Microarray Data Analysis

Tools in Pharmacogenomics Biomarker Identification for Cancer Patients.- High Performance Framework to Analyze Microarray Data.- Web and Cloud Computing to Analyze Microarray Data.- A Microarray Analysis Technique Using a Self-Organizing Multi-Agent Approach.- Improving Analysis and Annotation of Microarray Data with Protein Interactions.- Algorithms to Preprocess Microarray Image Data.- Microarray Data Preprocessing: From Experimental Design to Differential Analysis.- Supervised Methods for Biomarker Detection from Microarray Experiments.- Unsupervised Algorithms for Microarray Sample Stratification.- Pathway Enrichment Analysis of Microarray Data.- Network Analysis of Microarray Data.- geneExpressionFromGEO: An R Package to Facilitate Data Reading from Gene Expression Omnibus (GEO).- Scenarios for the Integration of Microarray Gene Expression Profiles in COVID-19-Related Studies.- Alignment of Microarray Data.- Integration of DNA Microarray with Clinical and Genomic Data.- ClusteringMethods for Microarray Data Sets.- Microarray Data Analysis Protocol.- Using Gene Ontology to Annotate and Prioritize Microarray Data.- Using MMRFBiolinks R-Package for Discovering Prognostic Markers in Multiple Myeloma.