Data sharing, integration and annotation are essential to ensure the reproducibility of the analysis and interpretation of the experimental findings. Often these activities are perceived as a role that bioinformaticians and computer scientists have to take with no or little input from the experimental biologist. On the contrary, biological researchers, being the producers and often the end users of such data, have a big role in enabling biological data integration. The quality and usefulness of data integration depend on the existence and adoption of standards, shared formats, and mechanisms that are suitable for biological researchers to submit and annotate the data, so it can be easily searchable, conveniently linked and consequently used for further biological analysis and discovery. Here, we provide background on what is data integration from a computational science point of view, how it has been applied to biological research, which key aspects contributed to its success and future directions.

The mountains of data thrusting from the new landscape of modern high-throughput biology are irrevocably changing biomedical research and creating a near-insatiable demand for training in data management and manipulation and data mining and analysis. Among life scientists, from clinicians to environmental researchers, a common theme is the need not just to use, and gain familiarity with, bioinformatics tools and resources but also to understand their underlying fundamental theoretical and practical concepts. Providing bioinformatics training to empower life scientists to handle and analyse their data efficiently, and progress their research, is a challenge across the globe. Delivering good training goes beyond traditional lectures and resource-centric demos, using interactivity, problem-solving exercises and cooperative learning to substantially enhance training quality and learning outcomes. In this context, this article discusses various pragmatic criteria for identifying training needs and learning objectives, for selecting suitable trainees and trainers, for developing and maintaining training skills and evaluating training quality. Adherence to these criteria may help not only to guide course organizers and trainers on the path towards bioinformatics training excellence but, importantly, also to improve the training experience for life scientists.

Many proteins are highly modular, being assembled from globular domains and segments of natively disordered polypeptides. Linear motifs, short sequence modules functioning independently of protein tertiary structure, are most abundant in natively disordered polypeptides but are also found in accessible parts of globular domains, such as exposed loops. The prediction of novel occurrences of known linear motifs attempts the difficult task of distinguishing functional matches from stochastically occurring non-functional matches. Although functionality can only be confirmed experimentally, confidence in a putative motif is increased if a motif exhibits attributes associated with functional instances such as occurrence in the correct taxonomic range, cellular compartment, conservation in homologues and accessibility to interacting partners. Several tools now use these attributes to classify putative motifs based on confidence of functionality.

Phospho3D is a database of three-dimensional (3D) structures of phosphorylation sites (P-sites) derived from the Phospho.ELM database, which also collects information on the residues surrounding the P-site in space (3D zones ). The database also provides the results of a large-scale structural comparison of the 3D zones versus a representative dataset of structures, thus associating to each P-site a number of structurally similar sites. The new version of Phospho3D presents an 11-fold increase in the number of 3D sites and incorporates several additional features, including new structural descriptors, the possibility of selecting non-redundant sets of 3D structures and the availability for download of non-redundant sets of structurally annotated P-sites. Moreover, it features P3Dscan, a new functionality that allows the user to submit a protein structure and scan it against the 3D zones collected in the Phospho3D database. Phospho3D version 2.0 is available at: http://www.phospho3d.org/ .

Background: Monitoring resistance phenotypes forPlasmodium falciparum, usingin vitrogrowth assays, and relating findings to parasite genotype has proved particularly challenging for the study of resistance to artemisinins.Methods: Plasmodium falciparumisolates cultured from 28 returning travellers diagnosed with malaria were assessed for sensitivity to artemisinin, artemether, dihydroartemisinin and artesunate and findings related to mutations inpfatp6andpfmdr1.Results: Resistance to artemetherin vitrowas significantly associated with apfatp6haplotype encoding two amino acid substitutions (pfatp6A623E and S769N; (mean IC₅₀(95% CI) values of 8.2 (5.7 – 10.7) for A623/S769versus623E/769 N 13.5 (9.8 – 17.3) nM with a mean increase of 65%; p = 0.012). Increased copy number ofpfmdr1was not itself associated with increased IC₅₀values for artemether, but when interactions between thepfatp6haplotype and increased copy number ofpfmdr1were examined together, a highly significant association was noted with IC₅₀values for artemether (mean IC₅₀(95% CI) values of 8.7 (5.9 – 11.6)versus16.3 (10.7 – 21.8) nM with a mean increase of 87%; p = 0.0068). Previously described SNPs inpfmdr1are also associated with differences in sensitivity to some artemisinins.Conclusions: These findings were further explored in molecular modelling experiments that suggest mutations inpfatp6are unlikely to affect differential binding of artemisinins at their proposed site, whereas there may be differences in such binding associated with mutations inpfmdr1. Implications for a hypothesis that artemisinin resistance may be exacerbated by interactions between PfATP6 and PfMDR1 and for epidemiological studies to monitor emerging resistance are discussed.

Background: Genes involved in post-mating processes of multiple mating organisms are known to evolve rapidly due to coevolution driven by sexual conflict among male-female interacting proteins. In the malaria mosquitoAnopheles gambiae- a monandrous species in which sexual conflict is expected to be absent or minimal - recent data strongly suggest that proteolytic enzymes specifically expressed in the female lower reproductive tissues are involved in the processing of male products transferred to females during mating. In order to better understand the role of selective forces underlying the evolution of proteins involved in post-mating responses, we analysed a cluster of genes encoding for three serine proteases that are down-regulated after mating, two of which specifically expressed in the atrium and one in the spermatheca ofA. gambiaefemales.Results: The analysis of polymorphisms and divergence of these female-expressed proteases in closely related species of theA. gambiaecomplex revealed a high level of replacement polymorphisms consistent with relaxed evolutionary constraints of duplicated genes, allowing to rapidly fix novel replacements to perform new or more specific functions. Adaptive evolution was detected in several codons of the 3 genes and hints of episodic selection were also found. In addition, the structural modelling of these proteases highlighted some important differences in their substrate specificity, and provided evidence that a number of sites evolving under selective pressures lie relatively close to the catalytic triad and/or on the edge of the specificity pocket, known to be involved in substrate recognition or binding. The observed patterns suggest that these proteases may interact with factors transferred by males during mating (e.g. substrates, inhibitors or pathogens) and that they may have differently evolved in independentA. gambiaelineages.Conclusions: Our results - also examined in light of constraints in the application of selection-inference methods to the closely related species of theA. gambiaecomplex - reveal an unexpectedly intricate evolutionary scenario. Further experimental analyses are needed to investigate the biological functions of these genes in order to better interpret their molecular evolution and to assess whether they represent possible targets for limiting the fertility ofAnophelesmosquitoes in malaria vector control strategies.