Abstract MemRBC is a result of open science research. It demonstrates the use of hi-level apps in a light-weight object oriented approach in R, keeping metadata and lineage recorded systematically for reproducibility and self-documentation. Many studies have been published on the modeling of the transformation of stomatocyte to discocyte to echinocyte shape of red blood cells. However, not many details and result data of the different numerical simulation approaches have been given, hindering a systematic comparison and the selection of an optimal approach. With the present work, the software package MembraneRBC is published that facilitates a couple of numerical approaches to be explored and combined in modeling workflows. Results of exemplary applications are given to explain some features of the implementations and their effects in modeling practice of RBC shape transformation. A spectral membrane shape model implementation is adapted here for RBC. It is based on the Spontaneous Curvature Model (SCM), extended by an area difference term, but no preferred area difference, such that membrane asymmetry is completely under control of the spontaneous curvature parameter C_0. Furthermore, the shear-elastic network (SEN) implementation is included, allowing for modeling spicule formation and redistribution. Implemented methods are: constraint Newton-based energy minimization, Monte Carlo dynamics, Newtonian dynamics, augmented Lagrangian minimization. The major advantage of the used object-oriented multi-method software package is the seamless data exchange between different approaches, with restart and protocol facility. This enables the combination of several modeling sub-tasks, like initial constraint energy minimization, dynamics simulation, and stability analyses in a few lines of code. Previously published related work Frickenhaus, S., & Woelper, C. (2024). MembraneR - a membrane shape modeling environment in R. Zenodo. https://doi.org/10.5281/zenodo.13354043 Software package given here MemRBR_0.3.7.tar.gz R-package source code, e.g., use install.packages("MemRBC_0.3.7.tar.gz"), having additional standard packages from CRAN. For Windows you need Rtools installed. Further dependencies are the packages rgl, pracma, crayon, Rcpp, RcppEigen, igraph, Rvcg, tictoc, fields, Matrix, Eigen, RSpectra, Carlson, qs2, nloptr, GA, sparseMatrix Additional DATA You may find additional data on B2SHARE:Frickenhaus, S. (2026). Collection of MemRBC data for the MemRBC R software (0.3.6) [Data set]. B2SHARE. https://doi.org/10.23728/b2share.wqd6j-5p063 LIMITATIONS A couple of low-level functions used in the documented apps are undocumented. Most of them are self-explaining when looking, e.g., how they are used in the apps code. Type, for example, PSD to see the code for Penylized Steepest Descend app.Currently, the app GAM, using external package GA for Genetig Algorithms, does not work, due to errors in GA. REPOSITORY MemRBC is registered on Helmholtz Software under https://helmholtz.software/software/memrbc and version managed on github: https://github.com/atfric/MemRBC Publication of the package in a condensed form is planned for CRAN. ERRATUM Citation citation.MemRBC() Frickenhaus, S. (2025). MemRBC - a numerical modeling laboratory for the stomatocyte-discocyte-echinocyte-transformation of Red Blood Cell shape, ZENODO, DOI: https://doi.org/10.5281/zenodo.15103741