Semantic text mining support for lignocellulose research

BMC Medical Informatics and Decision Making

Proceedings

Ingo Morgenstern¹  Adrian Tsang¹  Caitlin Murphy¹  Justin Powlowski²  René Witte³  Marie-Jean Meurs⁴  Greg Butler⁴ 

[1] Centre for Structural and Functional Genomics, Concordia University, Montréal, QC, Canada;Department of Biology, Concordia University, Montreal, QC, Canada;Centre for Structural and Functional Genomics, Concordia University, Montréal, QC, Canada;Department of Chemistry and Biochemistry, Concordia University, Montréal, QC, Canada;Department of Computer Science and Software Engineering, Concordia University, Montréal, QC, Canada;Department of Computer Science and Software Engineering, Concordia University, Montréal, QC, Canada;Centre for Structural and Functional Genomics, Concordia University, Montréal, QC, Canada;

关键词: Natural Language Processing;    Manual Annotation;    Grammar Rule;    Semantic Entity;    Gold Standard Corpus;   

DOI  :  10.1186/1472-6947-12-S1-S5

来源: Springer

【 摘 要 】

BackgroundBiofuels produced from biomass are considered to be promising sustainable alternatives to fossil fuels. The conversion of lignocellulose into fermentable sugars for biofuels production requires the use of enzyme cocktails that can efficiently and economically hydrolyze lignocellulosic biomass. As many fungi naturally break down lignocellulose, the identification and characterization of the enzymes involved is a key challenge in the research and development of biomass-derived products and fuels. One approach to meeting this challenge is to mine the rapidly-expanding repertoire of microbial genomes for enzymes with the appropriate catalytic properties.ResultsSemantic technologies, including natural language processing, ontologies, semantic Web services and Web-based collaboration tools, promise to support users in handling complex data, thereby facilitating knowledge-intensive tasks. An ongoing challenge is to select the appropriate technologies and combine them in a coherent system that brings measurable improvements to the users. We present our ongoing development of a semantic infrastructure in support of genomics-based lignocellulose research. Part of this effort is the automated curation of knowledge from information on fungal enzymes that is available in the literature and genome resources.ConclusionsWorking closely with fungal biology researchers who manually curate the existing literature, we developed ontological natural language processing pipelines integrated in a Web-based interface to assist them in two main tasks: mining the literature for relevant knowledge, and at the same time providing rich and semantically linked information.

【 授权许可】

CC BY   
© Meurs et al.; licensee BioMed Central Ltd. 2012