RNAMunin: A Deep Machine Learning Model for Non-coding RNA Discovery
Fuente:
arXiv
Saved in:
| Main Authors: | Lui, Lauren, Nielsen, Torben |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Multi-Modal Machine Learning for Population- and Subject-Specific lncRNA-Type 2 Diabetes Association Analysis
by: Siwach, Ashwani, et al.
Published: (2026)
by: Siwach, Ashwani, et al.
Published: (2026)
Rare Genomic Subtype Discovery from RNA-seq via Autoencoder Embeddings and Stability-Aware Clustering
by: Mezghiche, Alaa
Published: (2025)
by: Mezghiche, Alaa
Published: (2025)
Predicting Gene Disease Associations in Type 2 Diabetes Using Machine Learning on Single-Cell RNA-Seq Data
by: Toledo, Maria De La Luz Lomboy, et al.
Published: (2026)
by: Toledo, Maria De La Luz Lomboy, et al.
Published: (2026)
Assessing Concordance between RNA-Seq and NanoString Technologies in Ebola-Infected Nonhuman Primates Using Machine Learning
by: Rezapour, Mostafa, et al.
Published: (2024)
by: Rezapour, Mostafa, et al.
Published: (2024)
Global Ground Metric Learning with Applications to scRNA data
by: Kühn, Damin, et al.
Published: (2025)
by: Kühn, Damin, et al.
Published: (2025)
PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis
by: Wu, Yan, et al.
Published: (2024)
by: Wu, Yan, et al.
Published: (2024)
JojoSCL: Shrinkage Contrastive Learning for single-cell RNA sequence Clustering
by: Wang, Ziwen
Published: (2025)
by: Wang, Ziwen
Published: (2025)
CodonMoE: DNA Language Models for mRNA Analyses
by: Du, Shiyi, et al.
Published: (2025)
by: Du, Shiyi, et al.
Published: (2025)
HyperHELM: Hyperbolic Hierarchy Encoding for mRNA Language Modeling
by: van Spengler, Max, et al.
Published: (2025)
by: van Spengler, Max, et al.
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)
Robust Machine Learning for Regulatory Sequence Modeling under Biological and Technical Distribution Shifts
by: Yang, Yiyao
Published: (2026)
by: Yang, Yiyao
Published: (2026)
scMamba: A Pre-Trained Model for Single-Nucleus RNA Sequencing Analysis in Neurodegenerative Disorders
by: Oh, Gyutaek, et al.
Published: (2025)
by: Oh, Gyutaek, et al.
Published: (2025)
A Novel cVAE-Augmented Deep Learning Framework for Pan-Cancer RNA-Seq Classification
by: Polepalli, Vinil
Published: (2025)
by: Polepalli, Vinil
Published: (2025)
Modeling Temporal scRNA-seq Data with Latent Gaussian Process and Optimal Transport
by: Balik, Mehmet Yigit, et al.
Published: (2026)
by: Balik, Mehmet Yigit, et al.
Published: (2026)
A Comparative Analysis of Gene Expression Profiling by Statistical and Machine Learning Approaches
by: Bontonou, Myriam, et al.
Published: (2024)
by: Bontonou, Myriam, et al.
Published: (2024)
MLOmics: Cancer Multi-Omics Database for Machine Learning
by: Yang, Ziwei, et al.
Published: (2024)
by: Yang, Ziwei, et al.
Published: (2024)
DepoRanker: A Web Tool to predict Klebsiella Depolymerases using Machine Learning
by: Wright, George, et al.
Published: (2025)
by: Wright, George, et al.
Published: (2025)
Quantum AI for Cancer Diagnostic Biomarker Discovery
by: Saggi, Mandeep Kaur, et al.
Published: (2026)
by: Saggi, Mandeep Kaur, et al.
Published: (2026)
Contrastive Deep Learning for Variant Detection in Wastewater Genomic Sequencing
by: Chinda, Adele, et al.
Published: (2025)
by: Chinda, Adele, et al.
Published: (2025)
Machine Learning-Based Prediction of Key Genes Correlated to the Subretinal Lesion Severity in a Mouse Model of Age-Related Macular Degeneration
by: Yan, Kuan, et al.
Published: (2024)
by: Yan, Kuan, 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)
A Multi-Domain Multi-Task Approach for Feature Selection from Bulk RNA Datasets
by: Salta, Karim, et al.
Published: (2024)
by: Salta, Karim, et al.
Published: (2024)
A Large-Scale Comparative Analysis of Imputation Methods for Single-Cell RNA Sequencing Data
by: Iwashita, Yuichiro, et al.
Published: (2026)
by: Iwashita, Yuichiro, et al.
Published: (2026)
Whole-Genome Phenotype Prediction with Machine Learning: Open Problems in Bacterial Genomics
by: James, Tamsin, et al.
Published: (2025)
by: James, Tamsin, et al.
Published: (2025)
White-Box Diffusion Transformer for single-cell RNA-seq generation
by: Cui, Zhuorui, et al.
Published: (2024)
by: Cui, Zhuorui, 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)
Machine Learning-Based Analysis of Ebola Virus' Impact on Gene Expression in Nonhuman Primates
by: Rezapour, Mostafa, et al.
Published: (2024)
by: Rezapour, Mostafa, et al.
Published: (2024)
LoRA-BERT: a Natural Language Processing Model for Robust and Accurate Prediction of long non-coding RNAs
by: Jeon, Nicholas, et al.
Published: (2024)
by: Jeon, Nicholas, 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)
A Bioinformatic Approach Validated Utilizing Machine Learning Algorithms to Identify Relevant Biomarkers and Crucial Pathways in Gallbladder Cancer
by: Khatun, Rabea, et al.
Published: (2024)
by: Khatun, Rabea, 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)
by: Anaissi, Ali, et al.
Published: (2025)
Advancing Digital Precision Medicine for Chronic Fatigue Syndrome through Longitudinal Large-Scale Multi-Modal Biological Omics Modeling with Machine Learning and Artificial Intelligence
by: Xiong, Ruoyun
Published: (2025)
by: Xiong, Ruoyun
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)
Adversarial Domain Adaptation Enables Knowledge Transfer Across Heterogeneous RNA-Seq Datasets
by: Dradjat, Kevin, et al.
Published: (2026)
by: Dradjat, Kevin, et al.
Published: (2026)
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)
Bipartite Graph Attention-based Clustering for Large-scale scRNA-seq Data
by: Liang, Zhuomin, et al.
Published: (2026)
by: Liang, Zhuomin, et al.
Published: (2026)
Exploring the Potentials and Challenges of Using Large Language Models for the Analysis of Transcriptional Regulation of Long Non-coding RNAs
by: Wang, Wei, et al.
Published: (2024)
by: Wang, Wei, et al.
Published: (2024)
RNA-FrameFlow: Flow Matching for de novo 3D RNA Backbone Design
by: Anand, Rishabh, et al.
Published: (2024)
by: Anand, Rishabh, et al.
Published: (2024)
Discovery of Disease Relationships via Transcriptomic Signature Analysis Powered by Agentic AI
by: Chen, Ke, et al.
Published: (2025)
by: Chen, Ke, 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)
Similar Items
-
Multi-Modal Machine Learning for Population- and Subject-Specific lncRNA-Type 2 Diabetes Association Analysis
by: Siwach, Ashwani, et al.
Published: (2026) -
Rare Genomic Subtype Discovery from RNA-seq via Autoencoder Embeddings and Stability-Aware Clustering
by: Mezghiche, Alaa
Published: (2025) -
Predicting Gene Disease Associations in Type 2 Diabetes Using Machine Learning on Single-Cell RNA-Seq Data
by: Toledo, Maria De La Luz Lomboy, et al.
Published: (2026) -
Assessing Concordance between RNA-Seq and NanoString Technologies in Ebola-Infected Nonhuman Primates Using Machine Learning
by: Rezapour, Mostafa, et al.
Published: (2024) -
Global Ground Metric Learning with Applications to scRNA data
by: Kühn, Damin, et al.
Published: (2025)