{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:50Z","timestamp":1772138090736,"version":"3.50.1"},"reference-count":40,"publisher":"Oxford University Press (OUP)","issue":"17","license":[{"start":{"date-parts":[[2018,9,9]],"date-time":"2018-09-09T00:00:00Z","timestamp":1536451200000},"content-version":"vor","delay-in-days":8,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Isaac Peral and\/or Marie Curie co-fund Programme at UPM"},{"name":"Fundacion BBVA"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Recent microbiome dynamics studies highlight the current inability to predict the effects of external perturbations on complex microbial populations. To do so would be particularly advantageous in fields such as medicine, bioremediation or industrial scenarios.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>MDPbiome statistically models longitudinal metagenomics samples undergoing perturbations as a Markov Decision Process (MDP). Given a starting microbial composition, our MDPbiome system suggests the sequence of external perturbation(s) that will engineer that microbiome to a goal state, for example, a healthier or more performant composition. It also estimates intermediate microbiome states along the path, thus making it possible to avoid particularly undesirable\/unhealthy states. We demonstrate MDPbiome performance over three real and distinct datasets, proving its flexibility, and the reliability and universality of its output \u2018optimal perturbation policy\u2019. For example, an MDP created using a vaginal microbiome time series, with a goal of recovering from bacterial vaginosis, suggested avoidance of perturbations such as lubricants or sex toys; while another MDP provided a quantitative explanation for why salmonella vaccine accelerates gut microbiome maturation in chicks. This novel analytical approach has clear applications in medicine, where it could suggest low-impact clinical interventions that will lead to achievement or maintenance of a healthy microbial population, or alternately, the sequence of interventions necessary to avoid strongly negative microbiome states.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>Code (https:\/\/github.com\/beatrizgj\/MDPbiome) and result files (https:\/\/tomdelarosa.shinyapps.io\/MDPbiome\/) are available online.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/bty562","type":"journal-article","created":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T21:20:56Z","timestamp":1530825656000},"page":"i838-i847","source":"Crossref","is-referenced-by-count":12,"title":["MDPbiome: microbiome engineering through prescriptive perturbations"],"prefix":"10.1093","volume":"34","author":[{"given":"Beatriz","family":"Garc\u00eda-Jim\u00e9nez","sequence":"first","affiliation":[{"name":"Center for Plant Biotechnology and Genomics UPM - INIA, Universidad Politecnica de Madrid, Madrid, Spain"}]},{"given":"Tom\u00e1s","family":"de la Rosa","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Universidad Carlos III de Madrid, Madrid, Spain"}]},{"given":"Mark D","family":"Wilkinson","sequence":"additional","affiliation":[{"name":"Center for Plant Biotechnology and Genomics UPM - INIA, Universidad Politecnica de Madrid, Madrid, Spain"}]}],"member":"286","published-online":{"date-parts":[[2018,9,8]]},"reference":[{"key":"2023061313513990700_bty562-B1","doi-asserted-by":"crossref","first-page":"36","DOI":"10.3389\/fmicb.2018.00036","article-title":"A web application for obtaining insights into microbial ecology using longitudinal microbiome data","volume":"9","author":"Baksi","year":"2018","journal-title":"Front. 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