Imagen de Portada

Random Matrix Theory-guided sparse PCA for single-cell RNA-seq data

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Chardès, Victor
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning Biological Physics Quantitative Methods
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Inferring biological processes with intrinsic noise from cross-sectional data
por: Maddu, Suryanarayana, et al.
Publicado: (2024)

Inferring stochastic dynamics with growth from cross-sectional data
por: Zhang, Stephen, et al.
Publicado: (2025)

Integrating Dynamical Systems Modeling with Spatiotemporal scRNA-seq Data Analysis
por: Zhang, Zhenyi, et al.
Publicado: (2025)

The Dissipation Theory of Aging: A Quantitative Analysis Using a Cellular Aging Map
por: Khodaee, Farhan, et al.
Publicado: (2025)

Inference of dynamical gene regulatory networks from single-cell data with physics informed neural networks
por: Mircea, Maria, et al.
Publicado: (2024)

Machine learning approaches for interpretable antibody property prediction using structural data
por: Michalewicz, Kevin, et al.
Publicado: (2025)

adabmDCA 2.0 -- a flexible but easy-to-use package for Direct Coupling Analysis
por: Rosset, Lorenzo, et al.
Publicado: (2025)

Protein generation with embedding learning for motif diversification
por: Michalewicz, Kevin, et al.
Publicado: (2025)

Enhancing Swarms Durability to Threats via Graph Signal Processing and GNN-based Generative Modeling
por: Karin, Jonathan, et al.
Publicado: (2025)

Mass Balance Approximation of Unfolding Improves Potential-Like Methods for Protein Stability Predictions
por: Rossi, Ivan, et al.
Publicado: (2025)

Loop-Diffusion: an equivariant diffusion model for designing and scoring protein loops
por: Borisiak, Kevin, et al.
Publicado: (2024)

Donor-Aware scRNA-seq Benchmarks for IBD Classification
por: Muhire, Jonathan
Publicado: (2026)

Explainable Deep Learning Framework for SERS Bio-quantification
por: Zaki, Jihan K., et al.
Publicado: (2024)

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

Piezoelectricity and flexoelectricity in biological cells: The role of cell structure and organelles
por: Venkateshwarlu, Akepogu, et al.
Publicado: (2024)

Predicting Soil Macronutrient Levels: A Machine Learning Approach Models Trained on pH, Conductivity, and Average Power of Acid-Base Solutions
por: Kumar, Mridul, et al.
Publicado: (2025)

Live-cell imaging powered by computation
por: Shroff, Hari, et al.
Publicado: (2024)

Randomness with constraints: constructing minimal models for high-dimensional biology
por: Nemenman, Ilya, et al.
Publicado: (2025)

Quantifying cell cycle regulation by tissue crowding
por: Falcó, Carles, et al.
Publicado: (2024)

Nonlinear memory in cell division dynamics across species
por: Zhang, Shijie, et al.
Publicado: (2024)

ConfRover: Simultaneous Modeling of Protein Conformation and Dynamics via Autoregression
por: Shen, Yuning, et al.
Publicado: (2025)

Learning noisy tissue dynamics across time scales
por: Han, Ming, et al.
Publicado: (2025)

Global graph features unveiled by unsupervised geometric deep learning
por: Granfors, Mirja, et al.
Publicado: (2025)

Scalable Spatio-Temporal SE(3) Diffusion for Long-Horizon Protein Dynamics
por: Shoghi, Nima, et al.
Publicado: (2026)

Toward more accurate and generalizable brain deformation estimators for traumatic brain injury detection with unsupervised domain adaptation
por: Zhan, Xianghao, et al.
Publicado: (2023)

Decoding Neuronal Networks: A Reservoir Computing Approach for Predicting Connectivity and Functionality
por: Auslender, Ilya, et al.
Publicado: (2023)

Universal Cold RNA Phase Transitions
por: Rissone, Paolo, et al.
Publicado: (2024)

Feature selection revisited in the single-cell era
por: Yang, Pengyi, et al.
Publicado: (2021)

bioSBM: a random graph model to integrate epigenomic data in chromatin structure prediction
por: Zhang, Alex Chen Yi, et al.
Publicado: (2024)

Magnetic resonance imaging of mean cell size in human breast tumors
por: Xu, Junzhong, et al.
Publicado: (2019)

Computational predictions of nutrient precipitation for intensified cell 1 culture media via amino acid solution thermodynamics
por: Reddy, Jayanth Venkatarama, et al.
Publicado: (2025)

Enhanced Spatial Clustering of Single-Molecule Localizations with Graph Neural Networks
por: Pineda, Jesús, et al.
Publicado: (2024)

Extreme Learning Machine for the Characterization of Anomalous Diffusion from Single Trajectories (AnDi-ELM)
por: Manzo, Carlo
Publicado: (2021)

Reconstruction of three-dimensional shapes of normal and disease-related erythrocytes from partial observations using multi-fidelity neural networks
por: Wen, Haizhou, et al.
Publicado: (2025)

Better Models, Faster Training: Sigmoid Attention for single-cell Foundation Models
por: Sadashivaiah, Vijay, et al.
Publicado: (2026)

Maximum likelihood estimates of diffusion coefficients from single-particle tracking experiments
por: Bullerjahn, Jakob Tómas, et al.
Publicado: (2020)

scDiffusion: conditional generation of high-quality single-cell data using diffusion model
por: Luo, Erpai, et al.
Publicado: (2024)

Randomness in appendage coordination facilitates strenuous ground self-righting
por: Xuan, Qihan, et al.
Publicado: (2020)

Impact of phylogeny on structural contact inference from protein sequence data
por: Dietler, Nicola, et al.
Publicado: (2022)

A microsimulation model of behaviour change calibrated to reversal learning data
por: Reyes, Roben Delos, et al.
Publicado: (2024)