Evidence map›Paper›PMID 17501996›Full record

ArticleBMC microbiology2007

The gene expression data of Mycobacterium tuberculosis based on Affymetrix gene chips provide insight into regulatory and hypothetical genes.

Li M Fu, Casey S Fu-Liu

Abstract read
In one paragraph

Article in BMC microbiology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Commonalities ofFrontiers in immunology · 2022
    Article
  2. Point mutation in the stop codon ofMicrobiology (Reading, England) · 2021
    Article
  3. Two New Dihydrosphingosine Analogs AgainstFrontiers in microbiology · 2021
    Article
  4. Frontiers in microbiology · 2017
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Li M FuPacific Tuberculosis and Cancer Research Organization, Irvine, California, USA. lifu@patcar.org
Casey S Fu-Liu

Funding

Functional Genomics Study and Database for TuberculosisR01HL080311 · NHLBI · PACIFIC TUBERCULOSIS &CANCER RES ORG · PI FU, LI · 2004 to 2006
$1.3M
NHLBI NIH HHS HL-080311NHLBI NIH HHS R01 HL080311
6 · The paper itself

Abstract

backgroundTuberculosis remains a leading infectious disease with global public health threat. Its control and management have been complicated by multi-drug resistance and latent infection, which prompts scientists to find new and more effective drugs. With the completion of the genome sequence of the etiologic bacterium, Mycobacterium tuberculosis, it is now feasible to search for new drug targets by sieving through a large number of gene products and conduct genome-scale experiments based on microarray technology. However, the full potential of genome-wide microarray analysis in configuring interrelationships among all genes in M. tuberculosis has yet to be realized. To date, it is only possible to assign a function to 52% of proteins predicted in the genome.

resultsWe conducted a functional-genomics study using the high-resolution Affymetrix oligonucleotide GeneChip. Approximately one-half of the genes were found to be always expressed, including more than 100 predicted conserved hypotheticals, in the genome of M. tuberculosis during the log phase of in vitro growth. The gene expression profiles were analyzed and visualized through cluster analysis to epitomize the full details of genomic behavior. Broad patterns derived from genome-wide expression experiments in this study have provided insight into the interrelationships among genes in the basic cellular processes of M. tuberculosis.

conclusionOur results have confirmed several known gene clusters in energy production, information pathways, and lipid metabolism, and also hinted at potential roles of hypothetical and regulatory proteins.

Indexed as

Gene Expression ProfilingGenes, BacterialGenes, RegulatorOligonucleotide Array Sequence AnalysisHumansMycobacterium tuberculosisRNA, BacterialRNA, MessengerRNA, BacterialRNA, Messenger

Identifiers

PMID17501996
PMCPMC1884158

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.