Develops and tests algorithms adapting inverse Henderson problem solvers to parameterize multi-component interaction potentials from XL-MS data in homogeneous and three-phase systems.
Sadeghi \ and\ author F
2 Pith papers cite this work. Polarity classification is still indexing.
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years
2026 2verdicts
UNVERDICTED 2representative citing papers
A data-driven framework reduces particle-based transfer operators via concentration projection, geometric manifold, and finite-state discretization to reproduce clustering transitions and metastable states from simulation data.
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Methods for Inferring Interaction Potentials from Cross-Linking Mass Spectrometry Data
Develops and tests algorithms adapting inverse Henderson problem solvers to parameterize multi-component interaction potentials from XL-MS data in homogeneous and three-phase systems.
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Data-driven Reduction of Transfer Operators for Particle Clustering Dynamics
A data-driven framework reduces particle-based transfer operators via concentration projection, geometric manifold, and finite-state discretization to reproduce clustering transitions and metastable states from simulation data.