More detailed growth models using inference.
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Updated
Apr 24, 2020 - Python
More detailed growth models using inference.
Study Fc antibody dynamics using a multivalent binding model
Dissecting systems serology with a tensor factorization
A binding-reaction model for the common gamma chain receptor cytokines.
This is to show oscillations in the number of cells in G1 and in G2 phase of cell cycle.
A Multivalent Binding Model for FcgRs
The structure is the message: preserving experimental context through tensor decomposition
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Trafficking model of FcRn to explain the effects of failed release at the cell surface.
Clusters phosphoproteomics data by sequence and abundance dynamics
R code to model and visualize sweat sodium loss across temperature and humidity conditions for passive vs. active interventions.
A multi-omic view of MRSA infection using tensor factorization
Inferring antibody species from systems serology with a mechanistic binding model.
A modeling perspective on cell selective ligands
Gas6 signaling model for TAM receptors
Reproducible analysis for between-visit cerebrovascular and cardiovascular responses during the cold pressor test
Code for modeling performed in Barney et al.
Decoding cytokine signaling networks in cancer patients
Exploring what valency does to IL-2.
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