BACKGROUND: The availability of 12 fully sequenced Drosophila species genomes provides an excellent opportunity to explore the evolutionary mechanism, structure and function of gene families in Drosophila. Currently, several important resources, such as FlyBase, FlyMine and DroSpeGe, have been devoted to integrating genetic, genomic, and functional data of Drosophila into a well-organized form. However, all of these resources are gene-centric and lack the information of the gene families in Drosophila. DESCRIPTION: FlyPhy is a comprehensive phylogenomic analysis platform devoted to analyzing the genes and gene families in Drosophila. Genes were classified into families using a graph-based Markov Clustering algorithm and extensively annotated by a number of bioinformatic tools, such as basic sequence features, functional category, gene ontology terms, domain organization and sequence homolog to other databases. FlyPhy provides a simple and user-friendly web interface to allow users to browse and retrieve the information at multiple levels. An outstanding feature of the FlyPhy is that all the retrieved results can be added to a workset for further data manipulation. For the data stored in the workset, multiple sequence alignment, phylogenetic tree construction and visualization can be easily performed to investigate the sequence variation of each given family and to explore its evolutionary mechanism. CONCLUSION: With the above functionalities, FlyPhy will be a useful resource and convenient platform for the Drosophila research community. The FlyPhy is available at http://bioinformatics.zj.cn/fly/ .

UNLABELLED: Malaria, one of the world's most common diseases, is caused by the intracellular protozoan parasite known as Plasmodium. Recently, with the arrival of several malaria parasite genomes, we established an integrated system named PlasmoGF for comparative genomics and phylogenetic analysis of Plasmodium gene families. Gene families were clustered using the Markov Cluster algorithm implemented in TribeMCL program and could be searched using keywords, gene-family information, domain composition, Gene Ontology and BLAST. Moreover, a number of useful bioinformatics tools were implemented to facilitate the analysis of these putative Plasmodium gene families, including gene retrieval, annotation, sequence alignment, phylogeny construction and visualization. In the current version, PlasmoGF contained 8980 sets of gene families derived from six malaria parasite genomes: Plasmodium. falciparum, P. berghei, P. knowlesi, P. chabaudi, P. vivax and P. yoelii. The availability of such a highly integrated system would be of great interest for the community of researchers working on malaria parasite phylogenomics. AVAILABILITY: PlasmoGF is freely available at http://bioinformatics.zj.cn/pgf/