Summary: WAVES is a web application dedicated to bioinformatic tool integration. It provides an efficient way to implement a service for any bioinformatic software. Such services are automatically made available in three ways: web pages, web forms to include in remote websites and a RESTful web services single application programing interface to access remotely from applications. In order to fulfill the service's computational needs, WAVES can perform computation on various resources and environments, such as Galaxy instances. Availability and implementation: WAVES was developed with Django, a Python-based web framework. It was designed as a reusable web application. It is fully portable, as only a Python installation is required to run Django. It is licensed under GNU General Public License. Source code, documentation with examples and demo are available from http://www.atgc-montpellier.fr/waves/. Supplementary information: Supplementary data are available at Bioinformatics online.

Motivation: A reconciliation is an annotation of the nodes of a gene tree with evolutionary events-for example, speciation, gene duplication, transfer, loss, etc.-along with a mapping onto a species tree. Many algorithms and software produce or use reconciliations but often using different reconciliation formats, regarding the type of events considered or whether the species tree is dated or not. This complicates the comparison and communication between different programs. Results: Here, we gather a consortium of software developers in gene tree species tree reconciliation to propose and endorse a format that aims to promote an integrative-albeit flexible-specification of phylogenetic reconciliations. This format, named recPhyloXML, is accompanied by several tools such as a reconciled tree visualizer and conversion utilities. Availability and implementation: http://phylariane.univ-lyon1.fr/recphyloxml/.

BACKGROUND: Comparative genomics is a central step in many sequence analysis studies, from gene annotation and the identification of new functional regions in genomes, to the study of evolutionary processes at the molecular level (speciation, single gene or whole genome duplications, etc.) and phylogenetics. In that context, databases providing users high quality homologous families and sequence alignments as well as phylogenetic trees based on state of the art algorithms are becoming indispensable. METHODS: We developed an automated procedure allowing massive all-against-all similarity searches, gene clustering, multiple alignments computation, and phylogenetic trees construction and reconciliation. The application of this procedure to a very large set of sequences is possible through parallel computing on a large computer cluster. RESULTS: Three databases were developed using this procedure: HOVERGEN, HOGENOM and HOMOLENS. These databases share the same architecture but differ in their content. HOVERGEN contains sequences from vertebrates, HOGENOM is mainly devoted to completely sequenced microbial organisms, and HOMOLENS is devoted to metazoan genomes from Ensembl. Access to the databases is provided through Web query forms, a general retrieval system and a client-server graphical interface. The later can be used to perform tree-pattern based searches allowing, among other uses, to retrieve sets of orthologous genes. The three databases, as well as the software required to build and query them, can be used or downloaded from the PBIL (Pôle Bioinformatique Lyonnais) site at http://pbil.univ-lyon1.fr/.

UNLABELLED: We present a web service allowing to automatically assign sequences to homologous gene families from a set of databases. After identification of the most similar gene family to the query sequence, this sequence is added to the whole alignment and the phylogenetic tree of the family is rebuilt. Thus, the phylogenetic position of the query sequence in its gene family can be easily identified. AVAILABILITY: http://pbil.univ-lyon1.fr/software/HoSeqI/.

Data warehouses are dedicated to collecting heterogeneous and distributed data in order to perform decision analysis. Based on multidimensional model, OLAP commercial environments such as they are currently designed in traditional applications are used to provide means for the analysis of facts that are depicted by numeric data (e.g., sales depicted by amount or quantity sold). However, in numerous fields, like in medical or bioinformatics, multimedia data are used as valuable information in the decisional process. One of the problems when integrating multimedia data as facts in a multidimensional model is to deal with dimensions built on descriptors that can be obtained by various computation modes on raw multimedia data. Taking into account these computation modes makes possible the characterization of the data by various points of view depending on the user's profile, his best-practices, his level of expertise, and so on. We propose a new multidimensional model that integrates functional dimension versions allowing the descriptors of the multidimensional data to be computed by different functions. With this approach, the user is able to obtain and choose multiple points of view on the data he analyses. This model is used to develop an OLAP application for navigation into a hypercube integrating various functional dimension versions for the calculus of descriptors in a medical use case.