Biomedical subjects

Susanne M Humphrey

Publications and source records attributed to Susanne M Humphrey.

5 recordsLinked to original sources

PubMed2005

Using literature-based discovery to identify disease candidate genes.

We present BITOLA, an interactive literature-based biomedical discovery support system. The goal of this system is to discover new, potentially meaningful relations between a given starting concept of interest and other concepts, by mining the bibliographic database MEDLINE. To make the system more suitable for disease candidate gene discovery and to decrease the number of candidate relations, we integrate background knowledge about the chromosomal location of the starting disease as well as the chromosomal location of the candidate genes from resources such as LocusLink and Human Genome Organization (HUGO). BITOLA can also be used as an alternative way of searching the MEDLINE database. The system is available at http://www.mf.uni-lj.si/bitola/.

Algorithms↗

PubMed2005

Determining prominent subdomains in medicine.

We discuss an automated method for identifying prominent subdomains in medicine. The motivation is to enhance the results of natural language processing by focusing on sublanguages associated with medical specialties concerned with prevalent disorders. At the core of our approach is a statistical system for topical categorization of medical text. A method based on epidemiological evidence is compared to another that considers frequency of occurrence of Medline citations. We suggest the isolation of UMLS terminology peculiar to individual medical specialties as a way of enhancing natural language processing systems in the biomedical domain.

Abstracting and Indexing↗

PubMed2004

The NLM Indexing Initiative's Medical Text Indexer.

The Medical Text Indexer (MTI) is a program for producing MeSH indexing recommendations. It is the major product of NLM's Indexing Initiative and has been used in both semi-automated and fully automated indexing environments at the Library since mid 2002. We report here on an experiment conducted with MEDLINE indexers to evaluate MTI's performance and to generate ideas for its improvement as a tool for user-assisted indexing. We also discuss some filtering techniques developed to improve MTI's accuracy for use primarily in automatically producing the indexing for several abstracts collections.

Abstracting and Indexing↗

PubMed2003

Improving literature based discovery support by genetic knowledge integration.

We present an interactive literature based biomedical discovery support system (BITOLA). The goal of the system is to discover new, potentially meaningful relations between a given starting concept of interest and other concepts, by mining the bibliographic database Medline. To make the system more suitable for disease candidate gene discovery and to decrease the number of candidate relations, we integrate background knowledge about the chromosomal location of the starting disease as well as the chromosomal location of the candidate genes from resources such as LocusLink, HUGO and OMIM. The BITOLA system can be also used as an alternative way of searching the Medline database. The system is available at http://www.mf.uni-lj.si/bitola/.

Algorithms↗

PubMed2003

Gene indexing: characterization and analysis of NLM's GeneRIFs.

We present an initial analysis of the National Library of Medicine's (NLM) Gene Indexing initiative. Gene Indexing occurs at the time of indexing for all 4600 journals and over 500,000 articles added to PubMed/MEDLINE each year. Gene Indexing links articles about the basic biology of a gene or protein within eight model organisms to a specific record in the NLM's LocusLink database of gene products. The result is an entry called a Gene Reference Into Function (GeneRIF) within the LocusLink database. We analyzed the numbers of GeneRIFs produced in the first year of GeneRIF production. 27,645 GeneRIFs were produced, pertaining to 9126 loci over eight model organisms. 60% of these were associated with human genes and 27% with mouse genes. About 80% discuss genes with an established MeSH Heading or other MeSH term. We developed a prototype functional alerting system for researchers based on the GeneRIFs, and a strategy to find all of the literature related to genes. We conclude that the Gene Indexing initiative adds considerable value to the life sciences research community.

Abstracting and Indexing↗