Influenza research database: an integrated bioinformatics resource for influenza research and surveillance.

BackgroundThe recent emergence of the 2009 pandemic influenza A/H1N1 virus has highlighted the value of free and open access to influenza virus genome sequence data integrated with information about other important virus characteristics.DesignThe Influenza Research Database (IRD, http://www.fludb.org) is a free, open, publicly-accessible resource funded by the U.S. National Institute of Allergy and Infectious Diseases through the Bioinformatics Resource Centers program. IRD provides a comprehensive, integrated database and analysis resource for influenza sequence, surveillance, and research data, including user-friendly interfaces for data retrieval, visualization and comparative genomics analysis, together with personal log in-protected 'workbench' spaces for saving data sets and analysis results. IRD integrates genomic, proteomic, immune epitope, and surveillance data from a variety of sources, including public databases, computational algorithms, external research groups, and the scientific literature.ResultsTo demonstrate the utility of the data and analysis tools available in IRD, two scientific use cases are presented. A comparison of hemagglutinin sequence conservation and epitope coverage information revealed highly conserved protein regions that can be recognized by the human adaptive immune system as possible targets for inducing cross-protective immunity. Phylogenetic and geospatial analysis of sequences from wild bird surveillance samples revealed a possible evolutionary connection between influenza virus from Delaware Bay shorebirds and Alberta ducks.ConclusionsThe IRD provides a wealth of integrated data and information about influenza virus to support research of the genetic determinants dictating virus pathogenicity, host range restriction and transmission, and to facilitate development of vaccines, diagnostics, and therapeutics

VectorBase: improvements to a bioinformatics resource for invertebrate vector genomics.

VectorBase (http://www.vectorbase.org) is a NIAID-supported bioinformatics resource for invertebrate vectors of human pathogens. It hosts data for nine genomes: mosquitoes (three Anopheles gambiae genomes, Aedes aegypti and Culex quinquefasciatus), tick (Ixodes scapularis), body louse (Pediculus humanus), kissing bug (Rhodnius prolixus) and tsetse fly (Glossina morsitans). Hosted data range from genomic features and expression data to population genetics and ontologies. We describe improvements and integration of new data that expand our taxonomic coverage. Releases are bi-monthly and include the delivery of preliminary data for emerging genomes. Frequent updates of the genome browser provide VectorBase users with increasing options for visualizing their own high-throughput data. One major development is a new population biology resource for storing genomic variations, insecticide resistance data and their associated metadata. It takes advantage of improved ontologies and controlled vocabularies. Combined, these new features ensure timely release of multiple types of data in the public domain while helping overcome the bottlenecks of bioinformatics and annotation by engaging with our user community

A contagious living fluid: objectification and assemblage in the history of virology

This article deals with the birth of `the virus' as an object of technoscientific analysis. The aim is to discuss the process of objectification of pathogen virulence in virological and medical discourses. Through a short excursion into the history of modern virology, it will be argued that far from being a matter of fact, pathogen virulence had to be `produced', for example in petri-dishes, test-kits and hyper-real signification-practices. The now commonly accepted objective status of `the virus' has been an accomplishment of a complex ensemble of actors. Indeed, this illustrates why objectification rather than objectivity has become the main focus of science and technology studies. The objectification of `the' virus was by no means a smooth process. It involved more than five decades of highly speculative and fragmented research projects before it became actualized as a separate discipline under the heading of virology. The specific objectification of viruses took place through an inter-disciplinary de-differentiation of research questions, methodologies, techniques and technologies. The main argument of this article is that viruses only became intelligible after the establishment of a virology-assemblage. Its inauguration in the early 1950s was radical and sudden because only then could the various substrands of virological technoscience affect each other through deliberate enrolment, and engender a universal intelligibility

Protein-protein interactions: network analysis and applications in drug discovery

Physical interactions among proteins constitute the backbone of cellular function, making them an attractive source of therapeutic targets. Although the challenges associated with targeting protein-protein interactions (PPIs) -in particular with small molecules are considerable, a growing number of functional PPI modulators is being reported and clinically evaluated. An essential starting point for PPI inhibitor screening or design projects is the generation of a detailed map of the human interactome and the interactions between human and pathogen proteins. Different routes to produce these biological networks are being combined, including literature curation and computational methods. Experimental approaches to map PPIs mainly rely on the yeast two-hybrid (Y2H) technology, which have recently shown to produce reliable protein networks. However, other genetic and biochemical methods will be essential to increase both coverage and resolution of current protein networks in order to increase their utility towards the identification of novel disease-related proteins and PPIs, and their potential use as therapeutic targets

PHIDIAS: a pathogen-host interaction data integration and analysis system

PHIDIAS is a web-based database system serving as a centralized source to search, compare and analyse integrated genome sequences, conserved domains and transcriptional data related to pathogen-host interactions

PATRIC, the bacterial bioinformatics database and analysis resource

The Pathosystems Resource Integration Center (PATRIC) is the all-bacterial Bioinformatics Resource Center (BRC) (http://www.patricbrc.org). A joint effort by two of the original National Institute of Allergy and Infectious Diseases-funded BRCs, PATRIC provides researchers with an online resource that stores and integrates a variety of data types [e.g. genomics, transcriptomics, protein-protein interactions (PPIs), three-dimensional protein structures and sequence typing data] and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes in PATRIC, currently more than 10 000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. All the data and integrated analysis and visualization tools are freely available. This manuscript describes updates to the PATRIC since its initial report in the 2007 NAR Database Issu

Infectious Disease Ontology

Technological developments have resulted in tremendous increases in the volume and diversity of the data and information that must be processed in the course of biomedical and clinical research and practice. Researchers are at the same time under ever greater pressure to share data and to take steps to ensure that data resources are interoperable. The use of ontologies to annotate data has proven successful in supporting these goals and in providing new possibilities for the automated processing of data and information. In this chapter, we describe different types of vocabulary resources and emphasize those features of formal ontologies that make them most useful for computational applications. We describe current uses of ontologies and discuss future goals for ontology-based computing, focusing on its use in the field of infectious diseases. We review the largest and most widely used vocabulary resources relevant to the study of infectious diseases and conclude with a description of the Infectious Disease Ontology (IDO) suite of interoperable ontology modules that together cover the entire infectious disease domain

Novel approaches, including systems biology, to HIV vaccine research and development: Report from a Global HIV Vaccine Enterprise Working Group

The Global HIV Vaccine Enterprise convened a two-day workshop on August 10-11 2009, at the Fred Hutchison Cancer Research Center offices in Seattle, WA, to discuss the application of novel approaches,including systems biology, to HIV vaccine research and development. The goals of this Working Group were to identify key scientific issues and opportunities that have emerged since the Enterprise Scientific Strategic Plan1 was published in 2005, and to make recommendations to Enterprise stakeholders

Novel approaches, including systems biology, to HIV vaccine research and development: Report from a Global HIV Vaccine Enterprise Working Group

The Global HIV Vaccine Enterprise convened a two-day workshop on August 10-11 2009, at the Fred Hutchison Cancer Research Center offices in Seattle, WA, to discuss the application of novel approaches,including systems biology, to HIV vaccine research and development. The goals of this Working Group were to identify key scientific issues and opportunities that have emerged since the Enterprise Scientific Strategic Plan1 was published in 2005, and to make recommendations to Enterprise stakeholders

Mapping road network communities for guiding disease surveillance and control strategies

Human mobility is increasing in its volume, speed and reach, leading to the movement and introduction of pathogens through infected travelers. An understanding of how areas are connected, the strength of these connections and how this translates into disease spread is valuable for planning surveillance and designing control and elimination strategies. While analyses have been undertaken to identify and map connectivity in global air, shipping and migration networks, such analyses have yet to be undertaken on the road networks that carry the vast majority of travellers in low and middle income settings. Here we present methods for identifying road connectivity communities, as well as mapping bridge areas between communities and key linkage routes. We apply these to Africa, and show how many highly-connected communities straddle national borders and when integrating malaria prevalence and population data as an example, the communities change, highlighting regions most strongly connected to areas of high burden. The approaches and results presented provide a flexible tool for supporting the design of disease surveillance and control strategies through mapping areas of high connectivity that form coherent units of intervention and key link routes between communities for targeting surveillance.Comment: 11 pages, 5 figures, research pape