Sipros Ensemble improves database searching and filtering for complex metaproteomics

Abstract

Complex microbial communities can be characterized by metagenomics and metaproteomics. However, metagenome assemblies often generate enormous, and yet incomplete, protein databases, which undermines the identification of peptides and proteins in metaproteomics. This challenge calls for increased discrimination of true identifications from false identifications by database searching and filtering algorithms in metaproteomics.

Document Details

Document Type
Pub Defense Publication
Publication Date
Sep 22, 2017
Source ID
10.1093/bioinformatics/btx601

Entities

People

  • Chongle Pan
  • David Tabb
  • Jimmy K Eng
  • Li Zhou
  • Qiuming Yao
  • Ryan S Mueller
  • William Judson Hervey Iv
  • Xuan Guo

Organizations

  • Engineer Research and Development Center
  • Oak Ridge National Laboratory
  • Oregon State University
  • Stellenbosch University
  • United States Naval Research Laboratory
  • University of North Texas
  • University of Tennessee
  • University of Washington

Tags

Fields of Study

  • Biology

Readers

  • Microbial Pathology
  • Neural Network Machine Learning.
  • Parallel and Distributed Computing.

Technology Areas

  • Biotechnology