What is PATRIC?

PATRIC 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 is a NIH/NIAID-funded project of the University of Chicago with subcontract to the Biocomplexity Institute of Virginia Tech.

What PATRIC Offers

  • Comprehensive Collection of Consistently Annotated Genomes across all sequenced bacterial species from GenBank and other sources via RASTtk, a highly cited automated prokaryotic annotation system.
  • Rich Genome Metadata parsed from a variety of sources in over 60 fields such as, isolation source, geographic location, year of isolation, host and/or environment, antimicrobial resistance (AMR) phenotype, among others.
  • Data Integration Across Sources, Data Types, Molecular Entities, and Organisms. Data types include genomics, transcriptomics, protein-protein interactions, 3D protein structures, sequence typing data, and metadata, and are summarized and organized at various taxon, genome, and gene levels.
  • Suite of High-Throughput Computational Analysis Services including Comprehensive Genome Analysis, Genome Assembly, Genome Annotation, Similar Genome Finder, Proteome Comparison, Protein Family Sorter, Pathway Comparison, Metabolic Model Reconstruction, Phylogenetic Tree Construction, Variation/SNP Analysis, RNA-Seq Analysis, Differential Expression Analysis, TN-Seq Analysis, Metagenomic Binning, and others.
  • Command-Line Interface for programmatic access to PATRIC data and analysis services.
  • Personal Private Workspace to permanently save groups of genomic data, gene associations, and uploaded private data. Both private and public data can be analyzed together using PATRIC analysis tools. Data can be shared with other registered PATRIC users.

About the Computation Institute

The Computation Institute (CI), a joint initiative between the University of Chicago and Argonne National Laboratory, advances science through innovative computational approaches. The CI is both an intellectual nexus and resource center for those building and applying computational platforms for science. As an intellectual nexus, it brings together researchers from different disciplines with common interests in advancing the state-of-the-art in computing and its applications. As a resource center, it provides expert assistance to scholars whose work requires the most advanced computational methods. The CI’s research has increasingly broad impact as advanced computational and informatics approaches are becoming critical to future research breakthroughs in almost every scientific discipline. The CI is home to over 100 researchers and staff, including more than 70 fellows from University of Chicago faculty and Argonne scientists that have active collaborations with over 50 prestigious academic and research institutions across the globe. Current research is targeted at solving complex system-level problems in bioinformatics, biomedicine, neuroscience, genomics, metagenomics, energy and climate, astronomy and astrophysics, computational economics, and molecular engineering.

About the Biocomplexity Institute of Virginia Tech

The Biocomplexity Institute of Virginia Tech (BI) is a world-class research institute dedicated to the study of information biology. Housed in state-of-the-art facilities on Virginia Tech’s Blacksburg campus and National Capital Region Research Center, the institute broadly integrates disciplines – from molecular science to policy analysis – to address pressing challenges to human health, habitat, and well-being. BI uses an information biology approach to predict, explain, and visualize the behavior of massively interacting systems. Where conceptual and technological constraints once forced researchers to examine living systems one small slice at a time, we can now find complex connections ranging from the basic building blocks of life to public policy. BI is at the forefront of this scientific evolution, applying a deeply contextual approach to answer some of the most pressing challenges to human health, habitat, and well-being. BI's research is interdisciplinary to its core, integrating methods from the life, cognitive, and social sciences, as well environmental studies and infrastructural development. The institute guides emergency response to epidemics, makes urban infrastructure more sustainable, and accelerates the discovery of treatments for chronic diseases.