analyze_geo_microarrays.py : Differential expression analysis of published microarrays datasets from the NCBI Gene Expression Omnibus (GEO)
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Updated
Aug 1, 2021 - Python
analyze_geo_microarrays.py : Differential expression analysis of published microarrays datasets from the NCBI Gene Expression Omnibus (GEO)
UNet 2.0 - Pytorch implementation of the U-Net 2.0 for image semantic segmentation, with processing blocks for noisy images
Bioinformatics course project - Fall 2020, analysis of genetic expression omnibus (GEO) data series of Acute Myeloid Leukemia
Python port of R limma for differential expression analysis
Genomic data manipulation tool
A toolkit for navigating and analyzing gene expression datasets
Beacon v2 - CNAG Biomedical Informatics - Tools (Data ingestion tools)
bioTEA - A user friendly tool to perform transcript expression analysis
SparkRMA: Robust Multi-array Average (RMA) In Apache Spark
A list of publicly available Microarray Gene Expression datasets with proper attribution and associated toolkits.
Cross-platform (Windows + Linux) no-code desktop app for reproducible bulk RNA-seq & microarray analysis: STAR/HISAT2/Salmon alignment, DESeq2/limma, GO/KEGG/g:Profiler enrichment, and STRING PPI networks — with first-class support for crops and fungi that lack a Bioconductor OrgDb.
Label-driven comparison of gene expression regions across measurement technologies. Microarray, bulk RNA-seq and single-cell in one question, local first, no API keys.
extract experimental metadata from GEO xml files
CGI server for searching and visualizing array database
Differential Expression Analysis Pipeline
Genetic-embedded Nuclear Reaction Optimization with F-score filtering for gene selection in cancer classification. Published in IJMS 2025.
Automated GEO dataset search, download, and preprocessing tool for gene expression meta-analyses
Unsupervised clustering and differential expression of GABAergic interneuron markers in postmortem DLPFC: schizophrenia vs. control (GSE53987)
F-score filtering combined with Nuclear Reaction Optimization for gene selection in cancer classification. Methodology, datasets, and results from the CIMB 2025 paper.
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