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Database Commons - POGO-DB

POGO-DB

Citations: 4

z-index 0.99

Short name POGO-DB
Full name Database of Pairwise-comparisons Of Genomes and universal Orthologous genes
Description A major aim of metagenomic studies is to identify and compare the phylogenetic composition of different samples. This task is usually accomplished by the use of marker genes that are globally conserved across prokaryotes, such as the 16S rRNA gene. Therefore, the choice of markers can greatly affect the results of studies, as different marker genes evolve at different rates and may represent better or worse the phylogenetic relationships of different prokaryotic lineages. Database of Pairwise-comparisons Of Genomes and universal Orthologous genes (POGO-DB) provides a tool for users to probe questions regarding how different aspects of genome variation relate to each other, and to choose marker genes that will better fit the aims of specific studies in a more informed way.
URL http://pogo.ece.drexel.edu/
Year founded 2013
Last update & version 2014-01-01    v1.0
Availability Free to all users
University/Institution hosted Drexel University
Address 3141 Chestnut Street, Philadelphia, Pennsylvania 19104, USA
City Philadelphia
Province/State Pennsylvania
Country/Region United States
Contact name Gail L. Rosen
Contact email gailr@ece.drexel.edu
Data type(s)
Major organism(s)
Keyword(s)
  • 16S rRNA
  • marker gene
  • orthologous gene
Publication(s)
  • POGO-DB--a database of pairwise-comparisons of genomes and conserved orthologous genes. [PMID: 24198250]

    Yemin Lan, J Calvin Morrison, Ruth Hershberg, Gail L Rosen
    Nucleic acids research 2014:42(Database issue)
    4 Citations (Google Scholar as of 2016-01-28)

    Abstract: POGO-DB (http://pogo.ece.drexel.edu/) provides an easy platform for comparative microbial genomics. POGO-DB allows users to compare genomes using pre-computed metrics that were derived from extensive computationally intensive BLAST comparisons of >2000 microbes. These metrics include (i) average protein sequence identity across all orthologs shared by two genomes, (ii) genomic fluidity (a measure of gene content dissimilarity), (iii) number of 'orthologs' shared between two genomes, (iv) pairwise identity of the 16S ribosomal RNA genes and (v) pairwise identity of an additional 73 marker genes present in >90% prokaryotes. Users can visualize these metrics against each other in a 2D plot for exploratory analysis of genome similarity and of how different aspects of genome similarity relate to each other. The results of these comparisons are fully downloadable. In addition, users can download raw BLAST results for all or user-selected comparisons. Therefore, we provide users with full flexibility to carry out their own downstream analyses, by creating easy access to data that would normally require heavy computational resources to generate. POGO-DB should prove highly useful for researchers interested in comparative microbiology and benefit the microbiome/metagenomic communities by providing the information needed to select suitable phylogenetic marker genes within particular lineages.

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Accessibility

Rate of accessibility:
HTTP status codeDate requested
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200 OK2018-02-02
200 OK2018-01-30
200 OK2018-01-26
200 OK2018-01-23
200 OK2018-01-19
200 OK2018-01-16
200 OK2018-01-12
200 OK2018-01-09
200 OK2018-01-05
200 OK2018-01-02
200 OK2017-12-29
200 OK2017-12-26
200 OK2017-12-22
200 OK2017-12-19
200 OK2017-12-15
200 OK2017-12-12
200 OK2017-12-08
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200 OK2017-12-01
-1 Failed2017-11-28
200 OK2017-11-24
200 OK2017-11-21
200 OK2017-11-17
200 OK2017-11-14
200 OK2017-11-10
200 OK2017-11-07
200 OK2017-11-03
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200 OK2017-10-27
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200 OK2017-03-14
200 OK2017-03-10
200 OK2017-03-07
200 OK2017-03-03
200 OK2017-02-28
200 OK2017-02-24
200 OK2017-02-21
200 OK2017-02-17
200 OK2017-02-14
200 OK2017-02-10
200 OK2017-02-07
200 OK2017-02-03
200 OK2017-01-31
200 OK2017-01-27
200 OK2017-01-24
200 OK2017-01-20
200 OK2017-01-17
200 OK2017-01-13
200 OK2017-01-10
200 OK2017-01-06
200 OK2017-01-03
200 OK2016-12-30
200 OK2016-12-27
200 OK2016-12-23
200 OK2016-12-20
200 OK2016-12-16
200 OK2016-12-13
200 OK2016-12-09
200 OK2016-12-06
200 OK2016-12-02
200 OK2016-11-29
200 OK2016-11-25
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200 OK2016-11-18
200 OK2016-11-15
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200 OK2016-11-08
200 OK2016-11-04
200 OK2016-11-01
200 OK2016-10-28
200 OK2016-10-25
200 OK2016-10-21
200 OK2016-10-18
200 OK2016-10-14
200 OK2016-10-11
200 OK2016-10-07
200 OK2016-10-04
200 OK2016-09-30
200 OK2016-09-27
200 OK2016-09-23
200 OK2016-09-20
200 OK2016-09-16
200 OK2016-09-13
200 OK2016-09-09
200 OK2016-09-06
200 OK2016-09-02
200 OK2016-08-30
200 OK2016-08-26
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200 OK2016-08-19
200 OK2016-08-16
200 OK2016-08-12
200 OK2016-08-09
200 OK2016-08-05
200 OK2016-08-02
200 OK2016-07-29
200 OK2016-07-26
200 OK2016-07-22
200 OK2016-07-19
200 OK2016-07-15
200 OK2016-07-12
200 OK2016-07-08
200 OK2016-07-05
200 OK2016-07-01
200 OK2016-06-28
200 OK2016-06-24
200 OK2016-06-21
200 OK2016-06-17
200 OK2016-06-14
200 OK2016-06-10
200 OK2016-06-07
200 OK2016-06-03
200 OK2016-05-31
200 OK2016-05-27
200 OK2016-05-24
200 OK2016-05-20
200 OK2016-05-17
200 OK2016-05-13
200 OK2016-05-10
200 OK2016-05-06
200 OK2016-05-03
200 OK2016-04-29
200 OK2016-04-26
200 OK2016-04-22
200 OK2016-04-19
200 OK2016-04-15
200 OK2016-04-12
200 OK2016-04-08
200 OK2016-04-05
200 OK2016-04-01
200 OK2016-03-29
200 OK2016-03-28
200 OK2016-03-25
200 OK2016-03-23
200 OK2016-03-21
200 OK2016-03-18
200 OK2016-03-16
200 OK2016-03-14
200 OK2016-03-11
200 OK2016-03-09
200 OK2016-03-07
200 OK2016-03-04
200 OK2016-03-02
200 OK2016-02-29
200 OK2016-02-26
200 OK2016-02-24
200 OK2016-02-22
200 OK2016-02-19
200 OK2016-02-17
200 OK2016-02-15
200 OK2016-02-14
200 OK2016-02-12
200 OK2016-02-10
200 OK2016-02-08
200 OK2016-02-07
200 OK2016-02-05
200 OK2016-02-03
200 OK2016-02-01
200 OK2016-01-31
200 OK2016-01-29
200 OK2016-01-27
200 OK2016-01-25
200 OK2016-01-24
200 OK2016-01-22
200 OK2016-01-20
200 OK2016-01-18
200 OK2016-01-17
200 OK2016-01-15
200 OK2016-01-13
200 OK2016-01-11
200 OK2016-01-10
200 OK2016-01-08
200 OK2016-01-06
200 OK2016-01-04

Tags

DNA RNA
Prokaryote
16S rRNA marker gene orthologous gene

Record metadata

  • Created on: 2015-06-20
  • Curated by:
    • Shixiang Sun [2016-03-25]
    • Shixiang Sun [2015-11-21]
    • Shixiang Sun [2015-06-28]
    • Shixiang Sun [2015-06-26]
Stats