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

Transcriptional Profiling and Deriving a Seven-Gene Signature That Discriminates Active and Latent Tuberculosis: An Integrative Bioinformatics Approach

29 Mar 2022

Abstract excerpt

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (M.tb.). Our integrative analysis aims to identify the transcriptional profiling and gene expression signature that distinguish individuals with active TB (ATB) disease, and those with latent tuberculosis infection (LTBI). In the present study, we reanalyzed a microarray dataset (GSE37250) from GEO database and explored the data for...

Read the complete abstract on PubMed

Topics

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

Share to Diagnosis and treatment of tuberculosis
Share to Mycobacterium research and diagnosis
Share to Tuberculosis Research and Epidemiology

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 35456421
DOI: 10.3390/genes13040616

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 1 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Transcriptional Profiling and Deriving a Seven-Gene Signature That Discriminates Active and Latent Tuberculosis: An Integrative Bioinformatics ApproachPMID 35456421Read ↗

Human gene expression profiling identifies key therapeutic targets in tuberculosis infection: A systematic network meta-analysis.Semantic proximity Read ↗

Distinguish active tuberculosis with an immune-related signature and molecule subtypes: a multi-cohort analysisSemantic proximity Read ↗

Diagnosis of pulmonary tuberculosis via identification of core genes and pathways utilizing blood transcriptional signatures: a multicohort analysisSemantic proximity Read ↗

Identification and Classification of Differentially Expressed Genes and Network Meta-Analysis Reveals Potential Molecular Signatures Associated With TuberculosisSemantic proximity Read ↗

Identification of apoptosis-related gene signatures as potential biomarkers for differentiating active from latent tuberculosis via bioinformatics analysisSemantic proximity Read ↗

AIM2 and FCGR1A, two potential diagnostic biomarkers for distinguishing infection statuses of Mycobacterium tuberculosisSemantic proximity Read ↗

Identification of Gene Expression Biomarkers Predictive of Latent Tuberculosis Infection Using Machine Learning ApproachesSemantic proximity Read ↗

Transcriptional Profiling of Human Peripheral Blood Mononuclear Cells Identifies Diagnostic Biomarkers That Distinguish Active and Latent TuberculosisSemantic proximity Read ↗

Screening of extra-pulmonary tuberculosis signature genes and analysis of correlation with immune cellsSemantic proximity Read ↗

Coexpression Network Analysis-Based Identification of Critical Genes Differentiating between Latent and Active TuberculosisSemantic proximity Read ↗

Genome-wide transcriptional profiling identifies potential signatures in discriminating active tuberculosis from latent infectionSemantic proximity Read ↗

Stage specific classification of DEGs via statistical profiling and network analysis reveals potential biomarker associated with various stages of TBSemantic proximity Read ↗

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