The 2nd International Cells in ExperimentaL Life Science Workshop (CELLS-2018)


  • Oliver He
  • Sirarat Sarntivijai
  • Alexander D. Diehl

Workshop type:

  • Workshop

Workshop Abstract

Cell cultures are a crucial component in life science experiments. Cell cultures used in biomedical experiments come in the form of both sample biopsy primary cells, and maintainable immortal cell lineages. These cells are versatile and widely used in different domains. High-content genotyping and phenotyping lead to many newly discovered cell types. New molecular cell markers and pathways are also being found to be differential indicators between normal and diseased cells in this process. The Cell Ontology (CL) and Cell Line Ontology (CLO) have long been established as reference ontologies in the OBO framework. This year’s CELLS workshop will focus on two themes: (i) challenges in the knowledge representation of newly-discovered cell types, and (ii) challenges in the knowledge representation of cells in disease states. This workshop will provide a venue for panel discussions of innovative solutions as well as the challenges in the development and application of biomedical ontologies to represent and analyze in vivo and in vitro cell- and cell line-related knowledge and data, including stem cell technologies. The workshop will cover the extension of CL and CLO for ontological representation of cell types and cell lines in new methodologies and experiments. It will also cover the applications and challenges in real-world use cases which may require other ontological adaptations beyond CL and CLO. Selected submissions will be featured in a BMC Bioinformatics thematic CELLS issue.

This will be the second CELLS workshop. We have successfully held our first CELLS workshop (CELLS-2017) in Newcastle, UK, on September 2017 on the theme of identifying challenges from the ontology semantic perspective, and the experimental laboratory perspective ( There were 6 oral presentations in CELLS-2017. The corresponding six proceeding papers were extended, submitted, and eventually accepted for publication in the journal BMC Bioinformatics. The CELLS-2017 introductory paper in BMC Bioinformatics introduces this event and summarizes the papers:


The rapid advancement of cell technologies has inevitably come up with the challenges in keeping up with the volume of the data as well as the dynamic evolution of the data format and knowledge representation. Experimental cell cultures and cell lines are widely used and often generated de novo and de facto at the laboratory of origin, while normalization of experimental cell data produced in different laboratory settings is difficult due to the offline non-synchronous nature of multiple laboratories working on similar questions on the same timeline. It is also difficult to separate out data from metadata due to the level of granularity of the details obtained from high-content technologies. Knowledge representation and modeling is often driven by individual experiments. Consolidation of heterogeneous metadata is an eminent challenge. New knowledge obtained by high-resolution technologies (e.g., single-cell RNA sequencing) adds more data volume that requires robust analysis and representation, especially regarding novel cell populations that do not belong to existing classes of CL or CLO. A community-driven consensus on the minimal set of information to represent new discoveries within the evolving knowledge needs to be found. We will need to discuss how ontologies support the modeling, representation, and analysis of cell-related data, metadata, and knowledge learned from experimental cell studies. We will benefit from a shared consensus experimental cell metadata model which can only be derived by community participation, discussion, and collaboration wherever possible. The proposers will ensure that the workshop is relevant to international audiences from both industry and academia. This workshop will be extremely useful to designers and implementers of experimental cell metadata framework in large and complex enterprises, nationwide clinical data repositories, electronic health systems for healthcare, and biomedical science analysis.