Abstract. Domain-specific languages facilitate solving problems in a targeted domain by providing features particular to the domain. Declarative domain-specific languages have the additional benefit that users specify what something means rather than how to do something. As a result, the language compiler is free to choose the best implementation strategies and to generate multiple artifacts from a single description. PADS/ML is a declarative data description language designed to facilitate ad hoc data management. From a single description, the compiler generates a myriad of artifacts, including data structures for the in-memory representation of the data and parsers and printers. In this paper, we describe a new generic programming infrastructure for PADS/ML that allows third-party developers to define additional useful artifacts without modifying the compiler. We report on two case studies that use this infrastructure. In the first, we build a version of PADX for PADS/ML, allowing any data source with a PADS/ML description to be queried as if it were XML. In the second, we extend Harmony with the ability to synchronize any data with a PADS/ML description. 1

ProbeLynx [1] is a software system that has been published to accomplish the task of linking microarray sequences to annotation data. However, ProbeLynx uses certain tables directly from the Ensembl database and is therefore sensitive to schema changes. At the time of writing, ProbeLynx uses Ensembl version 47 (we are currently on version 52). Our objective is to design a flexible, up-todate annotation pipeline that can be used to regularly update the annotation of microarray probes using publicly accessible databases which provide coverage of the genome. This paper is part of a workshop to compare diffrom EADGENE and SABRE Post-analyses Workshop

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Multiple inheritance hierarchies are frequently used for the classification of concepts into a taxonomy, to model software by organizing classes into an inheritance hierarchy, for querying object-oriented databases, for knowledge representation, policy enforcement, and subtyping of service interfaces for safe composition and substitution. All these areas apply hierarchies and share the same concern of being able to compute inheritance or subsumption relationships efficiently. In this report, we elaborate on encoding multiple inheritance hierarchies for representing subsumption relationships between concepts defined in ontologies to enable efficient matching mechanisms for context-aware service discovery, composition and substitution, and other application domains. We present several encoding techniques originating from the programming languages domain for the subtyping of classes in multiple inheritance hierarchies and argue why these encoding techniques are not feasible for achieving efficient subsumption testing in ontologies. We developed a prime-based encoding technique for subsumption of concepts and properties that outperforms several well-known ontology reasoners for this particular problem, both in terms of having a compact representation of the encoding and being able to compute the subsumption relationship efficiently. Our algorithm also offers an interesting alternative for the class subtyping encoding techniques, as it yields a new way of compaction without the need for changing old conflicting codes during incremental encoding.

Functional module detection by functional flow pattern mining in protein interaction networks

PDF corresponds to the article as it appeared upon acceptance. Fully formatted PDF and full text (HTML) versions will be made available soon. Muscle Research and Gene Ontology: New standards for improved data integration.

This Provisional PDF corresponds to the article as it appeared upon acceptance. Fully formatted PDF and full text (HTML) versions will be made available soon. OnEX: Exploring changes in life science ontologies BMC Bioinformatics 2009, 10:250

doi:10.1093/bib/bbp043