Gene expression and cancer classification
Moving in bioRxiv, Nature Communications, Biotechnology advances, Journal of hepatology, medRxiv, Bioinformatics, Frontiers in Genetics and Nature.
- Moved, week to 23 Oct 2026
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- Papers in 60 days
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Latest in Gene expression and cancer classification
Newest first · last 60 days
XenoMix accurately quantifies mouse DNA contamination in PDX DNA methylation data with correlation coefficients above 0.99.
- Open access
SADRP outperforms state-of-the-art methods in drug response prediction by effectively modeling molecular structures and multi-omics data in cancer samples.
- Open access
LUNA, a generative AI model, accurately reconstructs tissue architecture from dissociated gene expression profiles, demonstrated by inferring spatial locations in over 1.2 million cells from the mouse brain atlas.
- Open access
- 6 cites
NMFBatch reduces technical variation by effectively correcting batch effects in proteomics data, demonstrated across diverse datasets including plasma and single-cell samples.
- Open access
VampW, a Bayesian method, reduces false discoveries and improves disease onset prediction by jointly modeling correlated omics features in time-to-event data.
- Open access
A gene-centered framework reveals context-dependent shifts in DNA methylation biomarker candidates across multiple cancers.
- Open access
- 1 cites
AmbiDose removes 92.0% of cross-species UMIs in human-mouse mixture while retaining 99.6% of same-species UMIs, reducing ambient RNA contamination in single-cell RNA sequencing.
- Open access
CellART accurately extracts comprehensive single-cell information from high-resolution spatial transcriptomics data using multimodal integration.
Multi-sample spatial transcriptomics reveals distinct regional fibrotic programs and cellular niches in human IPF, with 10X Xenium validation confirming key findings.
- Open access
- 20 cites
Translation engineering enables precise control of gene expression by modulating initiation, elongation, and termination phases, crucial for synthetic biology applications.
BatchVaria reveals that subtype-protected ComBat maintains nearly unchanged subtype contributions after correction, unlike naive ComBat which reduces them by 4.23%.
- Open access
DeepFS achieves 89.45% accuracy and 0.9647 AUC in diagnosing Alzheimer's disease from brain tissue transcriptomic data.
- Open access
Dreamlet enables fast, memory-efficient differential expression analysis of large-scale single-cell transcriptomics data, accurately identifying gene-trait associations across 150 Alzheimer's cases.
- 1 cited this week
- Open access
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Topics moving, week to 23 Oct 2026
- Single-cell and spatial transcriptomics6
- Neuroinflammation and Neurodegeneration Mechanisms5
- Bacteriophages and microbial interactions5
- Gut microbiota and health5
- Genomics and Phylogenetic Studies4
- Cancer Genomics and Diagnostics4
- Cancer Immunotherapy and Biomarkers4
- Alzheimer's disease research and treatments3
- Inflammatory Bowel Disease3
- Influenza Virus Research Studies3