research-article

A pattern-based approach to a cell tracking ontology.

Authors:

Heinrich HerreAuthors Info & Claims

Volume 159, Issue C

Pages 784 - 793

https://doi.org/10.1016/j.procs.2019.09.237

Published: 01 January 2019 Publication History

Abstract

Time-lapse microscopy has thoroughly transformed our understanding of biological motion and developmental dynamics from single cells to entire organisms. The increasing amount of cell tracking data demands the creation of tools to make extracted data searchable and interoperable between experiment and data types. In order to address that problem, the current paper reports on the progress in building the Cell Tracking Ontology (CTO): An ontology framework for describing, querying and integrating data from complementary experimental techniques in the domain of cell tracking experiments. CTO is based on a basic knowledge structure: the cellular genealogy serving as a backbone model to integrate specific biological ontologies into tracking data. As a first step we integrate the Phenotype and Trait Ontology (PATO) as one of the most relevant ontologies to annotate cell tracking experiments. The CTO requires both the integration of data on various levels of generality as well as the proper structuring of collected information. Therefore, in order to provide a sound foundation of the ontology, we have built on the rich body of work on top-level ontologies and established three generic ontology design patterns addressing three modeling challenges for properly representing cellular genealogies, i.e. representing entities existing in time, undergoing changes over time and their organization into more complex structures such as situations.

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Cited By

Loebe FBurek PHerre HBorgo SGalton AKutz O(2022)GFOApplied Ontology10.3233/AO-22026417:1(71-106)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/AO-220264
Burek PScherf NHerre H(2020)On the Formal Representation and Annotation of Cellular GenealogiesKnowledge Engineering and Knowledge Management10.1007/978-3-030-61244-3_14(194-203)Online publication date: 16-Sep-2020
https://dl.acm.org/doi/10.1007/978-3-030-61244-3_14

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A pattern-based approach to a cell tracking ontology.
1. Applied computing

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Published In

cover image Procedia Computer Science

Procedia Computer Science Volume 159, Issue C

2019

2653 pages

ISSN:1877-0509

EISSN:1877-0509

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Elsevier Science Publishers B. V.

Netherlands

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Published: 01 January 2019

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Cited By

Loebe FBurek PHerre HBorgo SGalton AKutz O(2022)GFOApplied Ontology10.3233/AO-22026417:1(71-106)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/AO-220264
Burek PScherf NHerre H(2020)On the Formal Representation and Annotation of Cellular GenealogiesKnowledge Engineering and Knowledge Management10.1007/978-3-030-61244-3_14(194-203)Online publication date: 16-Sep-2020
https://dl.acm.org/doi/10.1007/978-3-030-61244-3_14

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