Motivation: Our society has become data-rich to the extent that research in many areas has become impossible without computational approaches. Educational programmes seem to be lagging behind this development. At the same time, there is a growing need not only for strong data science skills, but foremost for the ability to both translate between tools and methods on the one hand, and application and problems on the other. Results: Here we present our experiences with shaping and running a masters' programme in bioinformatics and systems biology in Amsterdam. From this, we have developed a comprehensive philosophy on how translation in training may be achieved in a dynamic and multidisciplinary research area, which is described here. We furthermore describe two requirements that enable translation, which we have found to be crucial: sufficient depth and focus on multidisciplinary topic areas, coupled with a balanced breadth from adjacent disciplines. Finally, we present concrete suggestions on how this may be implemented in practice, which may be relevant for the effectiveness of life science and data science curricula in general, and of particular interest to those who are in the process of setting up such curricula. Supplementary information: Supplementary data are available at Bioinformatics online.

Teaching students with very diverse backgrounds can be extremely challenging. This article uses the Bioinformatics and Systems Biology MSc in Amsterdam as a case study to describe how the knowledge gap for students with heterogeneous backgrounds can be bridged. We show that a mix in backgrounds can be turned into an advantage by creating a stimulating learning environment for the students. In the MSc Programme, conversion classes help to bridge differences between students, by mending initial knowledge and skill gaps. Mixing students from different backgrounds in a group to solve a complex task creates an opportunity for the students to reflect on their own abilities. We explain how a truly interdisciplinary approach to teaching helps students of all backgrounds to achieve the MSc end terms. Moreover, transferable skills obtained by the students in such a mixed study environment are invaluable for their later careers.

MOTIVATION: Pangenome arrays contain DNA oligomers targeting several sequenced reference genomes from the same species. In microbiology, these can be employed to investigate the often high genetic variability within a species by comparative genome hybridization (CGH). The biological interpretation of pangenome CGH data depends on the ability to compare strains at a functional level, particularly by comparing the presence or absence of orthologous genes. Due to the high genetic variability, available genotype-calling algorithms can not be applied to pangenome CGH data. RESULTS: We have developed the algorithm PanCGH that incorporates orthology information about genes to predict the presence or absence of orthologous genes in a query organism using CGH arrays that target the genomes of sequenced representatives of a group of microorganisms. PanCGH was tested and applied in the analysis of genetic diversity among 39 Lactococcus lactis strains from three different subspecies (lactis.cremoris, hordniae) and isolated from two different niches (dairy and plant). Clustering of these strains using the presence/absence data of gene orthologs revealed a clear separation between different subspecies and reflected the niche of the strains.

SUMMARY: A Web-based visualization tool, the Microbial Genome Viewer, is presented that allows the user to combine complex genomic data in a highly interactive way. This Web tool enables the interactive generation of chromosome wheels and linear genome maps from genome annotation data stored in a MySQL database. The generated images are in scalable vector graphics (SVG) format, which is suitable for creating high-quality scalable images and dynamic Web representations. Gene-related data such as transcriptome and time-course microarray experiments can be superimposed on the maps for visual inspection. AVAILABILITY: The Microbial Genome Viewer 1.0 is freely available at http://www.cmbi.kun.nl/MGV