16:35-17:10 Greg Poore

Microbiome analyses of blood and tissues  

suggest cancer diagnostic approach

Starting 17:10 Social Event on gather.town Create an avatar and meet the speakers in our virtual lounge!

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QBiC Virtual Workshop November 2020

QBiC Virtual Workshop - "Bioinformatics in Cancer Research"

The Workshop will comprise lectures and relevant applications in the field of "Bioinformatics in Cancer Research”. Several distinguished guest speakers as well as experts from QBiC will share their research at various fronts in the field of cancer research.

26.11.2020, 10 a.m. to 4 p.m. via Zoom 


Friederike Hanssen (Ph.D. Student)
Dr. Luis Kuhn (Scientist)
Sven Fillinger (Team Leader IT and Software Development)

PD Dr. med. Juliane Walz (KKE Translational Immunology)
Dr. med. Markus Löffler (Department of General, Visceral and Transplant Surgery)
Dr. Nicolas Casadei (Institute of Medical Genetics and Applied Genomics)
Dr. Andre F. Martins (Werner Siemens Imaging Center)

The aim of this workshop is to present a wide range of novel bioinformatics methodologies in cancer research and to create a platform to interact with experts in their respective fields.

Major breakthroughs in this field during the past decade have revolutionized cancer research, allowing omics and biomedical imaging data to be generated at ever increasing volumes and resolution. The challenge however is the increasing complexity in handling the resulting datasets which can be large and highly heterogeneous.

We will introduce computational methods for management, processing and analysis of complex omics and imaging data that are currently available at the Tübingen Life Science Campus and discuss how they are applied to cancer research.


Time Speaker Topic
10:00-10:10 Dr. Sven Nahnsen

Introduction to the workshop

10:10-10:45 PD Dr. med. Juliane Walz Peptide-based Immunotherapy - Antigens, Combinations, Translation
10:45-10:50 Coffee break  
10:50-11:25 Dr. med. Markus Löffler  Cancer Immunotherapy: From Standard Therapy to Individualized Medicine
11:25-11:55 Sven Fillinger

FAIR data management in the context of cancer research. (Version 1.0.0-rc1). Zenodo. http://doi.org/10.5281/zenodo.4288828
(find the slides here)

11:55-13:15 Lunch  
13:15-13:50 Friederike Hanssen Bioinformatic analyses with portable and reproducible pipelines on public datasets
13:50-14:25 Dr. Nicolas Casadei

Overview of methods used in molecular oncology

(DNA & RNA sequencing, ATAC-seq, bulk vs single-cell, methylation, short vs long reads).

14:25-14:40 Coffee break  
14:40-15:15 Dr. Andre F. Martins Imaging tissue physiology with non-invasive metabolic approaches
15:15-15:45 Dr. Luis Kuhn Semantic segmentation for medical image analysis
15:45-15:50 Dr. Sven Nahnsen Conclusion
15:50-16:30   Post workshop breakout sessions:
  • (FAIR) Data management: Breakout room 1 
  • Image based analyses: Breakout room 2
  • Omics based analyses: Breakout room 3
  • Other: Breakout room 4

Nextflow Workshop April 2019

The development of reproducible, portable workflows is playing an increasingly important role in day-to-day data analysis at QBiC. The technological requirements for such workflows and analysis methods are reflected in the development of various domain-specific languages, which increasingly play a role in the scientific analysis of large data. At QBiC, the Nextflow platform was chosen for this purpose, which in combination with other projects such as nf-core has led to significantly improved workflows and standardization in the area of pipeline development.

In order to reinforce this development, a workshop with the core developers of Nextflow (Paolo Di Tommaso and Evan Floden) was initiated, which should offer beginners as well as advanced users the possibility to launch their own projects and pipeline developments with Nextflow.

The workshop will take place on April 11th/12th, 2019 in the premises of QBiC at the Tübingen University Hospital.


Registration is closed since March 29th. You will receive a bill with your institutional address that needs to be paid April 15th, 2019.


The workshop will be Thursday and Friday and the registration fee includes food and speaker fees.

We will update the agenda from time to time to make sure that everything is up to date. Also, there will be a social programme on Thursday, April 11 in the evening, so make sure to stay after the workshop in the evening!


Thursday, April 11

Time Topic
09:00-09:30 Intro to Nextflow programming model
09:30-10:00 Get Started: First Nextflow pipeline
10:00-10:30 Basic language structures and commands
10:30-10:45 Coffee Break
10:45-11:00 Basic language structures and commands continued
11:00-12:00 Nextflow Channels, concepts and usage
12:00-13:00 Nextflow Operators, concepts and usage

Lunch (sponsored by AWS)

14:00-15:45 Nextflow Processes, concepts and usage
15:45-16:00 Coffee Break
16:00-17:00 A simple RNAseq pipeline
open Try & Learn

Social Dinner at 07:00 PM at Restaurant Neckarmüller.

Friday, April 12

Time Topic
09:00-09:30 Nextflow Configuration
09:30-10:30 Managing dependencies (conda & containers)
10:30-10:45 Coffee Break
10:45-11:30 Deployment scenarios (clusters & cloud)

Error handling & troubleshooting

12:15-13:00 Common implementation patterns
13:00-14:00 Lunch (sponsored by AWS)
14:00-17:00 Hands-on: Implementation Variant Calling Pipeline
15:45-16:00 Coffee Break
16:00-17:00 Hands-on: Implementation Variant Calling Pipeline (continued)
open Q&A