title: Using ontologies in PROTEUS for modeling proteomics data mining applications.
abstract: Bioinformatics applications are often characterized by a combination of (pre) processing of raw data representing biological elements, (e.g. sequence alignment, structure prediction), and an high level data mining analysis. Developing such applications needs knowledge of both data mining and bioinformatics domains, that can be effectively achieved by combining ontology about the application domain and ontology about the approaches and processes to solve the given problem. In this paper we talk about using ontologies to model proteomics in silico experiments. In particular data mining of mass spectrometry proteomics data is considered.
authors.affiliation: Magna Graecia University, 88100 Catanzaro, Italy. cannataro@unicz.it
authors.forename: Mario
authors.initials: M
authors.lastname: Cannataro
authors.forename: Pietro Hiram
authors.initials: PH
authors.lastname: Guzzi
authors.forename: Tommaso
authors.initials: T
authors.lastname: Mazza
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Tradigo
authors.forename: Pierangelo
authors.initials: P
authors.lastname: Veltri
mesh_terms: D019295:Computational Biology / Q000295:instrumentation / Q000379:methods*; D030562:Databases, Protein; D006801:Humans; D016247:Information Storage and Retrieval; D013058:Mass Spectrometry / Q000295:instrumentation / Q000379:methods*; D040901:Proteomics / Q000295:instrumentation / Q000379:methods*; D018875:Vocabulary, Controlled