gms | German Medical Science

66. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS), 12. Jahreskongress der Technologie- und Methodenplattform für die vernetzte medizinische Forschung e. V. (TMF)

26. - 30.09.2021, online

Tackling Single Cell Data by Informatics and Biostatistics

Meeting Abstract

Suche in Medline nach

  • Georg Fuellen - Universitätsmedizin Rostock, Institut für Biostatistik und Informatik in Medizin und Alternsforschung, Rostock, Germany
  • Harald Binder - Universitätsklinikum Freiburg, Freiburg, Germany

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 66. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS), 12. Jahreskongress der Technologie- und Methodenplattform für die vernetzte medizinische Forschung e.V. (TMF). sine loco [digital], 26.-30.09.2021. Düsseldorf: German Medical Science GMS Publishing House; 2021. DocAbstr. 101

doi: 10.3205/21gmds112, urn:nbn:de:0183-21gmds1121

Veröffentlicht: 24. September 2021

© 2021 Fuellen et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe



Note: This workshop was approved for the on-site GMDS amd CEN-IBS 2020 in Berlin. The schedule (see below) for the full-day workshop was reconfimed in April 2021 by the speakers (*) but the times are just suggestions. Also, titles may still be updated and one contributed talk slot is available; as part of a "Call for Participation" campaign for the workshop & the entire conference, circulated to researchers in the fields of single-cell, agng and stem cell research, this slot shall be filled.

Background: Science Magazine has chosen single-cell analyses of gene activity through time as its 2018 Breakthrough of the Year. This one-day workshop aims at an introduction to an up-and-coming topic (cf "Human Cell Atlas", "LifeTime") for which data analysis is a major challenge, given the amount and scope of the datasets being generated. While currently still basic research, clinical applications are around the corner. A specific emphasis is given to longitudinal datasets, which are especially suitable for studying the development of disease and progression of aging processes.

The workshop is co-sponsored by the German Stem Cell Network (GSCN).

Session 1: Single-Cell analyses of Stem Cell and Aging Data, an Introduction

  • 8:00-8:35h Introduction to the Workshop (Georg Fuellen*, Harald Binder*)
  • 8:35-9:30h Invited: Angela Pisco*, Chan Zuckerberg Biohub: Tabula Muris Senis: looking at the hallmarks of aging through the transcriptomic lens
  • 9:30-10:00h Antonio del Sol*, University of Luxemburg: Single cell-based Multi-scale modelling in stem cell research

Session 2: LifeTime, and Bioinformatics & Biostatistics for single-cell data in depth

  • 10:30-11h Nikolaus Rajewsky, BIMSB Berlin: Principles of gene regulation in space and time by single-cell analyses (TBC)
  • 11-11:25h Antonio Scialdone*, Institute of Epigenetics and Stem Cells (IES), Helmholtz Zentrum München: Investigating cell competition in mouse embryos by single-cell transcriptomics and mathematical modelling
  • 11:25-11:45h Harald Binder(*), Freiburg: Where deep learning meets single cell gene expression data
  • 11:45-12h (contributed talk): TBC

Session 3: Aging and the Mammalian Heart

  • 14-14:30h Joao Pedro de Magalhaes*, Liverpool: Transcriptomics, single-cell sequencing and ageing
  • 14:30-14:45h Markus Wolfien*, Rostock: Automated annotation of rare-cell types from single-cell RNA-sequencing data through synthetic oversampling
  • 14:45-15h Anne-Marie Galow*, Dummerstorf: Integrative cluster analysis of whole hearts reveals proliferative cardiomyocytes
  • 15-1515h: Cyril Lagger, Liverpool (contributed talk): Investigating age-related dysregulation of intercellular communication from single-cell data
  • 15:15-15:30h Benedikt Obermayer*, Berlin (contributed talk): Variant analysis in single-cell transcriptomics

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.