MIMOSA: Algorithms for Microbial Profiling

Ozkan Ufuk Nalbantoglu, Khalid Sayood

Research output: Contribution to journalArticle

Abstract

A significant goal of the study of metagenomes obtained from an environment is to find the microbial diversity and the abundance of each organism in the community. Phylotyping and binning methods which address this problem generally operate using either marker sequences or by classifying each genome fragment individually. However, these approaches might not use all the information contained in the metagenome.

Original languageEnglish (US)
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
DOIs
StateAccepted/In press - Apr 26 2018

Fingerprint

Metagenome
Binning
Profiling
Fragment
Genome
Genes
Community

Keywords

  • Approximation algorithms
  • Bioinformatics
  • Classification algorithms
  • Genomics
  • MIMO communication
  • Metagenomics
  • Organisms
  • Sequential analysis
  • microbial diversity estimation
  • phylotyping
  • sequence analysis
  • sparse recovery algorithms

ASJC Scopus subject areas

  • Biotechnology
  • Genetics
  • Applied Mathematics

Cite this

MIMOSA : Algorithms for Microbial Profiling. / Nalbantoglu, Ozkan Ufuk; Sayood, Khalid.

In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, 26.04.2018.

Research output: Contribution to journalArticle

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