CARGO: a web portal to integrate customized biological information

Abstract

There is a huge quantity of information generated in Life Sciences, and it is dispersed in many databases and repositories. Despite the broad availability of the information, there is a great demand for methods that are able to look for, gather and display distributed data in a standardized and friendly way. CARGO (Cancer And Related Genes Online) is a configurable biological web portal designed as a tool to facilitate, integrate and visualize results from Internet resources, independently of their native format or access method. Through the use of small agents, called widgets, supported by a Rich Internet Application (RIA) paradigm based on AJAX, CARGO provides pieces of minimal, relevant and descriptive biological information. The tool is designed to be used by experimental biologists with no training in bioinformatics. In the current state, the system presents a list of human cancer genes. Available at http://cargo.bioinfo.cnio.es.

Figure 1.

The Cargo System. (a) Query module: available options are free-text search and pre-compiled lists of genes. (b) Core module: retrieves potential genes matching the input query. The user selects a gene from the results obtained, and the system dispatches the information to all the available widgets, which refresh accordingly. (c) Widgets: The widgets are activated by the user. Each widget provides concise information at different levels. The technologies and procedures used by the widget are hidden from the user. (d) In the example, the system fetches PDB files using FTP, then extracts information about sequence/structure alignments from The Sanger Institute (http://das.sanger.ac.uk/das/msdpdbsp/) using DAS (4), and conducts queries about SNPs using the Ensembl Variation API (http://www.ensembl.org/info/software/variation/index.html).

Figure 2.

Use of Cargo. The left frame shows the query interface. As an example, a search for ‘P53’ (red star) is shown. At the top, a small description is provided to the user. The rest of the working space shows the different widgets. Black boxes indicate activated widgets (iHOP, OMIM and SNP 3D). Black circles show the widget interface for visual configuration. By activating the SNP 3D widget, information about coding SNPs, structures and correspondence between them is provided (red lines). The OMIM widget provides information regarding allelic variants and diseases (blue lines). In the example, it links a specific allelic variant to hepatocellular carcinoma, which can then be visualized in the structure. The iHOP widget provides information from literature in the context of sentences. Therefore, the terms used by the query and other important labels (such as MeSH terms), are also highlighted (green pop-up, showing ‘Carcinoma, hepatocellular’ in iHOP widget) and a link to the original paper is provided.