← Cellular intervention design framework

Four reprogramming modalities

Pluripotency induction, directed differentiation, transdifferentiation, and phenotype reprogramming are not four unrelated computational questions. They are four constraint regimes on the same intervention design syntax: each modality fixes how source state, target state, admissible interventions, and feasibility penalties enter the template. Select a modality for its definition and indexed methods.

Reprogramming modality

Phenotype reprogramming

This page records Phenotype reprogramming and the 31 indexed methods for this reprogramming modality. Search the corpus below; the modality definition follows.

Definition

A constrained state shift within or near a lineage basin: diseased→healthy, exhausted→effector, aged→rejuvenated, resistant→sensitive.

Find a method for phenotype

31 methods

Matches method names, authors, paper titles, journals, PMIDs/DOIs, explicitness class, modalities, frameworks, and audit scores.

Cornelius et al.

Cornelius SP et al. · 2013 · Nature communications

The control of complex networks is of paramount importance in areas as diverse as ecosystem management, emergency response and cell reprogramming.

No code Repro N/A FAIR N/A

DEPCs (Crespo et al. 2013)

Crespo I et al. · 2013 · BMC systems biology

BACKGROUND: Cellular differentiation and reprogramming are processes that are carefully orchestrated by the activation and repression of specific sets of genes.

I D T P

No code Repro N/A FAIR N/A

FVS (Mochizuki et al.)

Mochizuki A et al. · 2013 · Journal of theoretical biology

Modern biology provides many networks describing regulations between many species of molecules.

D P

No code Repro N/A FAIR N/A

Stable Motifs

Zañudo JG et al. · 2015 · PLoS computational biology

Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell's fate, such as disease therapeutics and stem cell reprogramming.

D P

Code Repro 4/4 FAIR 0/5

Murrugarra et al.

Murrugarra D et al. · 2016 · BMC systems biology

BACKGROUND: Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a…

Code Repro 2/4 FAIR 0/5

Del Vecchio et al.

Del Vecchio D et al. · 2017 · Cell systems

To artificially reprogram cell fate, experimentalists manipulate the gene regulatory networks (GRNs) that maintain a cell's phenotype.

I D P

No code Repro N/A FAIR N/A

Zañudo et al. (FVS control)

Zañudo JGT et al. · 2017 · Proceedings of the National Academy of Sciences of the United States of America

What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that…

D P

Code Repro 4/4 FAIR 0/5

LDOI

Yang G et al. · 2018 · Frontiers in physiology

Dynamical models of biomolecular networks are successfully used to understand the mechanisms underlying complex diseases and to design therapeutic strategies.

Code Repro 4/4 FAIR 0/5

OncoTreat

Alvarez et al. · 2018 · Cancer Discovery

Classical Level 2 proxy method. Estimates master-regulator activity with VIPER and ranks compounds by their ability to reverse that activity profile against perturbation atlases.

Code Repro 3/4 FAIR 3/5

PCK (Phenotype Control Kernel)

Choo SM et al. · 2018 · BMC systems biology

BACKGROUND: Controlling complex molecular regulatory networks is getting a growing attention as it can provide a systematic way of driving any cellular state to a desired cell phenotypic state.

No code Repro N/A FAIR N/A

BRC (Boundary-Reaching Control)

Choo SM et al. · 2019 · Scientific reports

A cell phenotype can be represented by an attractor state of the underlying molecular regulatory network, to which other network states eventually converge.

No code Repro N/A FAIR N/A

Aguilar et al.

Aguilar B et al. · 2020 · Letters in biomathematics

One of the ultimate goals in systems biology is to develop control strategies to find efficient medical treatments.

Code Repro 3/4 FAIR 0/5

BoolIFFNN

Choo SM et al. · 2020 · Frontiers in physiology

The molecular regulatory network (MRN) within a cell determines cellular states and transitions between them.

D P

No code Repro N/A FAIR N/A

OCSANA+

Marazzi L et al. · 2020 · Bioinformatics (Oxford, England)

SUMMARY: OCSANA+ is a Cytoscape app for identifying nodes to drive the system toward a desired long-term behavior, prioritizing combinations of interventions in large-scale complex networks, and estimating the effects…

D P

Code Repro 4/4 FAIR 2/5

Sordo et al.

Sordo Vieira L et al. · 2020 · Bulletin of mathematical biology

Many problems in biology and medicine have a control component.

Code Repro 3/4 FAIR 0/5

CABEAN

Su C et al. · 2021 · Bioinformatics (Oxford, England)

SUMMARY: Direct cell reprogramming, also called transdifferentiation, has great potential for tissue engineering and regenerative medicine.

T P

Code Repro 4/4 FAIR 1/5

cSTAR

Rukhlenko OS et al. · 2022 · Nature

Understanding cell state transitions and purposefully controlling them is a longstanding challenge in biology.

Code Repro 1/4 FAIR 0/5

NETISCE

Marazzi L et al. · 2022 · NPJ systems biology and applications

The search for effective therapeutic targets in fields like regenerative medicine and cancer research has generated interest in cell fate reprogramming.

D P

Code Repro 4/4 FAIR 3/5

CellOracle

Kamimoto K et al. · 2023 · Nature

Cell identity is governed by the complex regulation of gene expression, represented as gene-regulatory networks1.

D P

Code Repro 4/4 FAIR 3/5

DCGS

An S et al. · 2023 · Bioinformatics (Oxford, England)

MOTIVATION: Cellular behavior is determined by complex non-linear interactions between numerous intracellular molecules that are often represented by Boolean network models.

Code Repro 4/4 FAIR 1/5

SiPER

Zheng M et al. · 2023 · Stem cell reports

Cellular conversion can be induced by perturbing a handful of key transcription factors (TFs).

I D T P

Code Repro 4/4 FAIR 1/5

CAESAR

Kim N et al. · 2024 · Briefings in bioinformatics

The tendency for cell fate to be robust to most perturbations, yet sensitive to certain perturbations raises intriguing questions about the existence of a key path within the underlying molecular network that…

D T P

Code Repro 3/4 FAIR 0/5

Transfer Learning (Wytock & Motter)

Wytock TP et al. · 2024 · Proceedings of the National Academy of Sciences of the United States of America

Recent developments in synthetic biology, next-generation sequencing, and machine learning provide an unprecedented opportunity to rationally design new disease treatments based on measured responses to gene…

I T P

Code Repro 4/4 FAIR 1/5

CANDiT

Sinha S et al. · 2025 · Cell reports. Medicine

Reactivating lineage commitment to differentiate, and hence eliminate, cancer stem cells (CSCs) remains a therapeutic challenge.

Code Repro 2/4 FAIR 0/5

DrugReflector

DeMeo B et al. · 2025 · Science (New York, N.Y.)

Phenotypic drug screening remains constrained by the vastness of chemical space and the technical challenges of scaling experimental workflows.

D P

Code Repro 4/4 FAIR 3/5

pbn-STAC

pbn-STAC · 2025

Method indexed in the Atlas. Editorial one-liner pending review.

Code Repro 4/4 FAIR 1/5

PDGrapher

Gonzalez et al. · 2025 · Nature Biotechnology

Recent Level 3 frontier. Graph neural network that predicts transcriptional responses to candidate interventions and ranks perturbations by predicted reconstruction of a target state.

Code Repro 4/4 FAIR 4/5

REVERT

Shin D et al. · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany)

A cell fate change such as tumorigenesis incurs critical transition.

Code Repro 4/4 FAIR 0/5

REVIVE

Jung S et al. · 2025 · Aging

Great efforts have been devoted to discovering rejuvenation strategies that counteract age-related functional decline and improve cellular functions in humans.

Code Repro 2/4 FAIR 1/5

TRAPT

Zhang G et al. · 2025 · Nature communications

Epigenomics-first deep learning maps a query gene set to ranked upstream TR activity using large ChIP/ATAC/H3K27ac compendia.

Code Repro 4/4 FAIR 4/5

Atlas-guided

Chung HK et al. · 2026 · Nature

CD8+ T cells differentiate into diverse states that shape immune outcomes in cancer and chronic infection1-4.

Code Repro 4/4 FAIR 1/5