In this paper, we describe an application, PubCloud that uses tagclouds for the summarization of results from queries over thePubMed database of biomedical literature. PubCloud responds toqueries of this database with tag clouds generated from wordsextracted from the abstracts returned by the query. The results ofa user study comparing the PubCloud tag-cloud summarization ofquery results with the standard result list provided by PubMedindicated that the tag cloud interface is advantageous in presenting descriptive information and in reducing user frustrationbut that it is less effective at the task of enabling users to discoverrelations between concepts.

BACKGROUND: User-scripts are programs stored in Web browsers that can manipulate the content of websites prior to display in the browser. They provide a novel mechanism by which users can conveniently gain increased control over the content and the display of the information presented to them on the Web. As the Web is the primary medium by which scientists retrieve biological information, any improvements in the mechanisms that govern the utility or accessibility of this information may have profound effects. GreaseMonkey is a Mozilla Firefox extension that facilitates the development and deployment of user-scripts for the Firefox web-browser. We utilize this to enhance the content and the presentation of the iHOP (information Hyperlinked Over Proteins) website. RESULTS: The iHOPerator is a GreaseMonkey user-script that augments the gene-centred pages on iHOP by providing a compact, configurable visualization of the defining information for each gene and by enabling additional data, such as biochemical pathway diagrams, to be collected automatically from third party resources and displayed in the same browsing context. CONCLUSION: This open-source script provides an extension to the iHOP website, demonstrating how user-scripts can personalize and enhance the Web browsing experience in a relevant biological setting. The novel, user-driven controls over the content and the display of Web resources made possible by user-scripts, such as the iHOPerator, herald the beginning of a transition from a resource-centric to a user-centric Web experience. We believe that this transition is a necessary step in the development of Web technology that will eventually result in profound improvements in the way life scientists interact with information.

Serial analysis of gene expression (SAGE) not only is a method for profiling the global expression of genes, but also offers the opportunity for the discovery of novel transcripts. SAGE tags are mapped to known transcripts to determine the gene of origin. Tags that map neither to a known transcript nor to the genome were hypothesized to span a splice junction, for which the exon combination or exon(s) are unknown. To test this hypothesis, we have developed an algorithm, SAGE2Splice, to efficiently map SAGE tags to potential splice junctions in a genome. The algorithm consists of three search levels. A scoring scheme was designed based on position weight matrices to assess the quality of candidates. Using optimized parameters for SAGE2Splice analysis and two sets of SAGE data, candidate junctions were discovered for 5%-6% of unmapped tags. Candidates were classified into three categories, reflecting the previous annotations of the putative splice junctions. Analysis of predicted tags extracted from EST sequences demonstrated that candidate junctions having the splice junction located closer to the center of the tags are more reliable. Nine of these 12 candidates were validated by RT-PCR and sequencing, and among these, four revealed previously uncharacterized exons. Thus, SAGE2Splice provides a new functionality for the identification of novel transcripts and exons. SAGE2Splice is available online at http://www.cisreg.ca.