Cover Image

VAE-MS: An Asymmetric Variational Autoencoder for Mutational Signature Extraction

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Egendal, Ida, Brøndum, Rasmus Froberg, Woodcock, Dan J, Yau, Christopher, Bøgsted, Martin
Format:	Preprint
Published:	2026
Subjects:	Applications Machine Learning Genomics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On the Relation Between Autoencoders and Non-negative Matrix Factorization, and Their Application for Mutational Signature Extraction
by: Egendal, Ida, et al.
Published: (2024)

Disentangling shared and private latent factors in multimodal Variational Autoencoders
by: Märtens, Kaspar, et al.
Published: (2024)

Multi-View Variational Autoencoder for Missing Value Imputation in Untargeted Metabolomics
by: Zhao, Chen, et al.
Published: (2023)

Combining Bayesian and Frequentist Inference for Laboratory-Specific Performance Guarantees in Copy Number Variation Detection
by: Talbot, Austin, et al.
Published: (2026)

HR-VILAGE-3K3M: A Human Respiratory Viral Immunization Longitudinal Gene Expression Dataset for Systems Immunity
by: Sun, Xuejun, et al.
Published: (2025)

Longitudinal prediction of DNA methylation to forecast epigenetic outcomes
by: Leroy, Arthur, et al.
Published: (2023)

Scalable Amortized GPLVMs for Single Cell Transcriptomics Data
by: Zhao, Sarah, et al.
Published: (2024)

Predicting loss-of-function impact of genetic mutations: a machine learning approach
by: Kaur, Arshmeet, et al.
Published: (2024)

TransST: Transfer Learning Embedded Spatial Factor Modeling of Spatial Transcriptomics Data
by: Liu, Shuo Shuo, et al.
Published: (2025)

Uncovering smooth structures in single-cell data with PCS-guided neighbor embeddings
by: Ma, Rong, et al.
Published: (2025)

Machine learning applied to omics data
by: Calviño, Aida, et al.
Published: (2024)

Bayesian Cox model with graph-structured variable selection priors for multi-omics biomarker identification
by: Hermansen, Tobias Østmo, et al.
Published: (2025)

Assumption-Lean Post-Integrated Inference with Surrogate Control Outcomes
by: Du, Jin-Hong, et al.
Published: (2024)

Mixed Models with Multiple Instance Learning
by: Engelmann, Jan P., et al.
Published: (2023)

Optimizing Prognostic Biomarker Discovery in Pancreatic Cancer Through Hybrid Ensemble Feature Selection and Multi-Omics Data
by: Zobolas, John, et al.
Published: (2025)

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

Wave-LSTM: Multi-scale analysis of somatic whole genome copy number profiles
by: Gadd, Charles, et al.
Published: (2024)

High-dimensional Many-to-many-to-many Mediation Analysis
by: Nguyen, Tien Dat, et al.
Published: (2026)

Penalized Principal Component Analysis Using Smoothing
by: Hurwitz, Rebecca M., et al.
Published: (2023)

Capturing Extreme Events in Turbulence using an Extreme Variational Autoencoder (xVAE)
by: Zhang, Likun, et al.
Published: (2025)

Primer C-VAE: An interpretable deep learning primer design method to detect emerging virus variants
by: Wang, Hanyu, et al.
Published: (2025)

Incorporating LLM Embeddings for Variation Across the Human Genome
by: Niu, Hongqian, et al.
Published: (2025)

Neural Population Decoding and Imbalanced Multi-Omic Datasets For Cancer Subtype Diagnosis
by: Kent, Charles Theodore, et al.
Published: (2024)

MitoFREQ: A Novel Approach for Mitogenome Frequency Estimation from Top-level Haplogroups and Single Nucleotide Variants
by: Andersen, Mikkel Meyer, et al.
Published: (2026)

Tutorial on survival modeling with applications to omics data
by: Zhao, Zhi, et al.
Published: (2023)

Effect Size-Driven Pathway Meta-Analysis for Gene Expression Data
by: Villatoro-García, Juan Antonio, et al.
Published: (2025)

Shotgun DNA sequencing for human identification: Dynamic SNP selection and likelihood ratio calculations accounting for errors
by: Andersen, Mikkel Meyer, et al.
Published: (2024)

BioKlustering: a web app for semi-supervised learning of maximally imbalanced genomic data
by: Ozminkowski, Samuel, et al.
Published: (2022)

Detecting and Correcting Sample-by-Sample Scale Distortion in RNA Sequencing Data
by: Thron, Christopher, et al.
Published: (2026)

Is your data alignable? Principled and interpretable alignability testing and integration of single-cell data
by: Ma, Rong, et al.
Published: (2023)

LSTM Autoencoder-based Deep Neural Networks for Barley Genotype-to-Phenotype Prediction
by: Wang, Guanjin, et al.
Published: (2024)

Fine-tuning Protein Language Models with Deep Mutational Scanning improves Variant Effect Prediction
by: Lafita, Aleix, et al.
Published: (2024)

Discovery of Disease Relationships via Transcriptomic Signature Analysis Powered by Agentic AI
by: Chen, Ke, et al.
Published: (2025)

Causal Discovery on Dependent Mixed Data with Applications to Gene Regulatory Network Inference
by: Chen, Alex, et al.
Published: (2026)

CoMMiT: Co-informed inference of microbiome-metabolome interactions via transfer learning
by: Li, Leiyue, et al.
Published: (2025)

Controlling the joint local false discovery rate is more powerful than meta-analysis methods in joint analysis of summary statistics from multiple genome-wide association studies
by: Jiang, Wei, et al.
Published: (2016)

Second-order group knockoffs with applications to GWAS
by: Chu, Benjamin B, et al.
Published: (2023)

Estimating Reproducibility in Genome-Wide Association Studies
by: Jiang, Wei, et al.
Published: (2015)

Nullstrap-DE: A General Framework for Calibrating FDR and Preserving Power in DE Methods, with Applications to DESeq2 and edgeR
by: Jiang, Chenxin, et al.
Published: (2025)

Robust Genomic Prediction and Heritability Estimation using Density Power Divergence
by: Chowdhury, Upama Paul, et al.
Published: (2024)