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Main Authors:	Usman, Mohammad, Varea, Olga, Radeva, Petia, Canals, Josep, Abante, Jordi, Ortiz, Daniel
Format:	Preprint
Published:	2025
Subjects:	Genomics Computer Vision and Pattern Recognition Machine Learning
Online Access:	https://arxiv.org/abs/2501.03923
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Online t-SNE for single-cell RNA-seq
by: Ma, Hui, et al.
Published: (2024)

Categorization and analysis of 14 computational methods for estimating cell potency from single-cell RNA-seq data
by: Wang, Qingyang, et al.
Published: (2023)

White-Box Diffusion Transformer for single-cell RNA-seq generation
by: Cui, Zhuorui, et al.
Published: (2024)

scRDiT: Generating single-cell RNA-seq data by diffusion transformers and accelerating sampling
by: Dong, Shengze, et al.
Published: (2024)

Meta-analysis of scRNA-seq data for choroidal endothelial cells in dry Age-related Macular Degeneration
by: Veksler, Kyle M., et al.
Published: (2026)

Partial domain adaptation enables cross domain cell type annotation between scRNA-seq and snRNA-seq
by: Chen, Xiran, et al.
Published: (2025)

A versatile informative diffusion model for single-cell ATAC-seq data generation and analysis
by: Huang, Lei, et al.
Published: (2024)

Systematic evaluation of the isolated effect of tissue environment on the transcriptome using a single-cell RNA-seq atlas dataset
by: Okada, Daigo, et al.
Published: (2024)

Predicting Breast Cancer Phenotypes from Single-cell RNA-seq Data Using CloudPred
by: Moghimianavval, Hossein, et al.
Published: (2024)

Discovering Interpretable Biological Concepts in Single-cell RNA-seq Foundation Models
by: Claye, Charlotte, et al.
Published: (2025)

Uncertainty-aware t-distributed Stochastic Neighbor Embedding for Single-cell RNA-seq Data
by: Ma, Hui, et al.
Published: (2024)

ScAtt: an Attention based architecture to analyze Alzheimer's disease at cell type level from single-cell RNA-sequencing data
by: Liu, Xiaoxia, et al.
Published: (2024)

scBench: Evaluating AI Agents on Single-Cell RNA-seq Analysis
by: Workman, Kenny, et al.
Published: (2026)

scCDCG: Efficient Deep Structural Clustering for single-cell RNA-seq via Deep Cut-informed Graph Embedding
by: Xu, Ping, et al.
Published: (2024)

Integrative analysis of ATAC-seq and RNA-seq for cells infected by human T-cell leukemia virus type 1
by: Tanaka, Azusa, et al.
Published: (2023)

scX: A user-friendly tool for scRNA-seq exploration
by: Waichman, Tomás Vega, et al.
Published: (2023)

Mix-Geneformer: Unified Representation Learning for Human and Mouse scRNA-seq Data
by: Nishio, Yuki, et al.
Published: (2025)

HybridQC: Machine Learning-Augmented Quality Control for Single-Cell RNA-seq Data
by: Lai, Kaitao
Published: (2025)

scASDC: Attention Enhanced Structural Deep Clustering for Single-cell RNA-seq Data
by: Min, Wenwen, et al.
Published: (2024)

Identification and characterization of unique to human regulatory sequences in embryonic stem cells reveal associations with transposable elements, distal enhancers, non-coding RNA, and DNA methylation-driven mechanisms of genome editing
by: Glinsky, Gennadi
Published: (2014)

JojoSCL: Shrinkage Contrastive Learning for single-cell RNA sequence Clustering
by: Wang, Ziwen
Published: (2025)

Comparison of algorithms used in single-cell transcriptomic data analysis
by: Isbarov, Jafar, et al.
Published: (2024)

A Bayesian approach to model uncertainty in single-cell genomic data
by: Ren, Shanshan, et al.
Published: (2025)

Modeling Temporal scRNA-seq Data with Latent Gaussian Process and Optimal Transport
by: Balik, Mehmet Yigit, et al.
Published: (2026)

Single‐Cell RNA‐seq Reveals Deubiquitination Genes as Prognostic Markers in Hepatocellular Carcinoma
by: Xuening Lv, et al.
Published: (2026)

Bipartite Graph Attention-based Clustering for Large-scale scRNA-seq Data
by: Liang, Zhuomin, et al.
Published: (2026)

Hypergraph Representations of scRNA-seq Data for Improved Clustering with Random Walks
by: He, Wan, et al.
Published: (2025)

Soft Graph Clustering for single-cell RNA Sequencing Data
by: Xu, Ping, et al.
Published: (2025)

Multi-modal single-cell foundation models via dynamic token adaptation
by: Zhao, Wenmin, et al.
Published: (2025)

Rare Genomic Subtype Discovery from RNA-seq via Autoencoder Embeddings and Stability-Aware Clustering
by: Mezghiche, Alaa
Published: (2025)

scInterpreter: Training Large Language Models to Interpret scRNA-seq Data for Cell Type Annotation
by: Li, Cong, et al.
Published: (2024)

A Hybrid Computational Intelligence Framework for scRNA-seq Imputation: Integrating scRecover and Random Forests
by: Anaissi, Ali, et al.
Published: (2025)

Pan-cancer gene set discovery via scRNA-seq for optimal deep learning based downstream tasks
by: Kim, Jong Hyun, et al.
Published: (2024)

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data
by: Huang, Yu-An, et al.
Published: (2025)

scReader: Prompting Large Language Models to Interpret scRNA-seq Data
by: Li, Cong, et al.
Published: (2024)

Defining the relationship between cathepsin B and esophageal adenocarcinoma: conjoint analysis of Mendelian randomization, transcriptome-wide association studies, and single-cell RNA sequencing data
by: Li, Jialin, et al.
Published: (2025)

Lower-dimensional projections of cellular expression improves cell type classification from single-cell RNA sequencing
by: Umar, Muhammad, et al.
Published: (2024)

GPU-accelerated single-cell analysis at scale with rapids-singlecell
by: Dicks, Severin, et al.
Published: (2026)

Deep Learning and Explainable AI: New Pathways to Genetic Insights
by: Wang, Chenyu, et al.
Published: (2025)

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