PATRIC Publications

Includes doi, PMID, and PMCID links.

Argo: an integrative, interactive, text mining-based workbench supporting curation

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A Rickettsia genome overrun by mobile genetic elements provides insight into the acquisition of genes characteristic of an obligate intracellular lifestyle.

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PATRIC: The Comprehensive Bacterial Bioinformatics Resource with a Focus on Human Pathogenic Species

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Driscoll, Mao and Gabbard Publish Work on PATRIC’s Host-Pathogen Data and Visualizations

Infectious disease research is generating an increasing amount of disparate data on pathogenic systems. There is a growing need for resources that effectively integrate, analyze, deliver and visualize these data, both to improve our understanding of infectious diseases and to facilitate the development of strategies for disease control and prevention.

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Drs. Sobral and Wattam Author a Chapter in “Brucella: Molecular Microbiology and Genetics”.

Chapter Title: Comparative genomics and phylogenomics of the Brucella.

PATRIC Team Publishes Paper on Text Mining for Type IV Secretion Systems.

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Dr. Dyer and Collaborators publish on human-bacterial pathogen protein interaction networks.

Bacillus anthracis, Francisella tularensis, and Yersinia pestis are bacterial pathogens that can cause anthrax, lethal acute pneumonic disease, and bubonic plague, respectively, and are listed as NIAID Category A priority pathogens for possible use as biological weapons. However, the interactions between human proteins and proteins in these bacteria remain poorly characterized leading to an incomplete understanding of their pathogenesis and mechanisms of immune evasion. In this study, we used a high-throughput yeast two-hybrid assay to identify physical interactions between human proteins and proteins from each of these three pathogens.

Dr. Bruno Sobral and Collaborators Publish Paper on Infectious Disease Text Mining

Event extraction approaches based on expressive structured representations of extracted information have been a significant focus of research in recent biomedical natural language processing studies. However, event extraction efforts have so far been limited to publication abstracts, with most studies further considering only the specific transcription factor-related subdomain of molecular biology of the GENIA corpus. To establish the broader relevance of the event extraction approach and proposed methods, it is necessary to expand on these constraints. In this study, we propose an adaptation of the event extraction approach to a subdomain related to infectious diseases and present analysis and initial experiments on the feasibility of event extraction from domain full text publications.

Drs. Gillespie and Sobral Reveal Diverse Rickettsiales Type IV Secretion System

With an obligate intracellular lifestyle, Alphaproteobacteria of the order Rickettsiales have inextricably coevolved with their various eukaryotic hosts, resulting in small, reductive genomes and strict dependency on host resources. Unsurprisingly, large portions of Rickettsiales genomes encode proteins involved in transport and secretion. One particular transporter that has garnered recent attention from researchers is the type IV secretion system (T4SS).