ArticlePatterns (New York, N.Y.)2020
scTenifoldNet: A Machine Learning Workflow for Constructing and Comparing Transcriptome-wide Gene Regulatory Networks from Single-Cell Data.
Article in Patterns (New York, N.Y.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed.
- Single-cell gene regulatory networks characterize colonic stem and immune cell homeostasis iniScience · 2026Article
- NEAT1 Coordinates a PDLIM5-CACNA1C Regulatory Program Associated with a Potentially Arrhythmogenic Cardiomyocyte State in the Border Zone During Early Myocardial Infarction.International journal of molecular sciences · 2026Article
- Machine Learning-Derived Sarcopenia Signature Identifies High-Risk Molecular State in T2D Skeletal Muscle.Cell biochemistry and biophysics · 2026Article
- Fzd7 Restrains Pink1-Dependent Mitophagy in Suture Stem Cells to Maintain Cranial Suture Patency.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Integrative Single-Cell and Spatial Transcriptomic Analyses Link Arachidonic Acid Metabolic Reprogramming to Proneural-to-Mesenchymal State Transition in Glioblastoma.Biomedicines · 2026Article
- Article
- Cell-specific multi-target mechanisms of cotinine in cervical cancer oncogenesis and progression.Discover oncology · 2026Article
- Integrative analysis and experimental validation of dioxin-interacting genes reveal diagnostic and prognostic biomarkers in lung adenocarcinoma.Clinical and experimental medicine · 2026Article
- Deciphering Cell-Type-Specific Transcriptional Regulation in Tomato Leaves Through Ensemble Machine Learning and Single-Cell Transcriptomics.Plants (Basel, Switzerland) · 2026Article
- Cell-o1 : training LLMs to solve single-cell reasoning puzzles with reinforcement learning.Bioinformatics (Oxford, England) · 2026Article
- Digit regeneration in mice is stimulated by sequential treatment with FGF2 and BMP2.Nature communications · 2026Article
- Cuproptosis-associated genesFrontiers in immunology · 2026Article
- Integrated single-cell transcriptomic and machine-learning analyses identify a CD36-associated macrophage state in diabetic nephropathy.Frontiers in immunology · 2026Article
- Establishment and maintenance of NRT2.1 inter-individual variability in plants.PLoS genetics · 2025Article
- Single-cell transcriptomic analysis reveals the heterogeneity and functional characteristics of macrophage subpopulations in colon cancer.Discover oncology · 2025Article
- Maintenance of chronic neuroinflammation in multiple sclerosis via interferon signaling and CD8 T-cell-mediated cytotoxicity.Research square · 2025Article
- CONSTRUCTING GENE REGULATORY NETWORK USING CHATTERJEE'S RANK CORRELATION WITH SINGLE-CELL TRANSCRIPTOMIC DATA.bioRxiv : the preprint server for biology · 2025Article
- scPOEM: robust co-embedding of peaks and genes revealing peak-gene regulation.Bioinformatics (Oxford, England) · 2025Article
- Maintenance of chronic neuroinflammation in multiple sclerosis via interferon signaling and CD8 T cell-mediated cytotoxicity.bioRxiv : the preprint server for biology · 2025Article
- Gene function revealed at the moment of stochastic gene silencingCommunications biology · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We present scTenifoldNet-a machine learning workflow built upon principal-component regression, low-rank tensor approximation, and manifold alignment-for constructing and comparing single-cell gene regulatory networks (scGRNs) using data from single-cell RNA sequencing. scTenifoldNet reveals regulatory changes in gene expression between samples by comparing the constructed scGRNs. With real data, scTenifoldNet identifies specific gene expression programs associated with different biological processes, providing critical insights into the underlying mechanism of regulatory networks governing cellular transcriptional activities.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.