Cover Image

Single-cell Curriculum Learning-based Deep Graph Embedding Clustering

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Huifa, Fu, Jie, Ling, Xinpeng, Sun, Zhiyu, Wang, Kuncan, Chen, Zhili
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Genomics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DP-DCAN: Differentially Private Deep Contrastive Autoencoder Network for Single-cell Clustering
by: Li, Huifa, et al.
Published: (2023)

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

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

scAGC: Learning Adaptive Cell Graphs with Contrastive Guidance for Single-Cell Clustering
by: Li, Huifa, et al.
Published: (2025)

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

DOGMA: Weaving Structural Information into Data-centric Single-cell Transcriptomics Analysis
by: Zhang, Ru, et al.
Published: (2026)

scSiameseClu: A Siamese Clustering Framework for Interpreting single-cell RNA Sequencing Data
by: Xu, Ping, et al.
Published: (2025)

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

Quantum-Boosted High-Fidelity Deep Learning
by: Wang, Feng-ao, et al.
Published: (2025)

Celler:A Genomic Language Model for Long-Tailed Single-Cell Annotation
by: Zhao, Huan, et al.
Published: (2025)

Gene Incremental Learning for Single-Cell Transcriptomics
by: Qi, Jiaxin, et al.
Published: (2025)

TFBS-Finder: Deep Learning-based Model with DNABERT and Convolutional Networks to Predict Transcription Factor Binding Sites
by: Ghosh, Nimisha, et al.
Published: (2025)

Knowledge Graph Sparsification for GNN-based Rare Disease Diagnosis
by: Cara, Premt, et al.
Published: (2025)

Soft-Evidence Fused Graph Neural Network for Cancer Driver Gene Identification across Multi-View Biological Graphs
by: Chen, Bang, et al.
Published: (2025)

scI2CL: Effectively Integrating Single-cell Multi-omics by Intra- and Inter-omics Contrastive Learning
by: Liu, Wuchao, et al.
Published: (2025)

PhenoGnet: A Graph-Based Contrastive Learning Framework for Disease Similarity Prediction
by: Baminiwatte, Ranga, et al.
Published: (2025)

SynLeaF: A Dual-Stage Multimodal Fusion Framework for Synthetic Lethality Prediction Across Pan- and Single-Cancer Contexts
by: Xing, Zheming, et al.
Published: (2026)

Absorb & Escape: Overcoming Single Model Limitations in Generating Genomic Sequences
by: Li, Zehui, et al.
Published: (2024)

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

Artificial Intelligence and Deep Learning Algorithms for Epigenetic Sequence Analysis: A Review for Epigeneticists and AI Experts
by: Tahir, Muhammad, et al.
Published: (2025)

A Novel cVAE-Augmented Deep Learning Framework for Pan-Cancer RNA-Seq Classification
by: Polepalli, Vinil
Published: (2025)

How Private Are DNA Embeddings? Inverting Foundation Model Representations of Genomic Sequences
by: Ouaari, Sofiane, et al.
Published: (2026)

DeepVRegulome: DNABERT-based deep-learning framework for predicting the functional impact of short genomic variants on the human regulome
by: Dutta, Pratik, et al.
Published: (2025)

CAVACHON: a hierarchical variational autoencoder to integrate multi-modal single-cell data
by: Hsieh, Ping-Han, et al.
Published: (2024)

Fast and Scalable Gene Embedding Search: A Comparative Study of FAISS and ScaNN
by: Refahi, Mohammad Saleh, et al.
Published: (2025)

TEPI: Taxonomy-aware Embedding and Pseudo-Imaging for Scarcely-labeled Zero-shot Genome Classification
by: Aakur, Sathyanarayanan, et al.
Published: (2024)

stMCDI: Masked Conditional Diffusion Model with Graph Neural Network for Spatial Transcriptomics Data Imputation
by: Li, Xiaoyu, et al.
Published: (2024)

Single Cells Are Spatial Tokens: Transformers for Spatial Transcriptomic Data Imputation
by: Wen, Hongzhi, et al.
Published: (2023)

Deep Generative Models for Discrete Genotype Simulation
by: Xie, Sihan, et al.
Published: (2025)

CASPER: Cross-modal Alignment of Spatial and single-cell Profiles for Expression Recovery
by: Kumar, Amit, et al.
Published: (2025)

Multi-Dimensional Spectral Geometry of Biological Knowledge in Single-Cell Transformer Representations
by: Kendiukhov, Ihor
Published: (2026)

Enhanced Gene Selection in Single-Cell Genomics: Pre-Filtering Synergy and Reinforced Optimization
by: Zhang, Weiliang, et al.
Published: (2024)

Missing-Modality-Aware Graph Neural Network for Cancer Classification
by: Tabakhi, Sina, et al.
Published: (2025)

xTrimoGene: An Efficient and Scalable Representation Learner for Single-Cell RNA-Seq Data
by: Gong, Jing, et al.
Published: (2023)

Masked Graph Autoencoders with Contrastive Augmentation for Spatially Resolved Transcriptomics Data
by: Fang, Donghai, et al.
Published: (2024)

Machine Learning-Based Genomic Linguistic Analysis (Gene Sequence Feature Learning): A Case Study on Predicting Heavy Metal Response Genes in Rice
by: Yang, Ruiqi, et al.
Published: (2025)

Dy-mer: An Explainable DNA Sequence Representation Scheme using Dictionary Learning
by: Peng, Zhiyuan, et al.
Published: (2024)

Omni-DNA: A Unified Genomic Foundation Model for Cross-Modal and Multi-Task Learning
by: Li, Zehui, et al.
Published: (2025)

Identification of Prognostic Biomarkers for Stage III Non-Small Cell Lung Carcinoma in Female Nonsmokers Using Machine Learning
by: Zheng, Huili, et al.
Published: (2024)

A New Framework for Explainable Rare Cell Identification in Single-Cell Transcriptomics Data
by: Su, Di, et al.
Published: (2026)