Cells in ExperimentaL Life Sciences (CELLS-2018): capturing the knowledge of normal and diseased cells with ontologies

Sirarat Sarntivijai,Yongqun He,Alexander D. Diehl

doi:10.1186/s12859-019-2721-9

Abstract

Cell cultures and cell lines are widely used in life science experiments. In conjunction with the 2018 International Conference on Biomedical Ontology (ICBO-2018), the 2nd International Workshop on Cells in ExperimentaL Life Science (CELLS-2018) focused on two themes of knowledge representation, for newly-discovered cell types and for cells in disease states. This workshop included five oral presentations and a general discussion session. Two new ontologies, including the Cancer Cell Ontology (CCL) and the Ontology for Stem Cell Investigations (OSCI), were reported in the workshop. In another representation, the Cell Line Ontology (CLO) framework was applied and extended to represent cell line cells used in China and their Chinese representation. Other presentations included a report on the application of ontologies to cross-compare cell types and marker patterns used in flow cytometry studies, and a presentation on new experimental findings about novel cell types based on single cell RNA sequencing assay and their corresponding ontological representation. The general discussion session focused on the ontology design patterns in representing newly-discovered cell types and cells in disease states.

Highlights

Open AccessCells in ExperimentaL Life Sciences (CELLS2018): capturing the knowledge of normal and diseased cells with ontologiesSirarat Sarntivijai1, Yongqun He2* and Alexander D
New knowledge obtained by high-resolution technologies adds more data volume that requires robust analysis and representation, especially regarding novel cell populations that do not correspond to existing classes of the community-based Cell Ontology (CL) [1] or Cell Line
Serra et al presented the development of the Cancer Cell Ontology (CCL) that represents cancer cell types related to a variety of hematologic malignancies using logical axioms that capture the expression of cellular surface markers using Protein Ontology (PRO) [10] classes [11]

Summary

Introduction

Open AccessCells in ExperimentaL Life Sciences (CELLS2018): capturing the knowledge of normal and diseased cells with ontologiesSirarat Sarntivijai1, Yongqun He2* and Alexander D. New knowledge obtained by high-resolution technologies (e.g., mass cytometry or single-cell RNA sequencing) adds more data volume that requires robust analysis and representation, especially regarding novel cell populations that do not correspond to existing classes of the community-based Cell Ontology (CL) [1] or Cell Line

Results

Conclusion