StemNet - Knowledge Management for Hematopoietic Stem Cell Transplantation

The goal of the StemNet Project (http://www.stemnet.de) is to develop a knowledge management system for Hematopoietic Stem Cell Transplantation and Immunogenetics [1] in order to assist biomedical researchers and practitioners in finding relevant information. The evolving knowledge service goes beyond tradtional approaches in that enables a targeted and fine-grained search for relevant biomedical entities (e.g. various protein functions, different types of immune cells, various sorts of antigens, blood diseases, clinical outcomes, etc.) in unstructured biomedical free text, in particular PubMed abstracts. At the same time, this information is linked to relevant biological database and ontology entries, such as UniProt, Entrez Gene, dbSNP, the Gene Ontology, the Sequence Ontology, and the Cell Ontology (see http://obo.sourceforge.net). Thus, StemNet enables the linking of heterogenuous knowledge sources to which the user only had separate access before. Semantic search and retrieval requires linguistic and semantic processing of documents. For this purpose, we employ state-of-the-art text-mining technologies [2, 3, 4, 5] , both to annotate and recognize semantic entities as well as to link them to databases and ontologies. Documents and their semantic metadata are then presented to the user via the Lucene search engine (http://lucene.apache.org/java/docs/index. html). In order to target user queries, annotated semantic entities are kept in special indices.