Abstract Summary: ENViz (Enrichment Analysis and Visualization) is a Cytoscape app that performs joint enrichment analysis of two types of sample matched datasets in the context of systematic annotations. Such datasets may be gene expression or any other high-throughput data collected in the same set of samples. The enrichment analysis is done in the context of pathway information, gene ontology or any custom annotation of the data. The results of the analysis consist of significant associations between profiled elements of one of the datasets to the annotation terms (e.g. miR-19 was associated to the cell-cycle process in breast cancer samples). The results of the enrichment analysis are visualized as an interactive Cytoscape network. Availability and implementation: ENViz is publically available in the Cytoscape App Store (http://apps.cytoscape.org/apps/enviz). For additional information please visit the tool website: http://www.agilent.com/labs/research/compbio/enviz/ Contact: [email protected]

SUMMARY: VistaClara is a plug-in for Cytoscape which provides a more flexible means to visualize gene and protein expression within a network context. An extended attribute browser is provided in the form of a graphical and interactive permutation matrix that resembles the heat map displays popular in gene-expression analysis. This extended browser permits a variety of display options and interactions not currently available in Cytoscape. AVAILABILITY: http://chianti.ucsd.edu/cyto_web/plugins/index.php.

MOTIVATIONS: Technological advances in biomedical research are generating a plethora of heterogeneous data at a high rate. There is a critical need for extraction, integration and management tools for information discovery and synthesis from these heterogeneous data. RESULTS: In this paper, we present a general architecture, called ALFA, for information extraction and representation from diverse biological data. The ALFA architecture consists of: (i) a networked, hierarchical, hyper-graph object model for representing information from heterogeneous data sources in a standardized, structured format; and (ii) a suite of integrated, interactive software tools for information extraction and representation from diverse biological data sources. As part of our research efforts to explore this space, we have currently prototyped the ALFA object model and a set of interactive software tools for searching, filtering, and extracting information from scientific text. In particular, we describe BioFerret, a meta-search tool for searching and filtering relevant information from the web, and ALFA Text Viewer, an interactive tool for user-guided extraction, disambiguation, and representation of information from scientific text. We further demonstrate the potential of our tools in integrating the extracted information with experimental data and diagrammatic biological models via the common underlying ALFA representation. CONTACT: [email protected].

The main task of molecular biologists seeking to understand the molecular basis of disease is identifying and interpreting the relationships of genes, proteins, and pathways in living organisms. While emerging technologies have provided powerful analysis tools to this end, they have also produced an explosion of data, which biologists need to make sense of. We have built software tools to support the synthesis activities of molecular biologists, in particular the activities of organizing, retrieving, using, sharing, and reusing diverse biological information. A key aspect of our approach, based upon the findings of user studies, is the use of narrative structure as a conceptual framework for developing and representing the "story" of how genes, proteins, and other molecules interact in biological processes. Biological stories are represented both textually and graphically within a simple conceptual model of items, collections, and stories.

FotoFile is an experimental system for multimedia organization and retrieval, based upon the design goal of making multimedia content accessible to non-expert users. Search and retrieval are done in terms that are natural to the task. The system blends human and automatic annotation methods. It extends textual search, browsing, and retrieval technologies to support multimedia data types.