Towards linked open gene mutations data

http://www.biomedcentral.com/1471-2105/13/S4/S7

Background With the advent of high-throughput technologies, a great wealth of variation data is being produced. Such information may constitute the basis for correlation analyses between genotypes and phenotypes and, in the future, for personalized medicine. Several databases on gene variation exist, but this kind of information is still scarce in the Semantic Web framework. In this paper, we discuss issues related to the integration of mutation data in the Linked Open Data infrastructure, part of the Semantic Web framework. We present the development of a mapping from the IARC TP53 Mutation database to RDF and the implementation of servers publishing this data.

Methods A version of the IARC TP53 Mutation database implemented in a relational database was used as first test set. Automatic mappings to RDF were first created by using D2RQ and later manually refined by introducing concepts and properties from domain vocabularies and ontologies, as well as links to Linked Open Data implementations of various systems of biomedical interest. Since D2RQ query performances are lower than those that can be achieved by using an RDF archive, generated data was also loaded into a dedicated system based on tools from the Jena software suite.

Results We have implemented a D2RQ Server for TP53 mutation data, providing data on a subset of the IARC database, including gene variations, somatic mutations, and bibliographic references. The server allows to browse the RDF graph by using links both between classes and to external systems. An alternative interface offers improved performances for SPARQL queries. The resulting data can be explored by using any Semantic Web browser or application.

Conclusions This has been the first case of a mutation database exposed as Linked Data. A revised version of our prototype, including further concepts and IARC TP53 Mutation database data sets, is under development. The publication of variation information as Linked Data opens new perspectives: the exploitation of SPARQL searches on mutation data and other biological databases may support data retrieval which is presently not possible. Moreover, reasoning on integrated variation data may support discoveries towards personalized medicine.

Gauging triple stores with actual biological data.

http://www.biomedcentral.com/1471-2105/13/S1/S3

Abstract

Background: Semantic Web technologies have been developed to overcome the limitations of the current Web and conventional data integration solutions. The Semantic Web is expected to link all the data present on the Internet instead of linking just documents. One of the foundations of the Semantic Web technologies is the knowledge representation language Resource Description Framework (RDF). Knowledge expressed in RDF is typically stored in so-called triple stores (also known as RDF stores), from which it can be retrieved with SPARQL, a language designed for querying RDF-based models. The Semantic Web technologies should allow federated queries over multiple triple stores. In this paper we compare the efficiency of a set of biologically relevant queries as applied to a number of different triple store implementations.
Results: Previously we developed a library of queries to guide the use of our knowledge base Cell Cycle Ontology implemented as a triple store. We have now compared the performance of these queries on five non-commercial triple stores: OpenLink Virtuoso (Open-Source Edition), Jena SDB, Jena TDB, SwiftOWLIM and 4Store. We examined three performance aspects: the data uploading time, the query execution time and the scalability. The queries we had chosen addressed diverse ontological or biological questions, and we found that individual store performance was quite query-specific. We identified three groups of queries displaying similar behaviour across the different stores: 1) relatively short response time queries, 2) moderate response time queries and 3) relatively long response time queries. SwiftOWLIM proved to be a winner in the first group, 4Store in the second one and Virtuoso in the third one.
Conclusions: Our analysis showed that some queries behaved idiosyncratically, in a triple store specific manner, mainly with SwiftOWLIM and 4Store. Virtuoso, as expected, displayed a very balanced performance – its load time and its response time for all the tested queries were better than average among the selected stores; it showed a very good scalability and a reasonable run-to-run reproducibility. Jena SDB and Jena TDB were consistently slower than the other three implementations. Our analysis demonstrated that most queries developed for Virtuoso could be successfully used for other implementations.

Knowledge sharing and collaboration in translational research, and the DC-THERA Directory.

http://bib.oxfordjournals.org/content/early/2011/10/02/bib.bbr051.full.pdf

Abstract

Biomedical research relies increasingly on large collections of data sets and knowledge whose generation, representation and analysis often require large collaborative and interdisciplinary efforts. This dimension of ‘big data’ research calls for the development of computational tools to manage such a vast amount of data, as well as tools that can improve communication and access to information from collaborating researchers and from the wider community. Whenever research projects have a defined temporal scope, an additional issue of data management arises, namely how the knowledge generated within the project can be made available beyond its boundaries and life-time. DC-THERA is a European ‘Network of Excellence’ (NoE) that spawned a very large collaborative and interdisciplinary research community, focusing on the development of novel immunotherapies derived from fundamental research in dendritic cell immunobiology. In this article we introduce the DC-THERA Directory, which is an information system designed to support knowledge management for this research community and beyond. We present how the use of metadata and Semantic Web technologies can effectively help to organize the knowledge generated by modern collaborative research, how these technologies can enable effective data management solutions during and beyond the project lifecycle, and how resources such as the DC-THERA Directory fit into the larger context of e-science.

This edition of SWAT4LS  was composed of an Hackathon (co-organized with the Open Knowledge Foundation working group and with the DevCSI JISC), a Tutorial day and the Workshop day. Overall the workshop was attended by about 90 participants.

I wish to thank the co-chair and co-organizers of the workshop (M.Scott Marshall, Paolo Romano, Adrian Pashcke, Albert Burger), the co-organizers of the Hackathon (Mahendra Mahey, Peter Murray-Rust, Jenny Molloy), the sponsors (BBSRC, NCBO, Biomed Central, Ontotext, Selventa), the excellent keynotes (Tetsuro Toyoda, Douglas Kell, Wendy Hall) the tutorial presenters and all participants.

More up to date details can be found on the SWAT4LS website

Lost in translation: data integration tools meet the Semantic Web (experiences from the Ondex project)

Presented at DEIT (Data Engineering and Internet Technology) 2011

(Conference Record # 17831, IEEE Catalog Number: CFP1113L-CDR, ISBN: 978-1-4244-8581-9)

Preprint available at: http://arxiv.org/abs/1103.4749

Abstract

More information is now being published in machine processable form on the web and, as de-facto distributed knowledge bases are materializing, partly encouraged by the vision of the Semantic Web, the focus is shifting from the publication of this information to its consumption. Platforms for data integration, visualization and analysis that are based on a graph representation of information appear first candidates to be consumers of web-based information that is readily expressible as graphs. The question is whether the adoption of these platforms to information available on the Semantic Web requires some adaptation of their data structures and semantics. Ondex is a network-based data integration, analysis and visualization platform which has been developed in a Life Sciences context. A number of features, including semantic annotation via ontologies and an attention to provenance and evidence, make this an ideal candidate to consume Semantic Web information, as well as a prototype for the application of network analysis tools in this context. By analyzing the Ondex data structure and its usage, we have found a set of discrepancies and errors arising from the semantic mismatch between a procedural approach to network analysis and the implications of a web-based representation of information. We report in the paper on the simple methodology that we have adopted to conduct such analysis, and on issues that we have found which may be relevant for a range of similar platforms

Andrea Splendiani, Albert Burger, Adrian Paschke, Paolo Romano, M. Scott Marshall.

Biomedical Semamtics in the Semantic Web (commentary)

http://www.jbiomedsem.com/content/2/S1/S1

Abstract

The Semantic Web offers an ideal platform for representing and linking biomedical information, which is a prerequisite for the development and application of analytical tools to address problems in data-intensive areas such as systems biology and translational medicine. As for any new paradigm, the adoption of the Semantic Web offers opportunities and poses questions and challenges to the life sciences scientific community: which technologies in the Semantic Web stack will be more beneficial for the life sciences? Is biomedical information too complex to benefit from simple interlinked representations? What are the implications of adopting a new paradigm for knowledge representation? What are the incentives for the adoption of the Semantic Web, and who are the facilitators? Is there going to be a Semantic Web revolution in the life sciences?

We report here a few reflections on these questions, following discussions at the SWAT4LS (Semantic Web Applications and Tools for Life Sciences) workshop series, of which this Journal of Biomedical Semantics special issue presents selected papers from the 2009 edition, held in Amsterdam on November 20^th.

]]> http://www.sgtp.net/AndreaSplendiani/publications/papers/biomedical-semantics-in-the-semantic-web/feed/ 0 52.3730545 4.8922224 http://www.sgtp.net/AndreaSplendiani/publications/edited-by/bmc-jbs-special-issue-on-semantic-web-applications-and-tools-for-life-sciences-2009/ http://www.sgtp.net/AndreaSplendiani/publications/edited-by/bmc-jbs-special-issue-on-semantic-web-applications-and-tools-for-life-sciences-2009/#comments Mon, 07 Mar 2011 14:39:28 +0000 sgtp http://www.sgtp.net/AndreaSplendiani/?p=335

Proceedings of the Workshop on Semantic Web Applications and Tools for Life Sciences (SWAT4LS-2010), Berlin, Germany, December 10, 2010.

Edited by: Albert Burger, M. Scott Marshall, Paolo Romano, Adrian Paschke, Andrea Splendiani

Available at http://CEUR-WS.org/Vol-698/