Tools for loading MEDLINE into a local relational database

Background  

Researchers who use MEDLINE for text mining, information extraction, or natural language processing may benefit from having a copy of MEDLINE that they can manage locally. The National Library of Medicine (NLM) distributes MEDLINE in eXtensible Markup Language (XML)-formatted text files, but it is difficult to query MEDLINE in that format. We have developed software tools to parse the MEDLINE data files and load their contents into a relational database. Although the task is conceptually straightforward, the size and scope of MEDLINE make the task nontrivial. Given the increasing importance of text analysis in biology and medicine, we believe a local installation of MEDLINE will provide helpful computing infrastructure for researchers.     

Ranking the whole MEDLINE database according to a large training set using text indexing

Background  

The MEDLINE database contains over 12 million references to scientific literature, with about 3/4 of recent articles including an abstract of the publication. Retrieval of entries using queries with keywords is useful for human users that need to obtain small selections. However, particular analyses of the literature or database developments may need the complete ranking of all the references in the MEDLINE database as to their relevance to a topic of interest. This report describes a method that does this ranking using the differences in word content between MEDLINE entries related to a topic and the whole of MEDLINE, in a computational time appropriate for an article search query engine.     

Purine cytokinin nomenclature: a working system of abbreviations

Many synonyms for the cytokinin 6-(benzylamino)purine and its metabolites have arisen in the literature despite a 1970 IUPAC-IUB directive delimiting such nomenclature. Examples of symbols and abbreviations for some classes of this cytokinin are given. The reasons for this continued synonomy are attributed to difficulties associated with the IUPAC-IUB recommendations. A modified system of abbreviations is presented in tabular form and the utility of the scheme discussed.     

Cloning and chromosomal mapping of mouse ADAM11, ADAM22 and ADAM23.

A cellular disintegrin, also called MDC and ADAM is a recently discovered gene family that encodes protein with disintegrin-like and metalloprotease-like domains. We have reported the identification of human cDNAs encoding novel ADAM family proteins that we named MDC2 and MDC3 because of their structural similarity to the MDC (Sagane, K. et al., 1998. Biochem. J. 334, 93-98). The Human Gene Nomenclature Committee assigned the gene symbols ADAM11 for the MDC, ADAM22 for the MDC2 and ADAM23 for the MDC3. Here we report the isolation of three novel murine cDNAs encoding the proteins closely related to the human ADAM11, ADAM22 and ADAM23. Their chromosomal locations in the mouse were identified by interspecies backcross mapping. The loci of these murine ADAM genes were in good accordance with the location of each human ortholog, ADAM11, ADAM22 and ADAM23. These findings suggest that three murine cDNAs that we have isolated are the murine ADAM11, ADAM22 and ADAM23 cDNAs. Northern blot analysis shows that all of these three murine ADAMs were highly expressed in the mouse brain. The structures of these ADAM proteins strongly suggest that they could function as integrin receptors. The implications of the cellular disintegrins in neural development are discussed.     

Putative function of ADAM9, ADAM10, and ADAM17 as APP alpha-secretase

The putative alpha-secretase cleaves the amyloid precursor protein (APP) of Alzheimer's disease in the middle of the amyloid beta peptide (Abeta) domain. It is generally thought that the alpha-secretase pathway mitigates Abeta formation in the normal brain. Several studies have suggested that ADAM9, ADAM10, and ADAM17 are candidate alpha-secretases belonging to the ADAM (a disintegrin and metalloprotease) family, which are membrane-anchored cell surface proteins. In this comparative study of ADAM9, ADAM10, and ADAM17, we examined the physiological role of ADAMs by expressing these ADAMs in COS-7 cells, and both "constitutive" and "regulated" alpha-secretase activities of these ADAMs were determined. We tried to suppress the expression of these ADAMs in human glioblastoma A172 cells, which contain large amounts of endogenous alpha-secretase, by lipofection of the double-stranded RNA (dsRNA) encoding each of these ADAMs. The results indicate that ADAM9, ADAM10, and ADAM17 catalyze alpha-secretory cleavage and therefore act as alpha-secretases in A172 cells. This is the first report that to suggest the endogenous alpha-secretase is composed of several ADAM enzymes.     

XplorMed: a tool for exploring MEDLINE abstracts

The most frequent access to the MEDLINE database of scientific abstracts is by keyword search. However, this is often not sufficient because although the user might find all the useful abstracts, these are buried in hundreds that are irrelevant. The exploratory tool XplorMed has been developed to analyse the result of any MEDLINE query. It suggests main groups of related topics and documents, sparing the user the need of reading all abstracts.     

ADAM function in embryogenesis

Cleavage of proteins inserted into the plasma membrane (shedding) is an essential process controlling many biological functions including cell signaling, cell adhesion and migration as well as proliferation and differentiation. ADAM surface metalloproteases have been shown to play an essential role in these processes. Gene inactivation during embryonic development have provided evidence of the central role of ADAM proteins in nematodes, flies, frogs, birds and mammals. The relative contribution of four subfamilies of ADAM proteins to developmental processes is the focus of this review.     

Resolving abbreviations to their senses in Medline

MOTIVATION: Biological literature contains many abbreviations with one particular sense in each document. However, most abbreviations do not have a unique sense across the literature. Furthermore, many documents do not contain the long forms of the abbreviations. Resolving an abbreviation in a document consists of retrieving its sense in use. Abbreviation resolution improves accuracy of document retrieval engines and of information extraction systems. RESULTS: We combine an automatic analysis of Medline abstracts and linguistic methods to build a dictionary of abbreviation/sense pairs. The dictionary is used for the resolution of abbreviations occurring with their long forms. Ambiguous global abbreviations are resolved using support vector machines that have been trained on the context of each instance of the abbreviation/sense pairs, previously extracted for the dictionary set-up. The system disambiguates abbreviations with a precision of 98.9% for a recall of 98.2% (98.5% accuracy). This performance is superior in comparison with previously reported research work. AVAILABILITY: The abbreviation resolution module is available at http://www.ebi.ac.uk/Rebholz/software.html.