Patryk Burek

A top-level ontology of functions and its application in the Open Biomedical Ontologies

MOTIVATION A clear understanding of functions in biology is a key component in accurate modelling of molecular, cellular and organismal biology. Using the existing biomedical ontologies it has been impossible to capture the complexity of the communitys knowledge about biological functions. RESULTS We present here a top-level ontological framework for representing knowledge about biological functions. This framework lends greater accuracy, power and expressiveness to biomedical ontologies by providing a means to capture existing functional knowledge in a more formal manner. An initial major application of the ontology of functions is the provision of a principled way in which to curate functional knowledge and annotations in biomedical ontologies. Further potential applications include the facilitation of ontology interoperability and automated reasoning. A major advantage of the proposed implementation is that it is an extension to existing biomedical ontologies, and can be applied without substantial changes to these domain ontologies. AVAILABILITY The Ontology of Functions (OF) can be downloaded in OWL format from http://onto.eva.mpg.de/. Additionally, a UML profile and supplementary information and guides for using the OF can be accessed from the same website.

Adoption of the Classical Theory of Definition to Ontology Modeling

Ontology modeling requires modeling languages expressive enough to represent various definition types. A definition type which seems to be of particular significance is that provided by the Classical Theory of Definition. In this paper we investigate if and how far the Classical Theory of Definition is adopted by some of the ontology modeling formalisms, namely by UML, ORM and DL. Moreover, we provide a means for representing some crucial issues in the context of the Classical Theory of Definition which seem to have no representation in the formalisms discussed. Among them are the identification of essential, peculiar and incidental predications and the representation of subsumption in the manner of the genus-differentia definition.

Assisting the Machine Paradigms for Human-Machine Interaction in Single Cell Tracking

Single cell tracking emerged as one of the fundamental experimental techniques over the past years in basic life science research. Though a large number of automated tracking methods has been introduced, they are still lacking the accuracy to reliably track complete cellular genealogies over many generations. Manual tracking on the other hand is tedious and slow. Semi-automated approaches to cell tracking are a good compromise to obtain comprehensive information in feasible amounts of time. In this work, we investigate the efficacy of different interaction paradigms for manual correction and processing of precomputed tracking results and present a respective tool that implements those strategies.

Essentialized conceptual structures in ontology modeling

Psychology and cognitive science show that human concepts possess particular structures (conceptual structures). However, in the process of ontology modeling information concerning the structure of human concepts is lost. In ontologies concepts are typically represented as undifferentiated collections of necessary (or necessary and sufficient) conditions. The lack of representation of conceptual structure may cause ontologies to be inadequate and may limit their usability for human users. We present an attempt to bring ontology modeling closer to theories of conceptual structures, in particular to psychological essentialism. A metaontology is developed to support the representation of conceptual structure, in particular the distinction between essential and merely necessary conditions.

Towards refactoring the Molecular Function Ontology with a UML profile for function modeling

BackgroundGene Ontology (GO) is the largest resource for cataloging gene products. This resource grows steadily and, naturally, this growth raises issues regarding the structure of the ontology. Moreover, modeling and refactoring large ontologies such as GO is generally far from being simple, as a whole as well as when focusing on certain aspects or fragments. It seems that human-friendly graphical modeling languages such as the Unified Modeling Language (UML) could be helpful in connection with these tasks.ResultsWe investigate the use of UML for making the structural organization of the Molecular Function Ontology (MFO), a sub-ontology of GO, more explicit. More precisely, we present a UML dialect, called the Function Modeling Language (FueL), which is suited for capturing functions in an ontologically founded way. FueL is equipped, among other features, with language elements that arise from studying patterns of subsumption between functions. We show how to use this UML dialect for capturing the structure of molecular functions. Furthermore, we propose and discuss some refactoring options concerning fragments of MFO.ConclusionsFueL enables the systematic, graphical representation of functions and their interrelations, including making information explicit that is currently either implicit in MFO or is mainly captured in textual descriptions. Moreover, the considered subsumption patterns lend themselves to the methodical analysis of refactoring options with respect to MFO. On this basis we argue that the approach can increase the comprehensibility of the structure of MFO for humans and can support communication, for example, during revision and further development.

FueL: Representing function structure and function dependencies with a UML profile for function modeling

Modeling functions is a key aspect of artifact design, including software engineering and business systems modeling, but it is likewise of fundamental importance in natural systems modeling, for example in modeling biological organisms. The Unified Modeling Language (UML), which originated from object-oriented software engineering, is nowadays a de facto standard for conceptual modeling and its current applications go far beyond software engineering. The paper investigates first to what extent UML is suited for modeling functions. We survey various approaches to function modeling with UML and identify their limitations. Based on the conducted analysis, we introduce a UML profile for function modeling, called the Function Modeling Language (FueL). FueL enables the modeling of the structure of functions, of relations between functions, such as function decomposition, as well as of function ascription, i.e., of relations linking functions with other types of entities. The main application field that we considered while developing FueL is bioinformatics. Nonetheless, the presented profile is domain-independent and is capable of modeling cross-domain systems. The profile has been tested on fragments of the Molecular Function Ontology, a sub-ontology of the Gene Ontology. In this connection the paper further demonstrates that the applications of FueL transcend the construction of new models, by showing how the profile aids restructuring and refactoring existing models.

Dually structured concepts in the semantic web: answer set programming approach

There is an ongoing discussion whether reasoning in the Semantic Web should be monotonic or not. However, it seems that the problem concerns not only reasoning over knowledge but knowledge itself, where apart from nondefeasible knowledge the defeasible knowledge can be distinguished. In the current paper we rely on the Dual Theory of Concepts, according to which concepts are dually structured into defeasible and nondefeasible parts. We develop a metaontology for representing both types of a concepts structure and apply it for annotating OWL axioms. The translation of annotated OWL axioms into a logic program under answer set semantics is provided. Hence the answer set solver Smodels may be used as reasoner for annotated ontologies, handling properly the distinction between monotonic and nonmonotonic reasoning.