About the Atlas

The Atlas of Computational Cell Reprogramming is a curated resource dedicated to the emerging field of computational cell fate engineering.

Every day, cells make decisions: whether to divide, differentiate, activate, repair tissue, respond to injury, or adopt entirely new identities. Over the past two decades, researchers have developed a growing collection of computational methods designed to understand and control these decisions. These approaches span induced pluripotency, directed differentiation, transdifferentiation, and phenotype reprogramming, drawing from systems biology, machine learning, network science, control theory, and increasingly artificial intelligence.

Despite rapid progress, the field remains fragmented. Computational methods are scattered across disciplines, evaluated using different assumptions, and often difficult to compare directly.

The Atlas was created to address this challenge. Our goal is to provide a continuously maintained map of computational approaches for cell reprogramming and cellular intervention design. Each method is systematically annotated, classified, and linked to its original publication. Beyond cataloging methods, the Atlas seeks to identify broader patterns across the field, including methodological trends, biological assumptions, validation strategies, reproducibility practices, and emerging technological directions.

The Atlas is built around a unifying perspective: many cell reprogramming methods can be viewed as attempts to solve a common intervention-design problem, namely finding molecular perturbations that move a cell from an initial state toward a desired target state. While biological modalities differ substantially, this shared computational perspective provides a framework for comparing methods that would otherwise appear unrelated. The formal treatment, explicitness classes (C0–C3), and modality definitions are on the framework page.

The initial release is built around the 57 peer-reviewed computational methods audited for the review Computational Cell Reprogramming: A Cross-Modality Framework for Cellular Intervention Design (2013–2026). The live index currently lists 57 methods and continues to grow as new peer-reviewed intervention-design methods are curated in.

The review introduced the cross-modality framework and reproducibility audit that structure this site at launch. The Atlas extends that work as a living resource: taxonomy placements, audit scores, and method entries are maintained here and updated between journal deposits. Full definitions, borderline cases, and the frozen audit matrix appear in the paper and Supporting Information; this site is the maintained catalog.

More broadly, we envision the Atlas as a community resource for researchers interested in understanding, predicting, and ultimately controlling cellular identity. Cell fate engineering is becoming increasingly central to regenerative medicine, disease modeling, synthetic biology, immunotherapy, and aging research. The Atlas focuses on computational approaches across all reprogramming modalities and application areas, including regenerative medicine, immunology, aging, and cancer reversion. By making the computational landscape more accessible and transparent, we hope to accelerate progress toward a future in which cellular states can be engineered with the same rigor that modern biology applies to genes and proteins.

The Atlas is a continuously updated and curated resource for computational cell reprogramming. New method nominations, corrections, reproducibility updates, and community feedback are welcomed through the Atlas curation process; see Curated Submissions.

Data & methodology — inclusion criteria, annotation schema, releases, and citation.

Data & methodology

Inclusion criteria

The Atlas indexes peer reviewed computational methods that, given a source cell distribution and a target identity or phenotype, explicitly predict an intervention designed to move the source toward the target. Upstream tools such as trajectory inference, optimal transport, and landscape reconstruction are enabling methods; they are not included here. This matches the inclusion criterion used for the 57 methods audited in the review.

Annotation schema

Each indexed method receives:

• One explicitness class placement (C0, C1, C2, or C3) with a written rationale tied to the role the intervention $u$ plays in the method's objective.
• One representation family (signature or state matching, regulatory network influence, or executable intervention model).
• One or more modalities (I, D, T, P), taken from the original publication.
• An audit of code availability, reproducibility (0 to 4), and FAIR4RS compliance (0 to 5), refreshed periodically.

Interactive audit summaries and the scoring rubric are on the reproducibility page; per-method scores appear on each method page.

Maintained index

The Atlas currently lists 57 methods and grows as new peer reviewed intervention design methods are added. Each release is tagged (v0.1.2 is current); the changelog records additions, replacements, and audit refreshes. Supporting Information S1 freezes the original 57 method audit at publication (2026-05-29). Headline reproducibility statistics in the review refer to that frozen set; methods added after publication are tagged on their method pages.

Every method page shows its last_audited date. Major releases are archived on Zenodo with a citable DOI (first deposit planned at publication); this site remains the live catalog between deposits.

Review article

Vera-Licona P. Computational Cell Reprogramming: A Cross-Modality Framework for Cellular Intervention Design. Under Revision, 2026.

The review introduces the four explicitness classes (C0, C1, C2, C3), the shared inverse design framing across reprogramming modalities, and the reproducibility audit summarized on the reproducibility page.

BibTeX: review article

@article{veralicona2026reprogramming,
  author  = {Vera-Licona, Paola},
  title   = {Computational Cell Reprogramming: A Cross-Modality Framework for Cellular Intervention Design},
  year    = {2026},
  note    = {Under Revision},
}

The full PDF, DOI, and supplementary tables will be linked here when the article is published. Reproduction materials will be archived on Zenodo and GitHub at acceptance.

Citation: this site

To cite the Atlas:

Vera-Licona, P. (2026). Atlas of Computational Cell Reprogramming, version v0.1.2.

A Zenodo DOI will be minted at publication of the review and added here.