Supplement to Application and evaluation of automated semantic annotation of gene expression experiments.
French L, Lane S, Law T, Xu L, Pavlidis P 
Bioinformatics (Oxford, England) 2009 Jun 15;25(12):1543-9
Abstract
Motivation:
Many microarray datasets are available online with formalized standards describing the probe sequences and expression values. Unfortunately, the description, conditions and parameters of the experiments are less commonly formalized and often occur as natural language text. This hinders searching, high-throughput analysis, organization and integration of the datasets.
Results:
We use the lexical resources and software tools from the Unified Medical Language System (UMLS) to extract concepts from text. We then link the UMLS concepts to classes in open biomedical ontologies. The result is accessible and clear semantic annotations of gene expression experiments. We applied the method to 595 expression experiments from Gemma, a resource for re-use and meta-analysis of gene expression profiling data. We evaluated and corrected all stages of the annotation process. The majority of missed annotations were due to a lack of cross-references. The most error prone stage was the extraction of concepts from phrases. Final review of the annotations in context of the experiments revealed 89% precision. We have integrated the annotation pipeline into Gemma.
Citation:
Leon French, Suzanne Lane, Tamryn Law, Lydia Xu, and Paul Pavlidis (2009) Application and evaluation of automated semantic annotation of gene expression experiments. Bioinformatics 25(12):1543-1549; doi:10.1093/bioinformatics/btp259
Example:
A detailed guide to how an example text fragment is annotated by the system.
Annotations:
Both manual and predicted annotations can be viewed and searched via the Gemma website.
Required Resources:
Recommended Resources:
Gemma
The Open Biomedical Ontologies
NCBO Bioportal
Jena
Tabulator Extension