MOTIVATION: The Burrows-Wheeler transform (BWT) is widely used for the fast alignment of high-throughput sequence data. This method also has potential applications in other areas of bioinformatics, and it can be specially useful for the fast searching of patterns on coverage data from different sources. RESULTS: We present a nucleosome pattern search method that converts levels of nucleosomal occupancy to a sequence-like format to which BWT searches can be applied. The method is embedded in a nucleosome map browser, 'Nucleosee', an interactive visual tool specifically designed to enhance BWT searches, giving them context and making them suitable for visual discourse analysis of the results. The proposed method is fast, flexible and sufficiently generic for the exploration of data in a broad and interactive way. AVAILABILITY AND IMPLEMENTATION: The proposed algorithm and visual browser are available for testing at http://cpg3.der.usal.es/nucleosee. The source code and installation packages are also available at https://github.com/rodrigoSantamaria/nucleosee. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: Systems biology demands the use of several point of views to get a more comprehensive understanding of biological problems. This usually leads to take into account different data regarding the problem at hand, but it also has to do with using different perspectives of the same data. This multifaceted aspect of systems biology often requires the use of several tools, and it is often hard to get a seamless integration of all of them, which would help the analyst to have an interactive discourse with the data. RESULTS: Focusing on expression profiling, BicOverlapper 2.0 visualizes the most relevant aspects of the analysis, including expression data, profiling analysis results and functional annotation. It also integrates several state-of-the-art numerical methods, such as differential expression analysis, gene set enrichment or biclustering. AVAILABILITY AND IMPLEMENTATION: BicOverlapper 2.0 is available at: http://vis.usal.es/bicoverlapper2

MOTIVATION: Several techniques analyze gene expression data from the point of view of biological ontologies. These methods focus on statistical and numerical analyses, but there is an additional need for fast, global and interactive visualizations of gene expression data in the context of biological ontologies. RESULTS: Voronto addresses these needs with an easy to use integration of custom gene expression data with custom or public ontologies. In order to do that, it implements Voronoi diagrams where ontologies are mapped with gene expression, providing a quick hierarchy browsing and integration with ontology's resources. AVAILABILITY: The tool is available at http://vis.usal.es/voronto. Source code available at https:/github.com/rodrigoSantamaria/Voronto.

SUMMARY: Treevolution is a tool for the representation and exploration of phylogenetic trees that facilitates visual analysis. There are several useful tools to visualize phylogenetic trees, but their level of interaction is usually low, especially in the case of radial representations. Highly interactive visualizations can improve the exploration and understanding of phylogenetic trees. Treevolution implements strategies to interact with phylogenetic trees in order to allow a more thorough analysis by users. AVAILABILITY: Treevolution is available at http://vis.usal.es/treevolution. Additional figures, a user's guide, a video demo and some examples are available at the same site. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UNLABELLED: BicOverlapper is a tool to visualize biclusters from gene-expression matrices in a way that helps to compare biclustering methods, to unravel trends and to highlight relevant genes and conditions. A visual approach can complement biological and statistical analysis and reduce the time spent by specialists interpreting the results of biclustering algorithms. The technique is based on a force-directed graph where biclusters are represented as flexible overlapped groups of genes and conditions. AVAILABILITY: The BicOverlapper software and supplementary material are available at http://vis.usal.es/bicoverlapper

BACKGROUND: Microarray analysis is an important area of bioinformatics. In the last few years, biclustering has become one of the most popular methods for classifying data from microarrays. Although biclustering can be used in any kind of classification problem, nowadays it is mostly used for microarray data classification. A large number of biclustering algorithms have been developed over the years, however little effort has been devoted to the representation of the results. RESULTS: We present an interactive framework that helps to infer differences or similarities between biclustering results, to unravel trends and to highlight robust groupings of genes and conditions. These linked representations of biclusters can complement biological analysis and reduce the time spent by specialists on interpreting the results. Within the framework, besides other standard representations, a visualization technique is presented which is based on a force-directed graph where biclusters are represented as flexible overlapped groups of genes and conditions. This microarray analysis framework (BicOverlapper), is available at http://vis.usal.es/bicoverlapper CONCLUSION: The main visualization technique, tested with different biclustering results on a real dataset, allows researchers to extract interesting features of the biclustering results, especially the highlighting of overlapping zones that usually represent robust groups of genes and/or conditions. The visual analytics methodology will permit biology experts to study biclustering results without inspecting an overwhelming number of biclusters individually.