Title :
Labeling and enhancing life sciences links
Author :
Heymann, S. ; Naumann, F. ; Raschid, L. ; Rieger, P.
Author_Institution :
University of Maryland
Abstract :
Life sciences data sources contain data about scientific objects such as genes and sequences that are richly interconnected, i.e., a gene object may have links to sequences, proteins, SNPs, citations, etc. Scientific knowledge is enhanced by exploration of relationships between scientific objects, requiring traversal of both links and paths (informally concatenations of links). There are significant limitations and challenges of such exploration, because the links are inherently poor with respect to syntactic representation and semantic knowledge. The links are syntactically poor because the source
Keywords :
Algorithm design and analysis; Bioinformatics; Data models; Database languages; Diseases; HTML; Humans; Labeling; Performance analysis; Proteins;
Conference_Titel :
Computational Systems Bioinformatics Conference, 2004. CSB 2004. Proceedings. 2004 IEEE
Conference_Location :
Stanford, CA, USA
Print_ISBN :
0-7695-2194-0
DOI :
10.1109/CSB.2004.1332512
