Application of machine learning (ML) / deep learning (DL) using multiple epigenetic features reveals H3K27Ac as driver of gene expression prediction across patients with glioblastoma [ChIP-Seq]
Direct links to NCBI, no account and no request form: the whole study as GSE296944_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 7 samples. Raw sequencing reads are also available from ENA.
Also filed as BioProject PRJNA1261972 and SRA study SRP584749. Searching any of these in the dataset finder brings you back here.
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- GSE339365 Genome-wide H3K4me3 profiling of circulating immune cells reveals dynamic epigenetic reprogramming during acute critical COVID-19 120 samples
- GSE302930 Epigenetic Atlas of Bladder Cancer Reveals Master Transcription Factors and Risk-Associated Regulatory Elements in Luminal and Basal-Squamous Molecular Subtypes 92 samples
- GSE296831 Epigenetic Context Defines the Transcriptional Activity of Canonical and Noncanonical NF-kappaB Signaling in Pancreatic Cancer [ChIP-Seq] 48 samples
- GSE294275 Transcriptional analysis of direct NSD2 target genes in t(4;14) multiple myeloma reveals H3K36me2-dependent regulation and H3K27me3 antagonism [CUT&TAG] 40 samples
- GSE267597 AP-1 Mediates Oncogenic Transcription and Predicts Fatality in Lung Squamous Cell Carcinoma Patients [ChIP-seq] 36 samples
- GSE282760 Epigenomic manipulation reveals the relationship between locus specific chromatin dynamics and gene expression [ChIP-seq] 36 samples
- GSE337829 Integrated single-cell profiling of RNA and DNA interactomes reveals targetable chromatin architectures in cancer [ChIP-Seq] 32 samples
- GSE279410 Mitochondrial metabolism and epigenetic crosstalk drive the SASP (ChIP-seq) 30 samples
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