Abstract
BackgroundThe indexing of scientific literature and content is a relevant and contemporary requirement within life science information systems. Navigating information available in legacy formats continues to be a challenge both in enterprise and academic domains. The emergence of semantic web technologies and their fusion with artificial intelligence techniques has provided a new toolkit with which to address these data integration challenges. In the emerging field of lipidomics such navigation challenges are barriers to the translation of scientific results into actionable knowledge, critical to the treatment of diseases such as Alzheimer's syndrome, Mycobacterium infections and cancer.ResultsWe present a literature-driven workflow involving document delivery and natural language processing steps generating tagged sentences containing lipid, protein and disease names, which are instantiated to custom designed lipid ontology. We describe the design challenges in capturing lipid nomenclature, the mandate of the ontology and its role as query model in the navigation of the lipid bibliosphere. We illustrate the extent of the description logic-based A-box query capability provided by the instantiated ontology using a graphical query composer to query sentences describing lipid-protein and lipid-disease correlations.ConclusionAs scientists accept the need to readjust the manner in which we search for information and derive knowledge we illustrate a system that can constrain the literature explosion and knowledge navigation problems. Specifically we have focussed on solving this challenge for lipidomics researchers who have to deal with the lack of standardized vocabulary, differing classification schemes, and a wide array of synonyms before being able to derive scientific insights. The use of the OWL-DL variant of the Web Ontology Language (OWL) and description logic reasoning is pivotal in this regard, providing the lipid scientist with advanced query access to the results of text mining algorithms instantiated into the ontology. The visual query paradigm assists in the adoption of this technology.
Highlights
Lipids and their metabolites have a very crucial role in the biology and cellular functions of many living organisms
To facilitate the lipidomic practitioner to navigate the relations between lipids, proteins and disease that are identified by text mining we developed an intelligent query interface which reformulates expressive pictorial representations of queries into the corresponding syntax of an A-box query language, nRQL for issue to the OWL-Description logics (DL) reasoner RACER
This was achieved through the coordination of distributed literature sources, natural language processing, ontology development, automated ontology instantiation [21], visual query guided reasoning over OWL-DL Aboxes [13]
Summary
Lipids and their metabolites have a very crucial role in the biology and cellular functions of many living organisms. Lipidomics [1] generates a large amount of heterogeneous chemical and biochemical data that must be integrated and analyzed in a systematic manner Such efforts are, hampered by the lack of consistent classification for lipids. Since its emergence in 1976, the IUPAC naming scheme has not evolved to accommodate the large number of novel lipid classes that have been discovered in the last 3 decades In this context different lipid research groups have developed their own classifications of lipids which are usually very narrow and only applicable for a restricted category of lipid. In the emerging field of lipidomics such navigation challenges are barriers to the translation of scientific results into actionable knowledge, critical to the treatment of diseases such as Alzheimer's syndrome, Mycobacterium infections and cancer
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