The goal of the National Cancer Institute's cancer Biomedical Informatics Grid initiative, or caBIG®, is the ability to share data and resources among cancer researchers. One means to achieving this goal is the development of semantically interoperable informatics tools based on common data models and controlled vocabularies. A tool for managing biospecimen repositories, caTissue, enables investigators to query for available tissues that are relevant to the needs of their research. For this functionality, the caTissue application data model must include annotation describing various specimen characteristics, and have this information accessible for query by the researcher end user. Having deployed caTissue over two years at Thomas Jefferson University, we report the lessons learned from our investigators' use of this complex, semantically interoperable software application. Overall we have found that object model complexity and semantic completeness pose obstacles to end user accessibility that require effective strategies to overcome.

A fixed-point alignment analysis technique is presented which is designed to locate common sequence motifs in collections of proteins or nucleic acids. Initially a program aligns a collection of sequences by a common sequence pattern or known biological feature. The common pattern or feature (fixed-point) may be a user-specified sequence string or a known sequence position like mRNA start site, which may be taken directly from the annotated feature table of GenBank. Once all alignment markers are located, the sequences are scanned for occurrences of given oligomers within a specified span both upstream and downstream of the fixed-point. The occurrences may then be plotted as a function of the position relative to the fixed-point, displayed as an actual sequence alignment or selectively summarized via various program options. Applications of the technique are discussed.