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Atlas of Computational Cell Reprogramming

← Methods

L1 · Network-informed inverse design heuristics T

Mogrify

Rackham OJ, Firas J, Fang H, Oates ME, Holmes ML, Knaupp AS, Suzuki H, Nefzger CM, Daub CO, Shin JW, Petretto E, Forrest AR, Hayashizaki Y, Polo JM, Gough J

2016 · Nature genetics

Transdifferentiation, the process of converting from one cell type to another without going through a pluripotent state, has great promise for regenerative medicine.

Abstract

From the original paper, Nature genetics · PubMed

Transdifferentiation, the process of converting from one cell type to another without going through a pluripotent state, has great promise for regenerative medicine. The identification of key transcription factors for reprogramming is currently limited by the cost of exhaustive experimental testing of plausible sets of factors, an approach that is inefficient and unscalable. Here we present a predictive system (Mogrify) that combines gene expression data with regulatory network information to predict the reprogramming factors necessary to induce cell conversion. We have applied Mogrify to 173 human cell types and 134 tissues, defining an atlas of cellular reprogramming. Mogrify correctly predicts the transcription factors used in known transdifferentiations. Furthermore, we validated two new transdifferentiations predicted by Mogrify. We provide a practical and efficient mechanism for systematically implementing novel cell conversions, facilitating the generalization of reprogramming of human cells. Predictions are made available to help rapidly further the field of cell conversion.

Summary

Editorial summary pending review by the maintainer. The paper's own abstract appears above; the Atlas summary in the maintainer's voice will explain how Mogrify relates to the cross-modality inverse-design framework of the review.

Why this level

Level 1 because the method scores candidate interventions through static regulatory-network influence relative to a target GRN, without computing the post-intervention state P^S,u\hat P_{S,u}. Representation family is regulatory-network influence. Cited in §3.2 of the review. Editorial rationale pending review by the maintainer.

Classification

Level
L1
Representation
Regulatory-network influence
Modalities
T
Intervention
Transcription factors
Framework
Static network analysis

Software

Code
www.mogrify.net/
Web tool
www.mogrify.net/
Reproducibility
Not audited
FAIR4RS
—

Last audited 2026-05-24

Citation

Rackham OJ et al. (2016). A predictive computational framework for direct reprogramming between human cell types., Nature genetics.

DOI: 10.1038/ng.3487

PMID: 26780608

BibTeX 
@article{mogrify2016,
  title  = {A predictive computational framework for direct reprogramming between human cell types.},
  author = {Rackham OJ et al.},
  year   = {2016},
  journal = {Nature genetics},
  pmid = {26780608},
  doi  = {10.1038/ng.3487}
}