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

Identification and Classification of Differentially Expressed Genes and Network Meta-Analysis Reveals Potential Molecular Signatures Associated With Tuberculosis

4 Nov 2019

Abstract excerpt

Tuberculosis (TB) is one of deadly transmissible disease that causes death worldwide; however, only 10% of people infected with Mycobacterium tuberculosis develop disease, indicating that host genetic factors may play key role in determining susceptibility to TB disease. In this way, the analysis of gene expression profiling of TB infected individuals can give us a snapshot of actively expressed genes and...

Read the complete abstract on PubMed

Topics

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

Share to Bioinformatics and Genomic Networks
Share to Computational Drug Discovery Methods
Share to Tuberculosis Research and Epidemiology

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 31749827
DOI: 10.3389/fgene.2019.00932

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

Identification and Classification of Differentially Expressed Genes and Network Meta-Analysis Reveals Potential Molecular Signatures Associated With TuberculosisPMID 31749827Read ↗

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

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

Gene network in pulmonary tuberculosis based on bioinformatic analysisSemantic proximity Read ↗

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

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

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

Identification of differentially expressed genes and hub genes of human hosts with tuberculosis through an integrated bioinformatics strategySemantic proximity Read ↗

Gene expression profiling meta-analysis reveals novel gene signatures and pathways shared between tuberculosis and rheumatoid arthritisSemantic proximity Read ↗

Identification of hub genes and establishment of a diagnostic model in tuberculosis infectionSemantic proximity Read ↗

An Integrative Network Approach to Identify Common Genes for the Therapeutics in Tuberculosis and Its Overlapping Non-Communicable DiseasesSemantic proximity Read ↗

Computational reassessment of RNA-seq data reveals key genes in active tuberculosisSemantic proximity Read ↗

Identification of differentially expressed genes and hub genes of human hosts with tuberculosis through an integrated bioinformatics and cell confirmation strategySemantic proximity Read ↗

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