Semantic Web Infrastructure for Fungal Enzyme Biotechnologists

Abstract

The FungalWeb Ontology aims to support the data integration needs of enzyme biotechnology from inception to product roll. Serving as a knowledgebase for decision support, the conceptualization seeks to link fungal species with enzymes, enzyme substrates, enzyme classifications, enzyme modifications, enzyme related intellectual property, enzyme retail and applications. The ontology, developed in the OWL language, is the result of the integration of numerous biological database schemas, web accessible text resources and components of existing ontologies. We assess the quantity of implicit knowledge in the Fungal Web ontology by analyzing the range of tags in the OWL files and along with other description logic (DL) computable metrics of the ontology, contrast it with other publicly available bio-ontologies. Thereafter we demonstrate how the FungalWeb Ontology supports its broad remit required in fungal biotechnology by (i) suggesting semantic queries typical of a fungal enzymologist involved in product development, (ii) presenting application scenarios, and (iii) presenting the conceptualizations of the ontological frame able to support these scenarios. Recognizing the complexity of the ontology query process for the non-technical manager we introduce a simplified query tool, Ontologent Interative Query (OntoIQ) that allows the user to browse and build queries from a selection of query patterns. The OntoIQ interface supports users not familiar with writing DL syntax allowing them access to the ontology with expressive description logic and automated reasoning tools. Finally we discuss the challenges encountered during the development of semantic infrastructure for fungal enzyme biotechnologists.

The Ecology of Ontologies in the Public Domain

“…Likewise inverse functional and symmetric relations were infrequently used. In order to reduce noise introduced into our analysis by the low level occurrence of tags we normalized our data using a similar approach to other authors [23,28]. The resulting analysis…”

Ontology Design for Solving Computationally-Intensive Problems on Heterogeneous Architectures

“…In parallel to this, ontologies can play vital role in solving domain specific problems by making use of knowledge representation and reasoning [1][2][3][4]. Due to the nature of existing hardware clusters [5], it is now common to have a cluster of hardware architectures [6] equipped with an NVIVIA GPGPUs and Xeon-Phi coprocessor in addition to traditional Intel CPUs.…”

Applying OWL Reasoning to Genomic Data

“…Both query pattern variants might collapse into one pattern if a query involves enumerated classes. The successful use of the query pattern is reported elsewhere [29], [30].…”

“…Queries can be also composed with the help of predefined query patterns. nRQL and OntoIQ 1 have been successfully used in the context of a fungal enzyme project [29], [30].…”