Back to search

Article

A modified multiple-criteria decision-making approach based on a protein-protein interaction network to diagnose latent tuberculosis

2024-05-09

Abstract excerpt

<title>Abstract</title> <p><bold>Background</bold> DNA microarrays provide informative data for transcriptional profiling and identifying gene expression signatures to help prevent progression from latent tuberculosis infection (LTBI) to active disease. However, constructing a prognostic model for distinguishing LTBI from active tuberculosis is very challenging due to the noisy nature of data and lack of a genera...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
8c32284f-f5d1-5ce9-a6e1-d5427f18fcf8
DOI
10.21203/rs.3.rs-4336345/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
A modified multiple-criteria decision-making approach based on a protein-protein interaction network to diagnose latent tuberculosisDOI 10.21203/rs.3.rs-4336345/v1
Transcriptional Profiling and Deriving a Seven-Gene Signature That Discriminates Active and Latent Tuberculosis: An Integrative Bioinformatics ApproachSemantic proximity
AIM2 and FCGR1A, two potential diagnostic biomarkers for distinguishing infection statuses of Mycobacterium tuberculosisSemantic proximity
Distinguish active tuberculosis with an immune-related signature and molecule subtypes: a multi-cohort analysisSemantic proximity
An integrated data analysis and computational approach to reveal gene signatures for paediatric Tuberculosis meningitis related to non-tuberculosis patientsSemantic proximity
A protein signature associated with active tuberculosis identified by plasma profiling and network-based analysisSemantic proximity
Stage specific classification of DEGs via statistical profiling and network analysis reveals potential biomarker associated with various stages of TBSemantic proximity
Identification of Gene Expression Biomarkers Predictive of Latent Tuberculosis Infection Using Machine Learning ApproachesSemantic proximity
Identification of apoptosis-related gene signatures as potential biomarkers for differentiating active from latent tuberculosis via bioinformatics analysisSemantic proximity
Identification and Classification of Differentially Expressed Genes and Network Meta-Analysis Reveals Potential Molecular Signatures Associated With TuberculosisSemantic proximity
Diagnostic biomarkers for invasive aspergillosis utilizing weighted gene co-expression network analysisSemantic proximity
SFM: A novel sequence-based fusion method for disease genes identification and prioritization.Semantic proximity
Multiple-Criteria Decision Analysis-Based Multifactor Dimensionality Reduction for Detecting Gene-Gene Interactions.Semantic proximity
Select a neighboring publication to make it the new centre.