ArticleNature methods2024
Biophysical modeling with variational autoencoders for bimodal, single-cell RNA sequencing data.
Article in Nature methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Integrating zero-inflation correction and transcriptional kinetics for single-cell transcriptomic analysis.PLoS computational biology · 2026Article
- Using the simple telegraph model to decipher transcriptional burst regulation across genome-wide data.iScience · 2026Article
- Deciphering global transcriptional dynamics coordinated by gene-gene regulatory interactions using single-cell data.Molecular systems biology · 2026Article
- Integrating host-microbiome multi-omics with machine learning: methods, benchmarks, and translational applications.Science China. Life sciences · 2026Review
- Complementary ROC-Derived Indices for Screening Improper Expression Profiles in RNA-Seq Differential Expression Analysis.Balkan medical journal · 2026Article
- Highly Constrained Kinetic Models for Single-Cell Gene Expression Analysis.bioRxiv : the preprint server for biology · 2026Article
- DeepMice: a novel protein-ligand molecular docking model based on multilevel mapping modules.Molecular diversity · 2026Article
- Article
- AI-powered programmable virtual humans toward human physiologically-based drug discovery.Drug discovery today · 2025Review
- Monod: model-based discovery and integration through fitting stochastic transcriptional dynamics to single-cell sequencing data.Nature methods · 2025Article
- Linear scaling reveals low-dimensional structure in observable microbial dynamics.bioRxiv : the preprint server for biology · 2025Article
- kallisto, bustools and kb-python for quantifying bulk, single-cell and single-nucleus RNA-seq.Nature protocols · 2025Review
- Anti-correlation of LacI association and dissociation rates observed in living cells.Nature communications · 2025Article
- Accurate quantification of nascent and mature RNAs from single-cell and single-nucleus RNA-seq.Nucleic acids research · 2025Article
- Exploring transcription modalities from bimodal, single-cell RNA sequencing data.NAR genomics and bioinformatics · 2024Article
- Spectral neural approximations for models of transcriptional dynamics.Biophysical journal · 2024Article
- Stochastic Modeling of Biophysical Responses to Perturbation.bioRxiv : the preprint server for biology · 2024Article
- kallisto, bustools, and kb-python for quantifying bulk, single-cell, and single-nucleus RNA-seq.bioRxiv : the preprint server for biology · 2024Article
- Review
- Studying stochastic systems biology of the cell with single-cell genomics data.bioRxiv : the preprint server for biology · 2023Article
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5 authors.
Funding
Abstract
Here we present biVI, which combines the variational autoencoder framework of scVI with biophysical models describing the transcription and splicing kinetics of RNA molecules. We demonstrate on simulated and experimental single-cell RNA sequencing data that biVI retains the variational autoencoder's ability to capture cell type structure in a low-dimensional space while further enabling genome-wide exploration of the biophysical mechanisms, such as system burst sizes and degradation rates, that underlie observations.
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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.