Interpretable deep learning in single-cell omics
Fuente:
arXiv
Saved in:
| Main Authors: | Wagle, Manoj M, Long, Siqu, Chen, Carissa, Liu, Chunlei, Yang, Pengyi |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Machine learning applied to omics data
by: Calviño, Aida, et al.
Published: (2024)
by: Calviño, Aida, et al.
Published: (2024)
scMRDR: A scalable and flexible framework for unpaired single-cell multi-omics data integration
by: Sun, Jianle, et al.
Published: (2025)
by: Sun, Jianle, et al.
Published: (2025)
scMEDAL for the interpretable analysis of single-cell transcriptomics data with batch effect visualization using a deep mixed effects autoencoder
by: Andrade, Aixa X., et al.
Published: (2024)
by: Andrade, Aixa X., et al.
Published: (2024)
White-Box Diffusion Transformer for single-cell RNA-seq generation
by: Cui, Zhuorui, et al.
Published: (2024)
by: Cui, Zhuorui, et al.
Published: (2024)
Fast and scalable Wasserstein-1 neural optimal transport solver for single-cell perturbation prediction
by: Chen, Yanshuo, et al.
Published: (2024)
by: Chen, Yanshuo, et al.
Published: (2024)
Multi-omic Causal Discovery using Genotypes and Gene Expression
by: Asiedu, Stephen, et al.
Published: (2025)
by: Asiedu, Stephen, et al.
Published: (2025)
scSiameseClu: A Siamese Clustering Framework for Interpreting single-cell RNA Sequencing Data
by: Xu, Ping, et al.
Published: (2025)
by: Xu, Ping, et al.
Published: (2025)
scRDiT: Generating single-cell RNA-seq data by diffusion transformers and accelerating sampling
by: Dong, Shengze, et al.
Published: (2024)
by: Dong, Shengze, et al.
Published: (2024)
UnPaSt: unsupervised patient stratification by biclustering of omics data
by: Hartung, Michael, et al.
Published: (2024)
by: Hartung, Michael, et al.
Published: (2024)
scI2CL: Effectively Integrating Single-cell Multi-omics by Intra- and Inter-omics Contrastive Learning
by: Liu, Wuchao, et al.
Published: (2025)
by: Liu, Wuchao, et al.
Published: (2025)
Machine and deep learning methods for predicting 3D genome organization
by: Wall, Brydon P. G., et al.
Published: (2024)
by: Wall, Brydon P. G., et al.
Published: (2024)
JojoSCL: Shrinkage Contrastive Learning for single-cell RNA sequence Clustering
by: Wang, Ziwen
Published: (2025)
by: Wang, Ziwen
Published: (2025)
Discovering Interpretable Biological Concepts in Single-cell RNA-seq Foundation Models
by: Claye, Charlotte, et al.
Published: (2025)
by: Claye, Charlotte, et al.
Published: (2025)
Genetic algorithms for multi-omic feature selection: a comparative study in cancer survival analysis
by: Cattelani, Luca, et al.
Published: (2026)
by: Cattelani, Luca, et al.
Published: (2026)
LaCoGSEA: Unsupervised deep learning for pathway analysis via latent correlation
by: Zheng, Zhiwei, et al.
Published: (2026)
by: Zheng, Zhiwei, et al.
Published: (2026)
Identifying multi-omics interactions for lung cancer drug targets discovery using Kernel Machine Regression
by: Ahmed, Md. Imtyaz, et al.
Published: (2025)
by: Ahmed, Md. Imtyaz, et al.
Published: (2025)
Machine Learning for analysis of Multiple Sclerosis cross-tissue bulk and single-cell transcriptomics data
by: Massafra, Francesco, et al.
Published: (2026)
by: Massafra, Francesco, et al.
Published: (2026)
Primer C-VAE: An interpretable deep learning primer design method to detect emerging virus variants
by: Wang, Hanyu, et al.
Published: (2025)
by: Wang, Hanyu, 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)
by: Kim, Jong Hyun, et al.
Published: (2024)
Uncovering smooth structures in single-cell data with PCS-guided neighbor embeddings
by: Ma, Rong, et al.
Published: (2025)
by: Ma, Rong, et al.
Published: (2025)
LOCO-EPI: Leave-one-chromosome-out (LOCO) as a benchmarking paradigm for deep learning based prediction of enhancer-promoter interactions
by: Tahir, Muhammad, et al.
Published: (2025)
by: Tahir, Muhammad, et al.
Published: (2025)
Hierarchical novel class discovery for single-cell transcriptomic profiles
by: Senoussi, Malek, et al.
Published: (2024)
by: Senoussi, Malek, et al.
Published: (2024)
Soft Graph Clustering for single-cell RNA Sequencing Data
by: Xu, Ping, et al.
Published: (2025)
by: Xu, Ping, et al.
Published: (2025)
Efficient Imputation for Patch-based Missing Single-cell Data via Cluster-regularized Optimal Transport
by: Liu, Yuyu, et al.
Published: (2026)
by: Liu, Yuyu, et al.
Published: (2026)
CAVACHON: a hierarchical variational autoencoder to integrate multi-modal single-cell data
by: Hsieh, Ping-Han, et al.
Published: (2024)
by: Hsieh, Ping-Han, et al.
Published: (2024)
Genome-Factory: A Library for Tuning, Deploying, and Interpreting Genomic Foundation Models
by: Wu, Weimin, et al.
Published: (2025)
by: Wu, Weimin, 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)
by: Umar, Muhammad, et al.
Published: (2024)
Uncertainty-aware t-distributed Stochastic Neighbor Embedding for Single-cell RNA-seq Data
by: Ma, Hui, et al.
Published: (2024)
by: Ma, Hui, et al.
Published: (2024)
CASPER: Cross-modal Alignment of Spatial and single-cell Profiles for Expression Recovery
by: Kumar, Amit, et al.
Published: (2025)
by: Kumar, Amit, et al.
Published: (2025)
Parameter-free representations outperform single-cell foundation models on downstream benchmarks
by: Souza, Huan, et al.
Published: (2026)
by: Souza, Huan, et al.
Published: (2026)
Bayesian Cox model with graph-structured variable selection priors for multi-omics biomarker identification
by: Hermansen, Tobias Østmo, et al.
Published: (2025)
by: Hermansen, Tobias Østmo, et al.
Published: (2025)
Disentangling Interpretable Factors with Supervised Independent Subspace Principal Component Analysis
by: Su, Jiayu, et al.
Published: (2024)
by: Su, Jiayu, et al.
Published: (2024)
scDiffusion: conditional generation of high-quality single-cell data using diffusion model
by: Luo, Erpai, et al.
Published: (2024)
by: Luo, Erpai, et al.
Published: (2024)
Central Dogma Transformer III: Interpretable AI Across DNA, RNA, and Protein
by: Ota, Nobuyuki
Published: (2026)
by: Ota, Nobuyuki
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)
by: Dutta, Pratik, et al.
Published: (2025)
scGHSOM: Hierarchical clustering and visualization of single-cell and CRISPR data using growing hierarchical SOM
by: Wen, Shang-Jung, et al.
Published: (2024)
by: Wen, Shang-Jung, et al.
Published: (2024)
Validating Interpretability in siRNA Efficacy Prediction: A Perturbation-Based, Dataset-Aware Protocol
by: Khodagholi, Zahra, et al.
Published: (2026)
by: Khodagholi, Zahra, et al.
Published: (2026)
On learning functions over biological sequence space: relating Gaussian process priors, regularization, and gauge fixing
by: Petti, Samantha, et al.
Published: (2025)
by: Petti, Samantha, et al.
Published: (2025)
DP-DCAN: Differentially Private Deep Contrastive Autoencoder Network for Single-cell Clustering
by: Li, Huifa, et al.
Published: (2023)
by: Li, Huifa, et al.
Published: (2023)
MOTGNN: Interpretable Graph Neural Networks for Multi-Omics Disease Classification
by: Yang, Tiantian, et al.
Published: (2025)
by: Yang, Tiantian, et al.
Published: (2025)
Similar Items
-
Machine learning applied to omics data
by: Calviño, Aida, et al.
Published: (2024) -
scMRDR: A scalable and flexible framework for unpaired single-cell multi-omics data integration
by: Sun, Jianle, et al.
Published: (2025) -
scMEDAL for the interpretable analysis of single-cell transcriptomics data with batch effect visualization using a deep mixed effects autoencoder
by: Andrade, Aixa X., et al.
Published: (2024) -
White-Box Diffusion Transformer for single-cell RNA-seq generation
by: Cui, Zhuorui, et al.
Published: (2024) -
Fast and scalable Wasserstein-1 neural optimal transport solver for single-cell perturbation prediction
by: Chen, Yanshuo, et al.
Published: (2024)