{"doi":"10.1016/j.cels.2016.12.002","title":"Parallelization and High-Performance Computing Enables Automated Statistical Inference of Multi-scale Models","abstract":"Mechanistic understanding of multi-scale biological processes, such as cell proliferation in a changing biological tissue, is readily facilitated by computational models. While tools exist to construct and simulate multi-scale models, the statistical inference of the unknown model parameters remains an open problem. Here, we present and benchmark a parallel approximate Bayesian computation sequential Monte Carlo (pABC SMC) algorithm, tailored for high-performance computing clusters. pABC SMC is fully automated and returns reliable parameter estimates and confidence intervals. By running the pABC SMC algorithm for ∼10<sup>6</sup> hr, we parameterize multi-scale models that accurately describe quantitative growth curves and histological data obtained in vivo from individual tumor spheroid growth in media droplets. The models capture the hybrid deterministic-stochastic behaviors of 10<sup>5</sup>-10<sup>6</sup> of cells growing in a 3D dynamically changing nutrient environment. The pABC SMC algorithm reliably converges to a consistent set of parameters. Our study demonstrates a proof of principle for robust, data-driven modeling of multi-scale biological systems and the feasibility of multi-scale model parameterization through statistical inference.","journal":"Cell Systems","year":2017,"id":12045,"datarank":0.6238324625039509,"base_score":4.1588830833596715,"endowment":4.1588830833596715,"self_citation_contribution":0.6238324625039509,"citation_network_contribution":0.0,"self_endowment_contribution":0.6238324625039509,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":63,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.0492,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2017-02-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":96019,"name":"Dennis Rickert","orcid":null,"position":1,"is_corresponding":false},{"id":42,"name":"Fabian Joachim Theis","orcid":"0000-0002-2419-1943","position":2,"is_corresponding":false},{"id":4422,"name":"Christiane Fuchs","orcid":"0000-0003-3565-8315","position":3,"is_corresponding":false},{"id":89502,"name":"Nick Jagiella","orcid":null,"position":0,"is_corresponding":true}],"reference_count":75,"raw_metadata":null,"created_at":"2026-03-01T18:20:47.508186Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}