meyer-lab/DrugResponseModel.jl

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Created over 5 years ago
Updated over 1 year ago

meyer-lab/DrugResponseModel.jl

meyer-lab

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This is to show oscillations in the number of cells in G1 and in G2 phase of cell cycle.

tHMM

A general Python framework for using hidden Markov models on binary trees or cell lineage trees.

ps-growth-model

More detailed growth models using inference.

mechanismEncoder

Developing patient-specific phosphoproteomic models using mechanistic autoencoders

tensorpack

A collection of tensor methods from the Meyer lab.

systemsSerology

Dissecting systems serology with a tensor factorization

FcRegression.jl

Study Fc antibody dynamics using a multivalent binding model

scCP

PARAFAC2 for modeling multi-sample single-cell RNAseq.

Jupyter Notebook

IL4-model

Jupyter Notebook

tensor-impute

Explore imputation methods for tensor data

gc-cytokines

A binding-reaction model for the common gamma chain receptor cytokines.

FcRn-trafficking

Trafficking model of FcRn to explain the effects of failed release at the cell surface.

gcSolver

C++ solver for the gamma chain cytokines

FcgR-binding

A Multivalent Binding Model for FcgRs

DDMC

Clusters phosphoproteomics data based on a combination of the sequence information and abundance changes over conditions.

analytic-Pf2

Attempting analytical PARAFAC solving for more accurate PARAFAC2 fitting.

asmlab.org

Meyer lab website