Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained modelshttps://doi.org/10.26165/JUELICH-DATA/YXLFKJJohann F. JadebeckAxel TheorellSamuel LewekeKatharina NöhJülich DATA2020-12-182022-03-17T10:51:26ZThis collection contains showcased models and pre-processing results (determining an independent flux space and rounding) that are used as basis for benchmarking the uniform sampling performance of the CHHR implementations of the HOPS library [10.1093/bioinformatics/btaa872] (https://github.com/modsim/hops) and the COBRA toolbox [doi.org/10.1038/s41596-018-0098-2]. Here, the pre-processing was performed with the COBRA toolbox for all benchmarks to guarantee fair comparability. The models are split in two classes: 1) simplices with 64, 256, 512, 1024, and 2048 dimensions; 2) metabolic network models (e_coli_core, iAT_PLT_256, iJO1366, RECON1, Recon2, Recon3D_301) [http://bigg.ucsd.edu/], [doi.org/10.1038/nbt.2488] formulated in SBML format [doi.org/10.1093/bioinformatics/btg015]. For each of these models, the left hand side of the constraint system (called <b>A</b>), the right hand side (called <b>b</b>), a shift of the transformation from sampling space, meaning the null space, to parameter space, meaning the full space of the model (called <b>p_shift</b>), the linear transformation from sampling space to parameter space (called <b>N</b>) and the Chebyshev center (called <b>start</b>) are provided. These files come in <b> rounded </b> and <b> unrounded </b> types, indicating if the rounding algorithm has been applied. For convenience, sometimes the rounding transformation is also given (indicated by <b>T</b>). The rounding transformation is only given in the <b>rounded</b> form, because it is identity otherwise. Additionally, the dataset contains an <i>E. coli </i> WT model with carbon atom transitions and isotope labelling measurements [10.1038/nprot.2009.58] used in the Bayesian inference non-uniform sampling example. The <i>E. coli</i> WT model is contained in a single FluxML file [doi.org/10.3389/fmicb.2019.01022]. To reproduce the data generated with the <i> E. coli WT </i> model, the rounding was calculated using the HOPS library and independent fluxes were provided by the high-performance simulator 13CFLUX2 [doi.org/10.1093/bioinformatics/bts646].Medicine, Health and Life SciencesMetabolic Network Model HOPS Sampling MCMC RoundingJohann F Jadebeck, Axel Theorell, Samuel Leweke, Katharina Nöh, HOPS: high-performance library for (non-)uniform sampling of convex-constrained models, Bioinformatics, 2020, btaa872, doi, 10.1093/bioinformatics/btaa872, https://doi.org/10.1093/bioinformatics/btaa872Jadebeck, Johann Fredrik2020-10-27CC0CC0 Waiver