Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Bioinformatic and Empirical Analysis of Novel Hypoxia-Inducible Targets of the Human Antituberculosis T Cell Response

20 Nov 2012

Abstract excerpt

We analyzed whole genome-based transcriptional profiles of Mycobacterium tuberculosis subjected to prolonged hypoxia to guide the discovery of novel potential Ags, by a combined bioinformatic and empirical approach. We analyzed the fold induction of the 100 most highly induced genes at 7 d of hypoxia, as well as transcript abundance, peptide-binding prediction (ProPred) adjusted for population-specific MHC class...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to interferon and immune responses
Share to Pneumonia and Respiratory Infections
Share to Tuberculosis Research and Epidemiology

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 23169589
DOI: 10.4049/jimmunol.1202281

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 8 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Bioinformatic and Empirical Analysis of Novel Hypoxia-Inducible Targets of the Human Antituberculosis T Cell ResponsePMID 23169589Read ↗

New Genome-Wide Algorithm Identifies Novel In-Vivo Expressed Mycobacterium Tuberculosis Antigens Inducing Human T-Cell Responses with Classical and Unconventional Cytokine ProfilesSemantic proximity Read ↗

Whole genome identification of Mycobacterium tuberculosisvaccine candidates by comprehensive data mining and bioinformatic analysesSemantic proximity Read ↗

Immunopathogenic Overlap and Shared Therapeutic Targets for Covid-19 and Tuberculosis Predicted from Transcriptomic Meta-AnalysisSemantic proximity Read ↗

Immunopathogenic overlap between COVID-19 and tuberculosis identified from transcriptomic meta-analysis and human macrophage infectionSemantic proximity Read ↗

Predicting bacterial fitness in Mycobacterium tuberculosis with transcriptional regulatory network-informed interpretable machine learningSemantic proximity Read ↗

Immunogenicity of Eight Dormancy Regulon-Encoded Proteins of Mycobacterium tuberculosis in DNA-Vaccinated and Tuberculosis-Infected MiceSemantic proximity Read ↗

The bacillary and macrophage response to hypoxia in tuberculosis and the consequences for T cell antigen recognitionSemantic proximity Read ↗

Regulation of the <i>Mycobacterium tuberculosis</i> hypoxic response gene encoding α-crystallinSemantic proximity Read ↗

Hypoxia Sensing and Persistence Genes Are Expressed during the Intragranulomatous Survival of Mycobacterium tuberculosisSemantic proximity Read ↗

Predicting fitness in Mycobacterium tuberculosis with transcriptional regulatory network-informed interpretable machine learningSemantic proximity Read ↗

Transcriptional analysis of human peripheral blood mononuclear cells stimulated by Mycobacterium tuberculosis antigenSemantic proximity Read ↗

Polymorphisms of 20 regulatory proteins between Mycobacterium tuberculosis and Mycobacterium bovis.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.