Literature DB >> 16899496

The Life Sciences Semantic Web is full of creeps!

Benjamin M Good1, Mark D Wilkinson.   

Abstract

The Semantic Web for the Life Sciences (SWLS), when realized, will dramatically improve our ability to conduct bioinformatics analyses using the vast and growing stores of web-accessible resources. This ability will be achieved through the widespread acceptance and application of standards for naming, representing, describing and accessing biological information. The W3C-led Semantic Web initiative has established most, if not all, of the standards and technologies needed to achieve a unified, global SWLS. Unfortunately, the bioinformatics community has, thus far, appeared reluctant to fully adopt them. Rather, we are seeing what could be described as 'semantic creep'-timid, piecemeal and ad hoc adoption of parts of standards by groups that should be stridently taking a leadership role for the community. We suggest that, at this point, the primary hindrances to the creation of the SWLS may be social rather than technological in nature, and that, like the original Web, the establishment of the SWLS will depend primarily on the will and participation of its consumers.

Mesh:

Year:  2006        PMID: 16899496     DOI: 10.1093/bib/bbl025

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  22 in total

1.  Semantic integration of data on transcriptional regulation.

Authors:  Michael Baitaluk; Julia Ponomarenko
Journal:  Bioinformatics       Date:  2010-04-28       Impact factor: 6.937

Review 2.  Genomic and genetic database resources for the grasses.

Authors:  Kevin L Childs
Journal:  Plant Physiol       Date:  2009-01       Impact factor: 8.340

3.  Bringing Web 2.0 to bioinformatics.

Authors:  Zhang Zhang; Kei-Hoi Cheung; Jeffrey P Townsend
Journal:  Brief Bioinform       Date:  2008-10-08       Impact factor: 11.622

4.  Learning from biomedical linked data to suggest valid pharmacogenes.

Authors:  Kevin Dalleau; Yassine Marzougui; Sébastien Da Silva; Patrice Ringot; Ndeye Coumba Ndiaye; Adrien Coulet
Journal:  J Biomed Semantics       Date:  2017-04-20

5.  Seahawk: moving beyond HTML in Web-based bioinformatics analysis.

Authors:  Paul M K Gordon; Christoph W Sensen
Journal:  BMC Bioinformatics       Date:  2007-06-18       Impact factor: 3.169

6.  The Ontology for Parasite Lifecycle (OPL): towards a consistent vocabulary of lifecycle stages in parasitic organisms.

Authors:  Priti P Parikh; Jie Zheng; Flora Logan-Klumpler; Christian J Stoeckert; Christos Louis; Pantelis Topalis; Anna V Protasio; Amit P Sheth; Mark Carrington; Matthew Berriman; Satya S Sahoo
Journal:  J Biomed Semantics       Date:  2012-05-23

7.  Current trends and new challenges of databases and web applications for systems driven biological research.

Authors:  Pradeep Kumar Sreenivasaiah; Do Han Kim
Journal:  Front Physiol       Date:  2010-12-03       Impact factor: 4.566

8.  BiologicalNetworks--tools enabling the integration of multi-scale data for the host-pathogen studies.

Authors:  Sergey Kozhenkov; Mayya Sedova; Yulia Dubinina; Amarnath Gupta; Animesh Ray; Julia Ponomarenko; Michael Baitaluk
Journal:  BMC Syst Biol       Date:  2011-01-14

9.  BioGateway: a semantic systems biology tool for the life sciences.

Authors:  Erick Antezana; Ward Blondé; Mikel Egaña; Alistair Rutherford; Robert Stevens; Bernard De Baets; Vladimir Mironov; Martin Kuiper
Journal:  BMC Bioinformatics       Date:  2009-10-01       Impact factor: 3.169

10.  OPPL-Galaxy, a Galaxy tool for enhancing ontology exploitation as part of bioinformatics workflows.

Authors:  Mikel Egaña Aranguren; Jesualdo Tomás Fernández-Breis; Chris Mungall; Erick Antezana; Alejandro Rodríguez González; Mark D Wilkinson
Journal:  J Biomed Semantics       Date:  2013-01-04
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