Genomics for Bioforensics

Abstract

The goal of the Genomics for Bioforensics project (FY06-FY08) has been to explore the application of genomics to the challenge of attribution for biological organisms: given a sample of an agent, can we use genomics to (help) determine whether the new sample is an endemic strain, a strain introduced from another place or time, or a novel (possibly engineered) strain? Specifically, given sequence data from a new sample, we have developed procedures to compare this "unknown" sequence to a reference database of sequences from previously collected samples and their associated metadata. To do this, we have created a reference database for a specific organism (influenza) and developed procedures to create a Microbial Forensics Workbench, which enables the user to compare the "unknown" strain with the strains in the Reference Database. The Workbench provides a novel automated method for clustering the "unknown" strain with the most similar strains in the Reference Database. This method for genotyping uses Complete Composition Vectors and Affinity Propagation Clustering (submitted for publication: Peterson et al., Bioinformatics). The Workbench also supports several visualization techniques, including display of a color-coded phylogenetic tree (using TreeViewJ, Colosimo et al., BMC Bioinformatics, also developed under this project), as well as map and timeline displays based on the Simile open source software.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2008
Accession Number
AD1107406

Entities

People

  • Joanne Luciano
  • Lynette Hirschman
  • Marc Colosimo
  • Matthew Peterson
  • Meredith Keybl
  • Scott Mardis

Organizations

  • MITRE Corporation

Tags

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Biology
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Data Integration
  • Data Set
  • Data Sets
  • Detection
  • Digital Data
  • Diseases And Disorders
  • Forensic Analysis
  • Health Services
  • Infectious Diseases
  • Lessons Learned
  • Metadata
  • Microorganisms
  • New York
  • Public Health
  • Sequence Analysis
  • Standards
  • Text Mining
  • Viruses
  • Visualizations

Fields of Study

  • Biology

Readers

  • Molecular Genetics
  • Virology (or Medical Virology).

Technology Areas

  • Biotechnology