Human immunodeficiency virus type 1 (HIV-1) continues to be a major cause of disease and premature death. As with all viruses, HIV-1 exploits a host cell to replicate. Improving our understanding of the molecular interactions between virus and human host proteins is crucial for a mechanistic understanding of virus biology, infection and host antiviral activities. This knowledge will potentially permit the identification of host molecules for targeting by drugs with antiviral properties. Here, we propose a data-driven approach for the analysis and prediction of the HIV-1 interacting proteins (VIPs) with a focus on the directionality of the interaction: host-dependency versus antiviral factors. Using support vector machine learning models and features encompassing genetic, proteomic and network properties, our results reveal some significant differences between the VIPs and non-HIV-1 interacting human proteins (non-VIPs). As assessed by comparison with the HIV-1 infection pathway data in the Reactome database (sensitivity > 90%, threshold = 0.5), we demonstrate these models have good generalization properties. We find that the 'direction' of the HIV-1-host molecular interactions is also predictable due to different characteristics of 'forward'/pro-viral versus 'backward'/pro-host proteins. Additionally, we infer the previously unknown direction of the interactions between HIV-1 and 1351 human host proteins. A web server for performing predictions is available at http://hivpre.cvr.gla.ac.uk/.

We consider a Synthetic Aperture Imaging Radiometer approach for feasibly enabling an aperture of unprecedented size, while yet achieving extreme sparsity in terms of both structure and number of antenna elements. A small array rotating on a tether around a rigid-boom-mounted 1-D antenna array engenders in a quarter revolution a continuum of projected baselines, which effectively constitute a 2-D aperture suitable for imaging applications, at previously infeasible spatial resolution. As the rotating tether-end array, which can be arbitrarily large, is a participant antenna element in every baseline of the aperture, a surprising level of sensitivity is achievable despite the sparsity in terms of both antennas and structure. Potential applications include RF earth imaging of soil moisture and ocean salinity from space for weather and climate modelling, at a higher spatial resolution than is currently feasible with any existing concept.

Motivation: The increasing rate of submission of genetic sequences into public databases is providing a growing resource for classifying the organisms that these sequences represent. To aid viral classification, we have developed ViCTree, which automatically integrates the relevant sets of sequences in NCBI GenBank and transforms them into an interactive maximum likelihood phylogenetic tree that can be updated automatically. ViCTree incorporates ViCTreeView, which is a JavaScript-based visualization tool that enables the tree to be explored interactively in the context of pairwise distance data. Results: To demonstrate utility, ViCTree was applied to subfamily Densovirinae of family Parvoviridae. This led to the identification of six new species of insect virus. Availability and implementation: ViCTree is open-source and can be run on any Linux- or Unix-based computer or cluster. A tutorial, the documentation and the source code are available under a GPL3 license, and can be accessed at http://bioinformatics.cvr.ac.uk/victree_web/. Supplementary information: Supplementary data are available at Bioinformatics online.

BACKGROUND: Virus genome sequences, generated in ever-higher volumes, can provide new scientific insights and inform our responses to epidemics and outbreaks. To facilitate interpretation, such data must be organised and processed within scalable computing resources that encapsulate virology expertise. GLUE (Genes Linked by Underlying Evolution) is a data-centric bioinformatics environment for building such resources. The GLUE core data schema organises sequence data along evolutionary lines, capturing not only nucleotide data but associated items such as alignments, genotype definitions, genome annotations and motifs. Its flexible design emphasises applicability to different viruses and to diverse needs within research, clinical or public health contexts. RESULTS: HCV-GLUE is a case study GLUE resource for hepatitis C virus (HCV). It includes an interactive public web application providing sequence analysis in the form of a maximum-likelihood-based genotyping method, antiviral resistance detection and graphical sequence visualisation. HCV sequence data from GenBank is categorised and stored in a large-scale sequence alignment which is accessible via web-based queries. Whereas this web resource provides a range of basic functionality, the underlying GLUE project can also be downloaded and extended by bioinformaticians addressing more advanced questions. CONCLUSION: GLUE can be used to rapidly develop virus sequence data resources with public health, research and clinical applications. This streamlined approach, with its focus on reuse, will help realise the full value of virus sequence data.

BACKGROUND: Relationships between species, genes and genomes have been printed as trees for over a century. Whilst this may have been the best format for exchanging and sharing phylogenetic hypotheses during the 20th century, the worldwide web now provides faster and automated ways of transferring and sharing phylogenetic knowledge. However, novel software is needed to defrost these published phylogenies for the 21st century. RESULTS: TreeRipper is a simple website for the fully-automated recognition of multifurcating phylogenetic trees (http://linnaeus.zoology.gla.ac.uk/~jhughes/treeripper/). The program accepts a range of input image formats (PNG, JPG/JPEG or GIF). The underlying command line c++ program follows a number of cleaning steps to detect lines, remove node labels, patch-up broken lines and corners and detect line edges. The edge contour is then determined to detect the branch length, tip label positions and the topology of the tree. Optical Character Recognition (OCR) is used to convert the tip labels into text with the freely available tesseract-ocr software. 32% of images meeting the prerequisites for TreeRipper were successfully recognised, the largest tree had 115 leaves. CONCLUSIONS: Despite the diversity of ways phylogenies have been illustrated making the design of a fully automated tree recognition software difficult, TreeRipper is a step towards automating the digitization of past phylogenies. We also provide a dataset of 100 tree images and associated tree files for training and/or benchmarking future software. TreeRipper is an open source project licensed under the GNU General Public Licence v3.

Several industrial and academic research groups are working to simplify the control of appliances and services by creating a truly universal remote control. Unlike the preprogrammed remote controls available today, these new controllers download a specification from the appliance or service and use it to automatically generate a remote control interface. This promises to be a useful approach because the specification can be made detailed enough to generate both speech and graphical interfaces. Unfortunately, generating good user interfaces can be difficult. Based on user studies and prototype implementations, this paper presents a set of requirements that we have found are needed for automatic interface generation systems to create high-quality user interfaces.

The personal universal controller (PUC) is an approach for improving the interfaces to complex appliances by introducing an intermediary graphical or speech interface. A PUC engages in two-way communication with everyday appliances, first downloading a specification of the appliance's functions, and then automatically creating an interface for controlling that appliance. The specification of each appliance includes a high-level description of every function, a hierarchical grouping of those functions, and dependency information, which relates the availability of each function to the appliance's state. Dependency information makes it easier for designers to create specifications and helps the automatic interface generators produce a higher quality result. We describe the architecture that supports the PUC, and the interface generators that use our specification language to build high-quality graphical and speech interfaces.