ArticleMethods in molecular biology (Clifton, N.J.)2022
Network Analysis of Microarray Data.
Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Comparing gene-gene co-expression network approaches for the analysis of cell differentiation and specification on scRNAseq data.Computational and structural biotechnology journal · 2025Article
- The impact of dropouts in scRNAseq dense neighborhood analysis.Computational and structural biotechnology journal · 2025Article
- Single-cell combined with transcriptome sequencing to explore the molecular mechanism of cell communication in idiopathic pulmonary fibrosis.Journal of cellular and molecular medicine · 2024Article
- Data-driven analysis and druggability assessment methods to accelerate the identification of novel cancer targets.Computational and structural biotechnology journal · 2023Review
- Toxicogenomics Data for Chemical Safety Assessment and Development of New Approach Methodologies: An Adverse Outcome Pathway-Based Approach.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Nextcast: A software suite to analyse and model toxicogenomics data.Computational and structural biotechnology journal · 2022Article
- The potential of a data centred approach & knowledge graph data representation in chemical safety and drug design.Computational and structural biotechnology journal · 2022Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
DNA microarrays are widely used to investigate gene expression. Even though the classical analysis of microarray data is based on the study of differentially expressed genes, it is well known that genes do not act individually. Network analysis can be applied to study association patterns of the genes in a biological system. Moreover, it finds wide application in differential coexpression analysis between different systems. Network based coexpression studies have for example been used in (complex) disease gene prioritization, disease subtyping, and patient stratification.In this chapter we provide an overview of the methods and tools used to create networks from microarray data and describe multiple methods on how to analyze a single network or a group of networks. The described methods range from topological metrics, functional group identification to data integration strategies, topological pathway analysis as well as graphical models.
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Registered trials
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.