{"doi":"10.7490/f1000research.1118310.1","title":"Engineering the microbiome under individualized perturbations","abstract":"<ns3:p>\n                  <ns3:bold>Abstract:</ns3:bold>\n                </ns3:p>\n                <ns3:p>Microbiome dynamics studies highlight the inability to predict the effects of external perturbation on complex microbial communities over time.</ns3:p>\n                <ns3:p>MDPbiome contributes to addressing this challenge, in the context of moving microbiome studies from descriptive to translational approaches. MDPbiome is an Artificial Intelligence system built using Markov Decision Processes (MDP) to provide in-silico recommendations (e.g., about diet, pre/pro-biotics, drugs, etc.) to guide the subject’s microbiome through a path towards health or high performance, relying on microbial community changes in response to perturbations.</ns3:p>\n                <ns3:p>In addition, given the lack of experimental longitudinal microbiome datasets, we have designed a novel system to simulate the dynamics of microbial communities under perturbations using genome-scale metabolic models (GEMs), called MMODES. This makes possible to extend the application of MDPbiome to novel microbial synthetic communities and suggest interventions to modulate them to preserve or to reach a desired state. Interventions can be modifications to the nutrients in the medium or the microorganisms in the community.</ns3:p>\n                <ns3:p>MDPbiome and MDPbiomeGEM (MDPbiome plus MMODES) systems have been successfully applied to several real and simulated case studies in human, animal and soil microbiomes, to chick gut flora maturation, soil decontamination, to recover from Crohn's disease, and to avoid bacterial vaginosis.</ns3:p>\n                <ns3:p>\n                  <ns3:bold>Funding</ns3:bold>\n                </ns3:p>\n                <ns3:p>Research was supported by the “Severo Ochoa Program for Centres of Excellence in R&amp;D” from the Agencia Estatal de Investigación of Spain (grant SEV-2016-0672 (2017-2021)) to the CBGP. BGJ was supported by a Postdoctoral contract associated to the Severo Ochoa Program.</ns3:p>","journal":"Faculty of 1000 Research Ltd","year":2020,"id":9623,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.0551,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-09-10","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":606,"name":"Mark D D. Wilkinson","orcid":"0000-0001-6960-357X","position":2,"is_corresponding":false},{"id":22069,"name":"Joaquı́n Medina","orcid":"0000-0002-1735-330X","position":3,"is_corresponding":false},{"id":1680,"name":"Beatriz García-Jiménez","orcid":"0000-0002-8129-6506","position":0,"is_corresponding":true}],"reference_count":0,"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":[]}