The 2016 Taherian Fard Hopfield-landscape paper was not the first Hopfield-style attractor model of cell fate — Wang 2011, Lang 2014, and Maetschke & Ragan 2014 preceded it

Taherian Fard et al. (2016, npj Systems Biology and Applications 2:16001) is the vault's canonical instance of the Waddington landscape being formalized as a Hopfield-network energy surface (claim-hopfield-network-formalizes-waddington-epigenetic-landscape). It is not, however, the first paper to model biological cell-state landscapes with attractor dynamics. Its own text explicitly credits at least three predecessors that predate it by two to five years:

• Wang, Zhang, Xu & Wang (2011, PNAS 108:8257–8262) — "used ODEs and simulated data to construct a probabilistic 'pseudo-potential' energy landscape."
• Lang, Li, Collins & Mehta (2014, PLoS Comp. Biol. 10:e1003734; arXiv 1211.3133, first posted 2012) — "used binarized gene-expression data" to build an explicitly associative-memory cell-fate model.
• Maetschke & Ragan (2014, Bioinformatics 30:1273–1279) — "constructed an HN from static gene-expression data."

The 2016 paper's contribution is therefore one of explicitness and validation, not of first arrival: it states the landscape-as-Hopfield-network mapping most directly and tests it across 12 datasets, but the attractor-landscape framing of cell fate was already several years old. This refines the "first formalization" reading the existing note could invite. All three predecessors, and the 2016 paper itself, trace their lineage to Hopfield (1982/1984) and the spin-glass tradition rather than to Amari — see claim-no-amari-application-to-developmental-biology-found-pre-2016 and, for the underlying priority thread, claim-amari-1972-associative-memory-precedes-hopfield. The earlier Huang, Eichler, Bar-Yam & Ingber (2005, Phys. Rev. Lett. 94:128701) attractor-network cell-fate paper sits upstream of this cluster but was not independently checked in this pass.