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The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
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The ITS2 Database
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ReprDB and panDB: minimalist databases with maximal microbial representation.

Wei Zhou1, Nicole Gay1,2, Julia Oh3

  • 1The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.

Microbiome
|January 20, 2018
PubMed
Summary

New microbial reference databases, reprDB and panDB, improve shotgun metagenomic analysis by assembling non-redundant genomes. These tools enhance the profiling of complex microbiomes, assigning taxonomic labels to more sequencing reads.

Keywords:
Pan-genomeReference databaseShotgun metagenomicsWhole-genome alignment

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Genomics

Background:

  • Shotgun metagenomic profiling is limited by the absence of unified, compact, and compatible microbial reference genome databases.
  • Existing computational tools struggle to compile and update databases efficiently, leading to under-profiling of complex microbiomes.

Purpose of the Study:

  • To develop efficient pipelines for assembling non-redundant microbial genomic information from open-access genomes.
  • To create species-resolution microbial reference databases (reprDB and panDB) for improved metagenomic analysis.

Main Methods:

  • Developed pipelines to traverse and assemble non-redundant genomic information from all open-access microbial genomes.
  • Created reprDB (representative/reference genomes) and panDB (novel iterative alignment for pan-genome identification).

Main Results:

  • Generated two compact, species-resolution microbial reference databases: reprDB and panDB.
  • Successfully assigned taxonomic labels and genome positions to the majority of metagenomic reads from human skin and gut microbiomes.
  • Demonstrated significant improvement over previous database-guided analyses.

Conclusions:

  • reprDB and panDB enable more comprehensive metagenomic profiling by utilizing the growing number of open-access microbial genomes.
  • Databases exclude redundant information, reducing storage, memory, and analysis time.
  • The novel iterative alignment algorithm enhances pan-genome identification efficiency for comparative genomics.