potential targets identified via high-throughput methods. In addition to data, the PRCs have provided biological reagents such as clones, antibodies and engineered bacterial strains, other deliverables include standard operating procedures (SOPs) and new technologies such as instrumental methods and software tools and finally publications related to all of these activities. Consequently, there were a number of unique challenges facing the Resource Center: (i) how to coordinate with the seven PRCs with various pathogens, technologies, processes, and data types; (ii) how to provide seamless integration of three institutions that make up the Resource Center; and (iii) how to provide timely and effective dissemination of newly discovered information to the user community. In particular, due to the breadth of the program, the potential user community is quite broad, from technology or informatics experts who may want to reanalyze the data or develop better algorithms, to a wide group of biomedical scientists who are interested in mining the data for their own studies or just finding new information on a protein or gene of interest quickly and easily. Accordingly, we developed a set of functional requirements early in the Biodefense Resource Center development: (i) to implement a center-specific submission protocol and data release plan for timely dissemination, (ii) to promote data interoperability, adopting common standards (such as HUPO Proteomic Standards Initiative [2,3,4]), defining a core set of metadata with mapping to controlled vocabularies and ontologies, recommending preferred IDs for gene/ protein mapping, and (iii) to provide value-added annotation to capture key findings and integration of the data with related resources for functional interpretation of the data. Available online at http://proteomicsresource.org, the architecture, initial content and general features of the Biodefense Proteomics Resource were briefly described elsewhere [5]. A breakdown of the Resources content by organism, PRC and other criteria can be seen at: http://www. proteomicsresource.org/Resources/Catalog.aspx. Tutorials and help are provided on the website: http://www.proteomicsresource. org/Resources/Tutorials.aspx , http://proteininformationresource. org/pirwww/support/help.shtml#30 The objective of this study is to provide a systems approach to the study of pathogen-host interactions, connecting the various types of experimental data on genomics, proteomics and host-pathogen interactions with information on pathways, regulatory networks, literature, functional annotation and experimental methods. Having most of this information accessible in one place can facilitate knowledge discovery and modeling of biological systems. Like many problems in data integration, it is easy to know the general outline of what we want, but often much harder to implement and navigate the information, especially if the original data crosses disciplinary, laboratory and institutional boundaries. Here we describe in detail a protein-centric approach for systems integration of such a large and heterogeneous set of data from the NIAID Biodefense Proteomics program, and present scientific case studies to illustrate its application to facilitate the basic understanding of pathogen-host interactions and for the identification of potential candidates for therapeutic or diagnostic targets. Several scientific use cases are presented that illustrate how one can search varied experimental data from different laboratories and even ones researching different infectious organism and their hosts to make potentially useful connections that could lead to new hypotheses and discoveries. Methods Biodefense Resource Center Infrastructure Based on the functional requirements of the Resource Center, we developed a bioinformatics infrastructure for integration of PRC deliverables (Figure 1). In our workflow, multiple data types from Pathogen-Host Omics Data PRCs are submitted to the center using a data submission protocol and standard exchange format, with the metadata using controlled vocabulary whenever possible. For functional interpretation of the data, we then map the gene and protein data based on identifier (ID) mapping or if necessary using peptide or sequence mapping to proteins in our data warehouse described below. All of the databases, along with information on the PRCs and organisms under study are listed in the proteomics catalog accessible from the web portal. Protein-Centric Data Integration The key design principal in the Resource Center is protein-centric data integration. Here the diverse experimental data are integrated and presented in a protein-centric manner where information is queried and presented via common proteins and connected to experimental data and the network of protein attributes, including information on the encoding genes, protein families, pathways, functions and more. In practice a protein-centric approach works well as proteins occupy a middle ground molecularly between gene and transcript information and higher levels of molecular and cellular structure and organization. Proteins are often the functional molecules in biological processes described by pathways, molecular interactions and other networks. Protein families, in turn, have proven to be invaluable in studying evolution and for inferring and transferring functional annotation across species. Master Protein Directory Underlying the protein-centric data integration is a data warehouse called the Master Protein Directory (MPD) where key information is extracted from the primary data and combined for rapid search, display and analysis capabilities. The MPD is built on the data and capabilities of iProClass [6] a warehouse of protein information, which in turn is built around UniProtKB [7] but supplemented with additional sequences from gene models in RefSeq [6] and Ensembl [7] and additional annotation and literature from other curated data resources such as Model Organism Databases [8,9,10,11,12,13] and GeneRIF [14]. The biodefense data are essentially additional data fields added to a subset of iProClass entries to create the MPD. Currently the MPD defines and supports information from the following types of data produced by the PRCs: Mass Spectrom- etry, Microarray, Clones, Protein Interaction, and Protein Structure. More data types or attributes may be added in the future if needed. Supplemental table S1 shows the common and unique fields used in the MPD for each data type. An advantage of the data warehouse design is that, if needed, additional fields can be extracted from the primary data and easily added as new attributes without greatly altering the existing database design or query mechanisms. The MPD data is stored in an Oracle database along with iProClass data. For data exchange, an XML file and schema for the current MPD are available for download at: ftp://141.161.76.88/pub/proteomics_ftp/rc/MD_data/ipro- class_mpd.dtd ftp://141.161.76.88/pub/proteomics_ftp/rc/MD_data/ipro- class_mpd.xml ftp://141.161.76.88/pub/proteomics_ftp/rc/MD_data/ipro- class_mpd.xsd The MPD including the website and FTP files is updated every 3 weeks in conjunction with iProClass or whenever new PRC data is released. Protein Mapping Process The various Proteomics Research Centers all used different sources and identifiers for the nucleotide and protein sequences in their analysis pipelines and occasionally would change sources depending on the experiment. This is a common problem encountered when PLoS ONE | www.plosone.org 2 September 2009 | Volume 4 | Issue 9 | e7162