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Using ontologies to study cell transitions.

Fuellen G, Jansen L, Leser U, Kurtz A - J Biomed Semantics (2013)

Bottom Line: Understanding, modelling and influencing the transition between different states of cells, be it reprogramming of somatic cells to pluripotency or trans-differentiation between cells, is a hot topic in current biomedical and cell-biological research.Scientific understanding of the complex molecular mechanisms underlying cell transitions could be improved by making essential pieces of knowledge available in a formal (and thus computable) manner.In particular, we discuss how comprehensive ontologies of cell phenotypes and of changes in mechanisms can be designed using the entity-quality (EQ) model.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock Medical School, Ernst-Heydemann-Str, 8, 18057 Rostock, Germany. fuellen@uni-rostock.de.

ABSTRACT

Background: Understanding, modelling and influencing the transition between different states of cells, be it reprogramming of somatic cells to pluripotency or trans-differentiation between cells, is a hot topic in current biomedical and cell-biological research. Nevertheless, the large body of published knowledge in this area is underused, as most results are only represented in natural language, impeding their finding, comparison, aggregation, and usage. Scientific understanding of the complex molecular mechanisms underlying cell transitions could be improved by making essential pieces of knowledge available in a formal (and thus computable) manner.

Results: We describe the outline of two ontologies for cell phenotypes and for cellular mechanisms which together enable the representation of data curated from the literature or obtained by bioinformatics analyses and thus for building a knowledge base on mechanisms involved in cellular reprogramming. In particular, we discuss how comprehensive ontologies of cell phenotypes and of changes in mechanisms can be designed using the entity-quality (EQ) model.

Conclusions: We show that the principles for building cellular ontologies published in this work allow deeper insights into the relations between the continuants (cell phenotypes) and the occurrents (cell mechanism changes) involved in cellular reprogramming, although implementation remains for future work. Further, our design principles lead to ontologies that allow the meaningful application of similarity searches in the spaces of cell phenotypes and of mechanisms, and, especially, of changes of mechanisms during cellular transitions.

No MeSH data available.


Related in: MedlinePlus

Outline of an ontology of cell mechanisms and its use to describe cell transitions. The figure shows a structure by which mechanism changes can be formally represented, using entity terms (shown on the left hand side) and quality modifiers (shown on the right hand side). The colour code follows the code used in Figure 3: Occurrents relevant for cell phenotypes are indicated in yellow, occurrents relevant for ultrastructures in blue, and occurrents directly involving molecules in green. 'Up’ and 'down’ are intended to indicate relative changes: 'Interaction Occludin-JAM Up’ states that there is a development in the cell to feature more interactions of this kind, no matter how many of them there have been before. With the exception of “is_a”, all relations are meant to have an all-some syntax (cf. Figure 1).
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Figure 2: Outline of an ontology of cell mechanisms and its use to describe cell transitions. The figure shows a structure by which mechanism changes can be formally represented, using entity terms (shown on the left hand side) and quality modifiers (shown on the right hand side). The colour code follows the code used in Figure 3: Occurrents relevant for cell phenotypes are indicated in yellow, occurrents relevant for ultrastructures in blue, and occurrents directly involving molecules in green. 'Up’ and 'down’ are intended to indicate relative changes: 'Interaction Occludin-JAM Up’ states that there is a development in the cell to feature more interactions of this kind, no matter how many of them there have been before. With the exception of “is_a”, all relations are meant to have an all-some syntax (cf. Figure 1).

Mentions: We distinguish between two types of processes going on in a cell: microscale mechanisms and macroscale changes thereof. Microscale mechanisms are the interactions between molecules going on in a cell at a certain time, while a macroscale change is the transition from one set of microscale mechanisms going on at one point of time to another such set at a later time. In order to transfer ontology-based annotation and search strategies from phenotypes at the anatomical level [12] to the domain of cell phenotypes and mechanism changes, we need to be able to formally describe both (a) cell phenotypes and (b) mechanism changes. Phenotypes are usually described by means of the entity-quality syntax (EQ) using the Phenotypic Quality Ontology PATO for anatomic phenotypes [13,14]. To apply the EQ syntax to the cell level, we outlined two ontologies, an ontology of cell parts (Figure 1) and an ontology of microscale mechanisms (Figure 2) to be used in combination with a small set of standardized modifiers (as 'qualities’).


Using ontologies to study cell transitions.

Fuellen G, Jansen L, Leser U, Kurtz A - J Biomed Semantics (2013)

Outline of an ontology of cell mechanisms and its use to describe cell transitions. The figure shows a structure by which mechanism changes can be formally represented, using entity terms (shown on the left hand side) and quality modifiers (shown on the right hand side). The colour code follows the code used in Figure 3: Occurrents relevant for cell phenotypes are indicated in yellow, occurrents relevant for ultrastructures in blue, and occurrents directly involving molecules in green. 'Up’ and 'down’ are intended to indicate relative changes: 'Interaction Occludin-JAM Up’ states that there is a development in the cell to feature more interactions of this kind, no matter how many of them there have been before. With the exception of “is_a”, all relations are meant to have an all-some syntax (cf. Figure 1).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4128511&req=5

Figure 2: Outline of an ontology of cell mechanisms and its use to describe cell transitions. The figure shows a structure by which mechanism changes can be formally represented, using entity terms (shown on the left hand side) and quality modifiers (shown on the right hand side). The colour code follows the code used in Figure 3: Occurrents relevant for cell phenotypes are indicated in yellow, occurrents relevant for ultrastructures in blue, and occurrents directly involving molecules in green. 'Up’ and 'down’ are intended to indicate relative changes: 'Interaction Occludin-JAM Up’ states that there is a development in the cell to feature more interactions of this kind, no matter how many of them there have been before. With the exception of “is_a”, all relations are meant to have an all-some syntax (cf. Figure 1).
Mentions: We distinguish between two types of processes going on in a cell: microscale mechanisms and macroscale changes thereof. Microscale mechanisms are the interactions between molecules going on in a cell at a certain time, while a macroscale change is the transition from one set of microscale mechanisms going on at one point of time to another such set at a later time. In order to transfer ontology-based annotation and search strategies from phenotypes at the anatomical level [12] to the domain of cell phenotypes and mechanism changes, we need to be able to formally describe both (a) cell phenotypes and (b) mechanism changes. Phenotypes are usually described by means of the entity-quality syntax (EQ) using the Phenotypic Quality Ontology PATO for anatomic phenotypes [13,14]. To apply the EQ syntax to the cell level, we outlined two ontologies, an ontology of cell parts (Figure 1) and an ontology of microscale mechanisms (Figure 2) to be used in combination with a small set of standardized modifiers (as 'qualities’).

Bottom Line: Understanding, modelling and influencing the transition between different states of cells, be it reprogramming of somatic cells to pluripotency or trans-differentiation between cells, is a hot topic in current biomedical and cell-biological research.Scientific understanding of the complex molecular mechanisms underlying cell transitions could be improved by making essential pieces of knowledge available in a formal (and thus computable) manner.In particular, we discuss how comprehensive ontologies of cell phenotypes and of changes in mechanisms can be designed using the entity-quality (EQ) model.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock Medical School, Ernst-Heydemann-Str, 8, 18057 Rostock, Germany. fuellen@uni-rostock.de.

ABSTRACT

Background: Understanding, modelling and influencing the transition between different states of cells, be it reprogramming of somatic cells to pluripotency or trans-differentiation between cells, is a hot topic in current biomedical and cell-biological research. Nevertheless, the large body of published knowledge in this area is underused, as most results are only represented in natural language, impeding their finding, comparison, aggregation, and usage. Scientific understanding of the complex molecular mechanisms underlying cell transitions could be improved by making essential pieces of knowledge available in a formal (and thus computable) manner.

Results: We describe the outline of two ontologies for cell phenotypes and for cellular mechanisms which together enable the representation of data curated from the literature or obtained by bioinformatics analyses and thus for building a knowledge base on mechanisms involved in cellular reprogramming. In particular, we discuss how comprehensive ontologies of cell phenotypes and of changes in mechanisms can be designed using the entity-quality (EQ) model.

Conclusions: We show that the principles for building cellular ontologies published in this work allow deeper insights into the relations between the continuants (cell phenotypes) and the occurrents (cell mechanism changes) involved in cellular reprogramming, although implementation remains for future work. Further, our design principles lead to ontologies that allow the meaningful application of similarity searches in the spaces of cell phenotypes and of mechanisms, and, especially, of changes of mechanisms during cellular transitions.

No MeSH data available.


Related in: MedlinePlus