Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained modelsdoi:10.26165/JUELICH-DATA/YXLFKJJülich DATA2020-12-181Johann F. Jadebeck; Axel Theorell; Samuel Leweke; Katharina Nöh, 2020, "Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models", https://doi.org/10.26165/JUELICH-DATA/YXLFKJ, Jülich DATA, V1Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained modelsdoi:10.26165/JUELICH-DATA/YXLFKJJohann F. JadebeckAxel TheorellSamuel LewekeKatharina NöhJülich DATAJohann F. JohannKatharina NöhJadebeck, Johann Fredrik2020-10-27Medicine, Health and Life SciencesMetabolic Network Model HOPS Sampling MCMC RoundingThis 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 A), the right hand side (called b), a shift of the transformation from sampling space, meaning the null space, to parameter space, meaning the full space of the model (called p_shift), the linear transformation from sampling space to parameter space (called N) and the Chebyshev center (called start) are provided. These files come in rounded and unrounded types, indicating if the rounding algorithm has been applied. For convenience, sometimes the rounding transformation is also given (indicated by T). The rounding transformation is only given in the rounded form, because it is identity otherwise. Additionally, the dataset contains an E. coli 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 E. coli WT model is contained in a single FluxML file [doi.org/10.3389/fmicb.2019.01022]. To reproduce the data generated with the E. coli WT 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].CC0 Waiver10.1093/bioinformatics/btaa872Johann F Jadebeck, Axel Theorell, Samuel Leweke, Katharina Nöh, HOPS: high-performance library for (non-)uniform sampling of convex-constrained models, Bioinformatics, 2020, btaa872A_e_coli_core_rounded.csvtext/csvA_e_coli_core_unrounded.csvtext/csvA_iAT_PLT_636_rounded.csvtext/csvA_iAT_PLT_636_unrounded.csvtext/csvA_iJO1366_rounded.csvtext/csvA_iJO1366_unrounded.csvtext/csvA_RECON1_rounded.csvtext/csvA_RECON1_unrounded.csvtext/csvA_Recon2_rounded.csvtext/csvA_Recon2_unrounded.csvtext/csvA_Recon3D_301_rounded.csvtext/csvA_Recon3D_301_unrounded.csvtext/csvA_simplex_1024D_rounded.csvtext/csvA_simplex_1024D_unrounded.csvtext/csvA_simplex_2048D_rounded.csvtext/csvA_simplex_2048D_unrounded.csvtext/csvA_simplex_256D_rounded.csvtext/csvA_simplex_256D_unrounded.csvtext/csvA_simplex_512D_rounded.csvtext/csvA_simplex_512D_unrounded.csvtext/csvA_simplex_64D_rounded.csvtext/csvA_simplex_64D_unrounded.csvtext/csvb_e_coli_core_rounded.csvtext/csvb_e_coli_core_unrounded.csvtext/csvb_iAT_PLT_636_rounded.csvtext/csvb_iAT_PLT_636_unrounded.csvtext/csvb_iJO1366_rounded.csvtext/csvb_iJO1366_unrounded.csvtext/csvb_RECON1_rounded.csvtext/csvb_RECON1_unrounded.csvtext/csvb_Recon2_rounded.csvtext/csvb_Recon2_unrounded.csvtext/csvb_Recon3D_301_rounded.csvtext/csvb_Recon3D_301_unrounded.csvtext/csvb_simplex_1024D_rounded.csvtext/csvb_simplex_1024D_unrounded.csvtext/csvb_simplex_2048D_rounded.csvtext/csvb_simplex_2048D_unrounded.csvtext/csvb_simplex_256D_rounded.csvtext/csvb_simplex_256D_unrounded.csvtext/csvb_simplex_512D_rounded.csvtext/csvb_simplex_512D_unrounded.csvtext/csvb_simplex_64D_rounded.csvtext/csvb_simplex_64D_unrounded.csvtext/csve_coli_core.xmltext/xmlE.coli_Zamboni2009.fmlapplication/octet-streamiAT_PLT_636.matapplication/matlab-matiJO1366.xmltext/xmlN_e_coli_core_rounded.csvtext/csvN_e_coli_core_unrounded.csvtext/csvN_iAT_PLT_636_rounded.csvtext/csvN_iAT_PLT_636_unrounded.csvtext/csvN_iJO1366_rounded.csvtext/csvN_iJO1366_unrounded.csvtext/csvN_RECON1_rounded.csvtext/csvN_RECON1_unrounded.csvtext/csvN_Recon2_rounded.csvtext/csvN_Recon2_unrounded.csvtext/csvN_Recon3D_301_rounded.csvtext/csvN_Recon3D_301_unrounded.csvtext/csvN_simplex_1024D_rounded.csvtext/csvN_simplex_2048D_rounded.csvtext/csvN_simplex_256D_rounded.csvtext/csvN_simplex_512D_rounded.csvtext/csvN_simplex_64D_rounded.csvtext/csvN_simplex_64D_unrounded.csvtext/csvp_shift_e_coli_core.csvtext/csvp_shift_e_coli_core_rounded.csvtext/csvp_shift_e_coli_core_unrounded.csvtext/csvp_shift_iAT_PLT_636_rounded.csvtext/csvp_shift_iAT_PLT_636_unrounded.csvtext/csvp_shift_iJO1366_rounded.csvtext/csvp_shift_iJO1366_unrounded.csvtext/csvp_shift_RECON1_rounded.csvtext/csvp_shift_RECON1_unrounded.csvtext/csvp_shift_Recon2_rounded.csvtext/csvp_shift_Recon2_unrounded.csvtext/csvp_shift_Recon3D_301_rounded.csvtext/csvp_shift_Recon3D_301_unrounded.csvtext/csvp_shift_simplex_1024D_rounded.csvtext/csvp_shift_simplex_2048D_rounded.csvtext/csvp_shift_simplex_256D_rounded.csvtext/csvp_shift_simplex_512D_rounded.csvtext/csvp_shift_simplex_64D_rounded.csvtext/csvp_shift_simplex_64D_unrounded.csvtext/csvRECON1.matapplication/matlab-matRecon2.xmltext/xmlRecon3D_301.matapplication/matlab-matstart_e_coli_core_rounded.csvtext/csvstart_e_coli_core_unrounded.csvtext/csvstart_iAT_PLT_636_rounded.csvtext/csvstart_iAT_PLT_636_unrounded.csvtext/csvstart_iJO1366_rounded.csvtext/csvstart_iJO1366_unrounded.csvtext/csvstart_RECON1_rounded.csvtext/csvstart_RECON1_unrounded.csvtext/csvstart_Recon2_rounded.csvtext/csvstart_Recon2_unrounded.csvtext/csvstart_Recon3D_301_rounded.csvtext/csvstart_Recon3D_301_unrounded.csvtext/csvstart_simplex_1024D_rounded.csvtext/csvstart_simplex_1024D_unrounded.csvtext/csvstart_simplex_2048D_rounded.csvtext/csvstart_simplex_2048D_unrounded.csvtext/csvstart_simplex_256D_rounded.csvtext/csvstart_simplex_256D_unrounded.csvtext/csvstart_simplex_512D_rounded.csvtext/csvstart_simplex_512D_unrounded.csvtext/csvstart_simplex_64D_rounded.csvtext/csvstart_simplex_64D_unrounded.csvtext/csvT_e_coli_core_rounded.csvtext/csvT_iAT_PLT_636_rounded.csvtext/csvT_iJO1366_rounded.csvtext/csvT_RECON1_rounded.csvtext/csvT_Recon2_rounded.csvtext/csvT_Recon3D_301_rounded.csvtext/csvT_simplex_1024D_rounded.csvtext/csvT_simplex_2048D_rounded.csvtext/csvT_simplex_256D_rounded.csvtext/csvT_simplex_512D_rounded.csvtext/csvT_simplex_64D_rounded.csvtext/csvT_simplex_64D_unrounded.csvtext/csv