PubMed · 16195710
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
2005. Sequence specificity.. https://doi.org/10.1038/ng1005-1013
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
BACKGROUND: Genomic functional information is valuable for biomedical research. However, such information frequently needs to be extracted from the scientific literature and structured in order to be exploited by automatic systems. Natural language processing is increasingly used for this purpose although it inherently involves errors. A postprocessing strategy that selects relations most likely to be correct is proposed and evaluated on the output of SemGen, a system that extracts semantic predications on the etiology of genetic diseases. Based on the number of intervening phrases between an argument and its predicate, we defined a heuristic strategy to filter the extracted semantic relations according to their likelihood of being correct. We also applied this strategy to relations identified with co-occurrence processing. Finally, we exploited postprocessed SemGen predications to investigate the genetic basis of Parkinson's disease. RESULTS: The filtering procedure for increased precision is based on the intuition that arguments which occur close to their predicate are easier to identify than those at a distance. For example, if gene-gene relations are filtered for arguments at a distance of 1 phrase from the predicate, precision increases from 41.95% (baseline) to 70.75%. Since this proximity filtering is based on syntactic structure, applying it to the results of co-occurrence processing is useful, but not as effective as when applied to the output of natural language processing. In an effort to exploit SemGen predications on the etiology of disease after increasing precision with postprocessing, a gene list was derived from extracted information enhanced with postprocessing filtering and was automatically annotated with GFINDer, a Web application that dynamically retrieves functional and phenotypic information from structured biomolecular resources. Two of the genes in this list are likely relevant to Parkinson's disease but are not associated with this disease in several important databases on genetic disorders. CONCLUSION: Information based on the proximity postprocessing method we suggest is of sufficient quality to be profitably used for subsequent applications aimed at uncovering new biomedical knowledge. Although proximity filtering is only marginally effective for enhancing the precision of relations extracted with co-occurrence processing, it is likely to benefit methods based, even partially, on syntactic structure, regardless of the relation.
Newborn screening started in the 1960s for the purpose of identifying phenylketonuric patients to begin early intervention and to prevent mental retardation in these patients. Soon thereafter, screening programs expanded to include additional genetic disorders added individually one at a time. In the 1980s, tandem mass spectrometry (MS/MS) was introduced in clinical laboratories, and in the 1990s, the technique was used for newborn screening. Unlike measuring one analyte at a time, MS/MS allows measurement of >40 analytes, in a few minutes with the use of a single assay. Currently, MS/MS is being used for the identification of several amino acid, organic acid and fatty acid disorders. Several states in the United States and many other countries are using MS/MS in newborn screening. However, there is a significant disparity among different newborn screening programs for disorders being screened by MS/MS and many other challenges are faced by the expanded newborn screening. It is anticipated that in the future the use of MS/MS in newborn screening will expand both at the analyte and geographic levels. Clinicians and laboratory scientists should become familiar with MS/MS, disorders being screened in their patients' population and the future of this emerging technology.
Explore the source record for details and available documents.