Reverse engineering morphogenesis through Bayesian optimization of physics-based models is a research paper published in npj Systems Biology and Applications (2024). On theSindex it has a DataRank of 0. It has been cited 8 times.
Scored on demand from live citation data
Linked data & code
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
NIGMS NIH HHS
Grant: R35 GM124935
National Science Foundation
Grant: 1941596
CAREER: Uncertainty Quantification and Optimization with Hybrid Models for Molecular-to-Systems Engineering
National Science Foundation
Grant: 2120200
BII: Emergent Mechanisms in Biology of Robustness, Integration & Organization (EMBRIO)
National Science Foundation
Grant: 2225601
RECODE: Vascular Differentiation and Morphogenesis Controlled with Hybrid Memristors
National Science Foundation
Grant: 2029814
MODULUS: Integrative multiscale modeling and multimodal experiments to decode systems-level molecular mecanisms of epithelial systems
National Institutes of Health
Grant: 1R35GM124935-01
Regulation and function of multicellular calcium signaling in epithelial growth and regeneration
FWCI
2.04
Citation Percentile
0.9%
Citation Trend
Fields of Study
MeSH Terms
Keywords