Quality control for terms and definitions in ontologies and taxonomies

BACKGROUND: Ontologies and taxonomies are among the most important computational resources for molecular biology and bioinformatics. A series of recent papers has shown that the Gene Ontology (GO), the most prominent taxonomic resource in these fields, is marked by flaws of certain characteristic types, which flow from a failure to address basic ontological principles. As yet, no methods have been proposed which would allow ontology curators to pinpoint flawed terms or definitions in ontologies in a systematic way. RESULTS: We present computational methods that automatically identify terms and definitions which are defined in a circular or unintelligible way. We further demonstrate the potential of these methods by applying them to isolate a subset of 6001 problematic GO terms. By automatically aligning GO with other ontologies and taxonomies we were able to propose alternative synonyms and definitions for some of these problematic terms. This allows us to demonstrate that these other resources do not contain definitions superior to those supplied by GO. CONCLUSION: Our methods provide reliable indications of the quality of terms and definitions in ontologies and taxonomies. Further, they are well suited to assist ontology curators in drawing their attention to those terms that are ill-defined. We have further shown the limitations of ontology mapping and alignment in assisting ontology curators in rectifying problems, thus pointing to the need for manual curation

Rekonstruktion und Analyse interzellulärer Signalnetzwerke

Skusa A. Reconstruction and analysis of intercellular signaling networks. Bielefeld (Germany): Bielefeld University; 2006.Cells in the human body communicate over long distances via two systems, the humoral system and the neuronal system. The humoral system works via first messenger substances, such as hormones, cytokines and neurotransmitters, which are released into the blood. Biomedical knowledge on this kind of intercellular signaling is well established, but in contrast to signaling processes inside cells, not much of this knowledge exists in a form that is easily accessible for automated approaches, such as databases or ontologies. Most of what is known about extracellular signaling is stored in terms of natural language text in the scientific literature. The present study aims at the reconstruction and analysis of cell-cell signaling pathways by applying automated approaches. Therefore, relevant data is extracted from molecular databases as well as from biomedical literature by applying concept based text mining. For this purpose, models and corresponding graph representations are developed to assemble intercellular signals from partial information since available data sources are scattered and incomplete. The resulting information is finally applied to generate hypotheses on cell-cell signaling in the context of neurodegenerative diseases. More specifically, from the few molecular databases containing appropriate data, one database is tested in a preliminary study and reconstruction approaches accessing the specific structure of this database are developed. To reconstruct information from natural language text, ONDEX, a framework for ONtological text inDEXing and data integration has been developed in a collaborative work. ONDEX supports concept based approaches, i.e. databases and ontologies are integrated into a standardized graph-based framework, where biological entities as concepts are linked by relations (i.e., "is-a", "part-of" or "synonym"). A major part of this thesis is the development and the integration of concept based text indexing and concept based co-occurrence searches into ONDEX. On this basis, MEDLINE abstracts are mapped to concepts of a number of ontologies (e.g., Gene Ontology, MeSH terms and Cell Ontology) and mined for relevant parts of intercellular signaling. From these relations finally, cell-cell signaling hypotheses are assembled. Whereas the networks resulting from the database reconstruction are not sufficient for reasonable analysis and further use, evaluations of the text mining results show that a significant number of known facts can be found by applying concept based co-occurrences searches. Finally, the text extraction results are reduced to a manageable amount of concept based co-occurrence hits and hypotheses for cell types involved in neurodegenerative diseases. In this case a number of known facts are reconstructed and suggestions for further improvements are made. The text extraction results demonstrate the possibility to reconstruct relations between biological entities from text by applying a concept based framework and thus, how a large text set can be reduced to a number of hypotheses allowing manual examination

Suchmaschinen: Status Quo und Entwicklungstendenzen

This article deals with search engines and their prospective developement. Apart from Google, Yahoo! and Microsoft, there are new alternative services that need to be analysed

Der Markt für Internet-Suchmaschinen

This article deals with the current situation on the search engine market and alternative search approaches. The opportunities for new competitors are analysed, as well

Towards a Comparison of Evolutionary Creativity in Biological and Cultural Evolution

Skusa A, Bedau MA. Towards a Comparison of Evolutionary Creativity in Biological and Cultural Evolution. In: Proceedings of the 8th International Conference on the Simulation and Synthesis of Living Systems (ALIFE VIII). 2003: 233-242

Evaluating an Evolutionary Approach for Reconstructing Gene Regulatory Networks

Whitehead D, Skusa A, Kennedy PJ. Evaluating an Evolutionary Approach for Reconstructing Gene Regulatory Networks. In: Proceedings of the 9th International Conference on the Simulation and Synthesis of Living Systems (ALIFE 9). 2004: 427-432

Analyzing Intercellular Communication Networks

Introduction The structure and dynamics of biological and technical networks have become a major topic of scientific research recently. The focus in biological network research so far has been mainly on intracellular networks, e.g. metabolic networks [1], gene-regulatory networks [2], or networks of protein-protein interactions [3]. What has not been taken into account yet is the humoral network of intercellular communication, which links intracellular signalling networks of different cells and cell types. Cells communicate in various ways. In this work, we concentrate on humoral communication through neurotransmitters, endocrine and cytokine messengers in the human body. The related substances act as first messengers and thus are released from specific cells to regulate functions in distant target cells by binding as ligands to specific receptors. Upon binding to its receptor ligands activate intracellular second messenger systems which finally lead to changes in cellular function