ReviewJournal of the Royal Society, Interface2014
A linear-encoding model explains the variability of the target morphology in regeneration.
Review in Journal of the Royal Society, Interface, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
47 citing papers in PubMed, 100 citations in OpenAlex.
- Transcriptional Profiling of Planarian Regeneration Habituating to Physiological Stressor Reveals Individual and Collective Dynamics.bioRxiv : the preprint server for biology · 2026Article
- Mind Everywhere: A Framework for Conceptualizing Goal-Directedness in Biology and Other Domains-Part Two.Biological theory · 2026Article
- Aging as a Loss of Goal-Directedness: An Evolutionary Simulation and Analysis Unifying Regeneration with Anatomical Rejuvenation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Harnessing the analog computing power of regulatory networks with the Regulatory Network Machine.iScience · 2025Article
- The Multiscale Wisdom of the Body: Collective Intelligence as a Tractable Interface for Next-Generation Biomedicine.BioEssays : news and reviews in molecular, cellular and developmental biology · 2025Review
- AI-driven automated discovery tools reveal diverse behavioral competencies of biological networks.eLife · 2025Article
- Open problems in synthetic multicellularity.NPJ systems biology and applications · 2024Article
- Stress sharing as cognitive glue for collective intelligences: A computational model of stress as a coordinator for morphogenesis.Biochemical and biophysical research communications · 2024Article
- Evolutionary Implications of Self-Assembling Cybernetic Materials with Collective Problem-Solving Intelligence at Multiple Scales.Entropy (Basel, Switzerland) · 2024Article
- Bioelectric networks: the cognitive glue enabling evolutionary scaling from physiology to mind.Animal cognition · 2023Review
- Future medicine: from molecular pathways to the collective intelligence of the body.Trends in molecular medicine · 2023Review
- Cellular signaling pathways as plastic, proto-cognitive systems: Implications for biomedicine.Patterns (New York, N.Y.) · 2023Review
- Darwin's agential materials: evolutionary implications of multiscale competency in developmental biology.Cellular and molecular life sciences : CMLS · 2023Review
- The nonlinearity of regulation in biological networks.NPJ systems biology and applications · 2023Article
- Cellular Competency during Development Alters Evolutionary Dynamics in an Artificial Embryogeny Model.Entropy (Basel, Switzerland) · 2023Article
- Learning in Transcriptional Network Models: Computational Discovery of Pathway-Level Memory and Effective Interventions.International journal of molecular sciences · 2022Article
- Competency in Navigating Arbitrary Spaces as an Invariant for Analyzing Cognition in Diverse Embodiments.Entropy (Basel, Switzerland) · 2022Article
- Minimal Developmental Computation: A Causal Network Approach to Understand Morphogenetic Pattern Formation.Entropy (Basel, Switzerland) · 2022Article
- Active inference, morphogenesis, and computational psychiatry.Frontiers in computational neuroscience · 2022Article
- Computational Systems Biology of Morphogenesis.Methods in molecular biology (Clifton, N.J.) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A fundamental assumption of today's molecular genetics paradigm is that complex morphology emerges from the combined activity of low-level processes involving proteins and nucleic acids. An inherent characteristic of such nonlinear encodings is the difficulty of creating the genetic and epigenetic information that will produce a given self-assembling complex morphology. This 'inverse problem' is vital not only for understanding the evolution, development and regeneration of bodyplans, but also for synthetic biology efforts that seek to engineer biological shapes. Importantly, the regenerative mechanisms in deer antlers, planarian worms and fiddler crabs can solve an inverse problem: their target morphology can be altered specifically and stably by injuries in particular locations. Here, we discuss the class of models that use pre-specified morphological goal states and propose the existence of a linear encoding of the target morphology, making the inverse problem easy for these organisms to solve. Indeed, many model organisms such as Drosophila, hydra and Xenopus also develop according to nonlinear encodings producing linear encodings of their final morphologies. We propose the development of testable models of regeneration regulation that combine emergence with a top-down specification of shape by linear encodings of target morphology, driving transformative applications in biomedicine and synthetic bioengineering.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.