2003 Special issue Towards a formalization of disease-specific ontologies for neuroinformatics Amarnath Gupta a , Bertram Luda ¨scher a, * , Jeffrey S. Grethe b , Maryann E. Martone b a San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0505, USA b Department of Neuroscience, University of California San Diego, USA Received 31 January 2003; revised 11 July 2003; accepted 11 July 2003 Abstract We present issues arising when trying to formalize disease maps, i.e. ontologies to represent the terminological relationships among concepts necessary to construct a knowledge-base of neurological disorders. These disease maps are being created in the context of a large- scale data mediation system being created for the Biomedical Informatics Research Network (BIRN). The BIRN is a multi-university consortium collaborating to establish a large-scale data and computational grid around neuroimaging data, collected across multiple scales. Test bed projects within BIRN involve both animal and human studies of Alzheimer’s disease, Parkinson’s disease and schizophrenia. Incorporating both the static ‘terminological’ relationships and dynamic processes, disease maps are being created to encapsulate a comprehensive theory of a disease. Terms within the disease map can also be connected to the relevant terms within other ontologies (e.g. the Unified Medical Language System), in order to allow the disease map management system to derive relationships between a larger set of terms than what is contained within the disease map itself. In this paper, we use the basic structure of a disease map we are developing for Parkinson’s disease to illustrate our initial formalization for disease maps. q 2003 Elsevier Ltd. All rights reserved. Keywords: Neuruoinformatics; Semantic; Parkinson’s disease; Logic Model; Ontology 1. Introduction Recently there has been a significant increase in the development and publication of terminological systems for biology. In addition to general-purpose controlled vocabularies such as the Unified Medical Language System (UMLS) (National Library of Medicine, 2003) and Gene Ontology (Gene Ontology Consortium, 2002), a large number of more specialized vocabularies are being created. For example, TaO (TAMBIS Ontology) (Stevens et al., 1999) is an ontology for protein properties, motifs and similarities; The Cyc family of ontologies (EcoCyc (Karp, Riley, Paley, Pellegrini-Toole, & Krummenacker, 1999), MetaCyc (Karp, Riley, Saier, Paulsen, & Pellegrini-Toole, 2000), HinCyc (Karp, Ouzounis, & Paley, 1996)) describe the genes, gene product function, metabolism and regulation within specific species such as E. coli and the H. influenza; whereas the MGED Ontology provides standard terms for the annotation of microarray experiments. In the domain of neuroscience, BrainML (Gardner, Xiao, Abato, Knuth, & Gardner, 2002) is a controlled vocabulary for describing the standard vocabulary of neurophysiological experiments. NeuroML represents a standardized vocabulary to express information about neural simulations. Despite this growth, it was observed by (Karp, 2000; Williams & Andersen, 2003) and others that many of the publicly available ontologies remain just controlled vocabul- aries and do not satisfy the primary requirements of being a formal ontology that can used for purposes like automated logical interpretation. Hence they cannot be easily integrated into larger information management systems. Gruber (1993) defined an ontology as a “formal explicit specification of a shared conceptualization”, 1 where conceptualization refers to “an abstract model of how people think of things in the world, usually restricted to a particular subject area” (Guninger & Lee, 2002). 0893-6080/$ - see front matter q 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.neunet.2003.07.008 Neural Networks 16 (2003) 1277–1292 www.elsevier.com/locate/neunet * Corresponding author. Tel.: þ 1-858-822-0864; fax: þ1-858-822-0861. E-mail address: ludaesch@sdsc.edu (B. Luda ¨scher). 1 See also Guarino’s detailed discussion on the notion of ‘formal ontology’ (Guarino & Giaretta, 1995).