PATRIC

PATRIC[1] (Pathosystems Resource Integration Center) is the Bacterial Bioinformatics Resource Center, an information system designed to support the biomedical research community’s work on bacterial infectious diseases via integration of vital pathogen information with rich data and analysis tools. PATRIC sharpens and hones the scope of available bacterial phylogenomic data from numerous sources specifically for the bacterial research community, in order to save biologists time and effort when conducting comparative analyses. The freely available PATRIC platform provides an interface for biologists to discover data and information and conduct comprehensive comparative genomics and other analyses in a one-stop shop. PATRIC, a project of Virginia Tech’s Cyberinfrastructure Division, is funded by the National Institutes of Allergy and Infectious Diseases (NIAID), a component of the National Institutes of Health (NIH).

For other uses, see Patric (disambiguation).

What PATRIC Offers
  • Consistent annotations across all sequenced bacterial species from GenBank.
  • Annotate your bacterial genome for free in less than 24 hours using the same RAST annotation service that is used at PATRIC.
  • Data and Information Searches
  • Perform a PATRIC global search or conduct advanced searches based on Taxonomy, Gene Name, Locus Tag, Protein Function/Families, Pathways, EC Numbers, GO Terms, Host-Pathogen Interactions, and more.
  • Perform a BLAST search against plasmid-specific BLAST databases containing genomic sequences or proteins in PATRIC.
  • Perform enhanced literature search and text mining techniques to identify genes, proteins, diseases, drugs, organisms, and other entities of interest.
  • Personal workspace that allows users to permanently save sequences of interest collected from PATRIC. From here manage and analyze saved data within your customized groups.
  • Numerous comparative analysis and interactive visualizations to help investigators discover emergent properties in complex systems. Exportable sequences and other specifics about the data used to create your custom visualizations.
  • Rich, interactive visualizations that support analyses such as, a bird’s-eye view of the conservation (or lack thereof) of particular genes of interest, discerning how many proteins have the same function within a single genome, and identifying proteins with multiple homologs or paralogs across a set of genomes.
  • Freely available data and analysis results, presented in tabular, graphic, and downloadable formats.

PATRIC Data Release Policy

Bacterial Organisms Covered in the PATRIC Database

Tools and Comparative Analyses on PATRIC
  • Protein Family Sorter: Compares protein families across closely related or diverse groups of genomes, visualizes them using interactive heatmaps, and generates multiple sequence alignments and phylogenetic trees for an individual families. The heatmap view is an interactive visualization tool that provides an overview of the distribution of proteins across a selected set of genomes.
  • Comparative pathways: Compares consistently annotated metabolic pathways across closely related or diverse groups of genomes and visualizes them using interactive KEGG maps and heatmaps. The heatmap view is an interactive visualization tool that provides an overview of the distribution of genomes across the set of EC numbers within a selected pathway.
  • Metadata: Supports searches for and locates genomes of interest based on various combinations of 61 different metadata fields. For instance, all genomes that have been isolated from humans, genomes related by phylogeny, or genomes related by lifestyle.
  • ID Mapping: Quickly maps PATRIC identifiers to those from other prominent external databases, such as GenBank, RefSeq, UniProt, etc. Alternatively, researchers can start with a list of external database identifiers and map them to the corresponding PATRIC features.
  • Genome Browser and Compare Region Viewer: Visualizes and compares genome annotations from multiple sources and allows users to view gene neighborhoods.
  • 3D Structures and Experiment Data: Provides consolidated and uniform data access via summaries of all relevant post-genomic datasets available in various public repositories, such as GEO, ArrayExpress, the (former) Proteomics Resource Centers, PRIDE, NCBI structure, IntAct, and BIND.
  • Disease View: Presents infectious disease, virulence, and outbreak data associated with various taxon. Includes an interactive graph presenting relationships between pathogens, genes, and diseases and a disease map, which geolocates reports of associated diseases around the globe in real-time.
  • BLAST[2]
  • RAST[3] prokaryotic genome annotation service
  • KLEIO[4] advanced MedLine search tool

About Cyberinfrastructure Division and VBI

The CyberInfrastructure Division at VBI develops methods, infrastructure, and resources to help enable scientific discoveries in infectious disease research and other research fields. The group applies the principles of cyberinfrastructure to integrate data, computational infrastructure, and people. CyberInfrastructure Division has developed many public resources for curated, diverse molecular and literature data from various infectious disease systems, and implemented the processes, systems, and databases required to support them. It also conducts research by applying its methods and data to make new discoveries of its own.

The Virginia Bioinformatics Institute (VBI) at Virginia Tech has a research platform centered on understanding the "disease triangle" of host-pathogen-environment interactions in plants, humans and other animals. By successfully channeling innovation into transdisciplinary approaches that combine information technology and biology, researchers at VBI are addressing some of today’s key challenges in the biomedical, environmental, and plant sciences.

See also

References
  1. Gillespie JJ, Wattam AR, Cammer SA, et al. (November 2011). "PATRIC: the comprehensive bacterial bioinformatics resource with a focus on human pathogenic species". Infection and Immunity. 79 (11): 4286–98. doi:10.1128/IAI.00207-11. PMC 3257917. PMID 21896772.
  2. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990). "Basic local alignment search tool" (PDF). J Mol Biol. 215 (3): 403–410. doi:10.1016/S0022-2836(05)80360-2. PMID 2231712. Archived from the original (PDF) on 2010-10-13.
  3. Aziz, RK; Bartels, D; Best, AA; DeJongh, M; Disz, T; Edwards, RA; Formsma, K; Gerdes, S; Glass, EM; Kubal, Michael; Meyer, Folker; Olsen, Gary J; Olson, Robert; Osterman, Andrei L; Overbeek, Ross A; McNeil, Leslie K; Paarmann, Daniel; Paczian, Tobias; Parrello, Bruce; Pusch, Gordon D; Reich, Claudia; Stevens, Rick; Vassieva, Olga; Vonstein, Veronika; Wilke, Andreas; Zagnitko, Olga (2008). "The RAST Server: Rapid Annotations using Subsystems Technology". BMC Genomics. 9: 75. doi:10.1186/1471-2164-9-75. PMC 2265698. PMID 18261238.
  4. C. Nobata; P. Cotter; N. Okazaki; B. Rea; Y. Sasaki; Y. Tsuruoka; J. Tsujii; S. Ananiadou (2008). "Kleio: a knowledge-enriched information retrieval system for biology" (PDF). Proc. of the 31st Annual International ACM SIGIR Conference: 787–788. Archived from the original (PDF) on 2011-07-17. Retrieved 2010-09-13.
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