Topic I: A Fuzzy Set Theory Approach for the Analysis of Biological Literature and Topic I: Extraction of Molecular Biology features from the full text of scientific papers

The increment of information in biology makes it difficult for researchers in the field to keep up-to-date with the literature. Searching scientific literature is an information retrieval problem.
The MEDLINE database of scientific abstracts can be scanned using electronic mechanisms. Tentatively intersting abstracts can be selected by matching words joined by boolean operators. However, this way of selecting documents is not optimal. Non-specific queries have to be effected. In order to aid this analysis we have developed a system that complies a summary of subjects and related documents on the results of MEDLINE query. For this, we have applied a fuzzy binary relation formalism that deduces relations between words present in set of abstracts preprocessed with a standard grammatical tagger. Those relations are used to derive ensembles of related words and their associated subsets of abstracts


Topic II;

A database of full text is made for the storage of full text scientific papers appearing in journals those are electronically accessible. Entries to database is submitted automatically,
in organised way. For this we have already developed a mechanism. Database of full text papers is developed, because then we will be able to extract more biological features, and accuracy of the system in extracting biological features will also increase. In order to help the development of molecular biology databases and to extract information, we will develope templates for the diverse molecular phenomena. Uptill now only databases of journal abstracts are available