ArticleCell reports methods2024
Fatecode enables cell fate regulator prediction using classification-supervised autoencoder perturbation.
Article in Cell reports methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Decoding cell fate: integrated experimental and computational analysis at the single-cell level.Bioinformatics (Oxford, England) · 2025Review
- Discovering governing equations of biological systems through representation learning and sparse model discovery.NAR genomics and bioinformatics · 2025Article
- scVAEDer: integrating deep diffusion models and variational autoencoders for single-cell transcriptomics analysis.Genome biology · 2025Article
- FateNet: an integration of dynamical systems and deep learning for cell fate prediction.Bioinformatics (Oxford, England) · 2024Article
- Adversarial training improves model interpretability in single-cell RNA-seq analysis.Bioinformatics advances · 2023Article
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4 authors.
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Abstract
Cell reprogramming, which guides the conversion between cell states, is a promising technology for tissue repair and regeneration, with the ultimate goal of accelerating recovery from diseases or injuries. To accomplish this, regulators must be identified and manipulated to control cell fate. We propose Fatecode, a computational method that predicts cell fate regulators based only on single-cell RNA sequencing (scRNA-seq) data. Fatecode learns a latent representation of the scRNA-seq data using a deep learning-based classification-supervised autoencoder and then performs in silico perturbation experiments on the latent representation to predict genes that, when perturbed, would alter the original cell type distribution to increase or decrease the population size of a cell type of interest. We assessed Fatecode's performance using simulations from a mechanistic gene-regulatory network model and scRNA-seq data mapping blood and brain development of different organisms. Our results suggest that Fatecode can detect known cell fate regulators from single-cell transcriptomics datasets.
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