{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T17:04:09Z","timestamp":1755795849692,"version":"3.44.0"},"publisher-location":"Cham","reference-count":35,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783032014351"},{"type":"electronic","value":"9783032014368"}],"license":[{"start":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T00:00:00Z","timestamp":1755561600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T00:00:00Z","timestamp":1755561600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-01436-8_15","type":"book-chapter","created":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T03:24:37Z","timestamp":1755487477000},"page":"276-296","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Interaction Graphs of\u00a0Phytoplankton Species Interactions Using Logical Learning"],"prefix":"10.1007","author":[{"given":"Madeleine","family":"Eyraud","sequence":"first","affiliation":[]},{"given":"Maxime","family":"Folschette","sequence":"additional","affiliation":[]},{"given":"Katsumi","family":"Inoue","sequence":"additional","affiliation":[]},{"given":"S\u00e9bastien","family":"Lefebvre","sequence":"additional","affiliation":[]},{"given":"C\u00e9dric","family":"Lhoussaine","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,8,19]]},"reference":[{"key":"15_CR1","doi-asserted-by":"publisher","unstructured":"Bruggeman, J., Kooijman, S.: A biodiversity-inspired approach to aquatic ecosystem modeling. Limnol. Oceanogr. 52 (2007). https:\/\/doi.org\/10.4319\/lo.2007.52.4.1533","DOI":"10.4319\/lo.2007.52.4.1533"},{"key":"15_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1007\/978-3-030-60327-4_11","volume-title":"Computational Methods in Systems Biology","author":"S Chevalier","year":"2020","unstructured":"Chevalier, S., No\u00ebl, V., Calzone, L., Zinovyev, A., Paulev\u00e9, L.: Synthesis and simulation of ensembles of Boolean networks for cell fate decision. In: Abate, A., Petrov, T., Wolf, V. (eds.) CMSB 2020. LNCS, vol. 12314, pp. 193\u2013209. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-60327-4_11"},{"key":"15_CR3","doi-asserted-by":"publisher","unstructured":"Chevalier, S., Froidevaux, C., Paulev\u00e9, L., Zinovyev, A.: Synthesis of Boolean networks from biological dynamical constraints using answer-set programming. In: 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), pp. 34\u201341 (2019). https:\/\/doi.org\/10.1109\/ICTAI.2019.00014","DOI":"10.1109\/ICTAI.2019.00014"},{"key":"15_CR4","doi-asserted-by":"publisher","unstructured":"Cutler, D., Edwards, T., Beard, K., et al.: Random forests for classification in ecology. Ecology 88(11), 2783\u20132792 (2007). https:\/\/doi.org\/10.1890\/07-0539.1","DOI":"10.1890\/07-0539.1"},{"key":"15_CR5","doi-asserted-by":"publisher","unstructured":"Dutkiewicz, S., Boyd, P., Riebesell, U.: Exploring biogeochemical and ecological redundancy in phytoplankton communities in the global ocean. Glob. Change Biol. 27 (2020). https:\/\/doi.org\/10.1111\/gcb.15493","DOI":"10.1111\/gcb.15493"},{"key":"15_CR6","doi-asserted-by":"publisher","first-page":"554","DOI":"10.4319\/lo.2012.57.2.0554","volume":"57","author":"K Edwards","year":"2012","unstructured":"Edwards, K., Thomas, M., Klausmeier, C., Litchman, E.: Allometric scaling and taxonomic variation in nutrient utilization traits and maximum growth rate of phytoplankton. Limnol. Oceanogr. 57, 554\u2013566 (2012). https:\/\/doi.org\/10.4319\/lo.2012.57.2.0554","journal-title":"Limnol. Oceanogr."},{"key":"15_CR7","doi-asserted-by":"publisher","first-page":"540","DOI":"10.1002\/lno.10033","volume":"60","author":"K Edwards","year":"2015","unstructured":"Edwards, K., Thomas, M., Klausmeier, C., Litchman, E.: Light and growth in marine phytoplankton: allometric, taxonomic, and environmental variation. Limnol. Oceanogr. 60, 540\u2013552 (2015). https:\/\/doi.org\/10.1002\/lno.10033","journal-title":"Limnol. Oceanogr."},{"key":"15_CR8","doi-asserted-by":"publisher","unstructured":"Edwards, K., Thomas, M., Klausmeier, C., Litchman, E.: Phytoplankton growth and the interaction of light and temperature: a synthesis at the species and community level. Limnol. Oceanogr. 61, n\/a\u2013n\/a (2016). https:\/\/doi.org\/10.1002\/lno.10282","DOI":"10.1002\/lno.10282"},{"key":"15_CR9","doi-asserted-by":"publisher","unstructured":"Emna, K., Rapaport, A., Le Floc\u2019h, E., Fouilland, E.: Demonstration of facilitation between microalgae to face environmental stress. Sci. Rep. (2019). https:\/\/doi.org\/10.1038\/s41598-019-52450-9","DOI":"10.1038\/s41598-019-52450-9"},{"key":"15_CR10","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.ecss.2015.03.010","volume":"159","author":"T Fari\u00f1as","year":"2015","unstructured":"Fari\u00f1as, T., Bacher, C., Soudant, D., Belin, C., Laurent, B.: Assessing phytoplankton realized niches using a French national phytoplankton monitoring network. Estuar. Coast. Shelf Sci. 159, 15\u201327 (2015). https:\/\/doi.org\/10.1016\/j.ecss.2015.03.010","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"15_CR11","doi-asserted-by":"publisher","unstructured":"Follows, M., Dutkiewicz, S., Grant, S., Chisholm, S.: Emergent biogeography of microbial communities in a model ocean. Science (New York, N.Y.) 315, 1843\u20136 (2007). https:\/\/doi.org\/10.1126\/science.1138544","DOI":"10.1126\/science.1138544"},{"key":"15_CR12","doi-asserted-by":"publisher","unstructured":"Gaucherel, C., Fayolle, S., Savelli, R., Philippine, O., Pommereau, F., Dupuy, C.: Diagnosis of planktonic trophic network dynamics with sharp qualitative changes. Peer Community J. 4(e58) (2023). https:\/\/doi.org\/10.24072\/pcjournal.417","DOI":"10.24072\/pcjournal.417"},{"key":"15_CR13","doi-asserted-by":"publisher","unstructured":"Gaucherel, C., Pommereau, F.: Using discrete systems to exhaustively characterize the dynamics of an integrated ecosystem. Methods Ecol. Evol. 10 (2019). https:\/\/doi.org\/10.1111\/2041-210X.13242","DOI":"10.1111\/2041-210X.13242"},{"key":"15_CR14","doi-asserted-by":"publisher","first-page":"141","DOI":"10.3354\/meps08659","volume":"415","author":"K Grangere","year":"2010","unstructured":"Grangere, K., Lefebvre, S., Bacher, C., Cugier, P., M\u00e9nesguen, A.: Modelling the spatial heterogeneity of ecological processes in an intertidal estuarine bay: dynamic interactions between bivalves and phytoplankton. Mar. Ecol. Prog. Ser. 415, 141\u2013158 (2010). https:\/\/doi.org\/10.3354\/meps08659","journal-title":"Mar. Ecol. Prog. Ser."},{"key":"15_CR15","doi-asserted-by":"publisher","unstructured":"Guziolowski, C., et al.: Exhaustively characterizing feasible logic models of a signaling network using answer set programming. Bioinformatics 30 (2013). https:\/\/doi.org\/10.1093\/bioinformatics\/btt393","DOI":"10.1093\/bioinformatics\/btt393"},{"key":"15_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.pocean.2021.102558","volume":"194","author":"E Houliez","year":"2021","unstructured":"Houliez, E., et al.: Spatio-temporal drivers of microphytoplankton community in the bay of Biscay: do species ecological niches matter? Prog. Oceanogr. 194, 102558 (2021). https:\/\/doi.org\/10.1016\/j.pocean.2021.102558","journal-title":"Prog. Oceanogr."},{"key":"15_CR17","unstructured":"Iken, O., Folschette, M., Ribeiro, T.: Automatic modeling of dynamical interactions within marine ecosystems. Master\u2019s thesis, University of Lille, France (2021)"},{"issue":"1","key":"15_CR18","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1007\/s10994-013-5353-8","volume":"94","author":"K Inoue","year":"2013","unstructured":"Inoue, K., Ribeiro, T., Sakama, C.: Learning from interpretation transition. Mach. Learn. 94(1), 51\u201379 (2013). https:\/\/doi.org\/10.1007\/s10994-013-5353-8","journal-title":"Mach. Learn."},{"key":"15_CR19","doi-asserted-by":"publisher","unstructured":"Vanhoutte-Brunier\u00a0de Joux, A., Fernand, L., M\u00e9nesguen, A., Lyons, S., Gohin, F., Philippe, C.: Modelling the Karenia Mikimotoi bloom that occurred in the western English channel during summer 2003. Ecolog. Model. (0304-3800) 210(4), 351\u2013376 (2008). https:\/\/doi.org\/10.1016\/j.ecolmodel.2007.08.025","DOI":"10.1016\/j.ecolmodel.2007.08.025"},{"key":"15_CR20","doi-asserted-by":"publisher","unstructured":"Karasiewicz, S., Breton, E., Lefebvre, A., Fari\u00f1as, T., Lefebvre, S.: Realized niche analysis of phytoplankton communities involving HAB: phaeocystis SPP. As a case study. Harmful Algae 72, 1\u201313 (2018). https:\/\/doi.org\/10.1016\/j.hal.2017.12.005","DOI":"10.1016\/j.hal.2017.12.005"},{"key":"15_CR21","doi-asserted-by":"publisher","unstructured":"Karasiewicz, S., Dol\u00e9dec, S., Lefebvre, S.: Within outlying mean indexes: refining the OMI analysis for the realized niche decomposition. PeerJ 5(e3364) (2017). https:\/\/doi.org\/10.7717\/peerj.3364","DOI":"10.7717\/peerj.3364"},{"key":"15_CR22","doi-asserted-by":"publisher","unstructured":"Karasiewicz, S., Lefebvre, A.: Environmental impact on harmful species pseudo-nitzschia spp and Phaeocystis Globosa phenology and niche. J. Mar. Sci. Eng. 10 (2022). https:\/\/doi.org\/10.3390\/jmse10020174","DOI":"10.3390\/jmse10020174"},{"issue":"1","key":"15_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40645-020-00369-5","volume":"7","author":"M Kawamiya","year":"2020","unstructured":"Kawamiya, M., Hajima, T., Tachiiri, K., Watanabe, S., Yokohata, T.: Two decades of earth system modeling with an emphasis on model for interdisciplinary research on climate (MIROC). Prog. Earth Planet. Sci. 7(1), 1\u201313 (2020). https:\/\/doi.org\/10.1186\/s40645-020-00369-5","journal-title":"Prog. Earth Planet. Sci."},{"key":"15_CR24","doi-asserted-by":"publisher","first-page":"1077","DOI":"10.5194\/essd-15-1077-2023","volume":"15","author":"A Lefebvre","year":"2023","unstructured":"Lefebvre, A., Devreker, D.: How to learn more about hydrological conditions and phytoplankton dynamics and diversity in the eastern English channel and the southern bight of the north sea: the Suivi r\u00e9gional des nutriments data set (1992\u20132021). Earth Syst. Sci. Data 15, 1077\u20131092 (2023). https:\/\/doi.org\/10.5194\/essd-15-1077-2023","journal-title":"Earth Syst. Sci. Data"},{"key":"15_CR25","unstructured":"Mart\u00ednez, D., Aleny\u00e0, G., Ribeiro, T., Inoue, K., Torras, C.: Relational reinforcement learning for planning with exogenous effects. J. Mach. Learn. Res. 18(78), 1\u201344 (2017). http:\/\/jmlr.org\/papers\/v18\/16-326.html"},{"key":"15_CR26","doi-asserted-by":"publisher","unstructured":"Mutshinda, C., Finkel, Z., Widdicombe, C., Irwin, A.: Phytoplankton traits from long-term oceanographic time-series. Mar. Ecol. Progress Ser. 576 (2017). https:\/\/doi.org\/10.3354\/meps12220","DOI":"10.3354\/meps12220"},{"key":"15_CR27","doi-asserted-by":"publisher","unstructured":"Okazaki, K., Inoue, K.: Explainable model fusion for customer journey mapping. Front. Artif. Intell. 5 (2022). https:\/\/doi.org\/10.3389\/frai.2022.824197","DOI":"10.3389\/frai.2022.824197"},{"key":"15_CR28","doi-asserted-by":"publisher","unstructured":"Paulev\u00e9, L., Gaucherel, C.: Inference of ecological networks and possibilistic dynamics based on Boolean networks from observations and prior knowledge. Technical report, University of Bordeaux (2024). https:\/\/doi.org\/10.1101\/2024.07.01.601264","DOI":"10.1101\/2024.07.01.601264"},{"key":"15_CR29","doi-asserted-by":"publisher","unstructured":"Ribeiro, T., Folschette, M., Magnin, M., Inoue, K.: Learning any memory-less discrete semantics for dynamical systems represented by logic programs. Mach. Learn. (1), 1\u201378 (2021). https:\/\/doi.org\/10.1007\/s10994-021-06105-4","DOI":"10.1007\/s10994-021-06105-4"},{"key":"15_CR30","unstructured":"Ribeiro, T., Folschette, M., Magnin, M., Inoue, K.: Polynomial algorithm for learning from interpretation transition. In: 1st International Joint Conference on Learning & Reasoning (2021). hal-03347026"},{"key":"15_CR31","doi-asserted-by":"publisher","unstructured":"Simon, F., et al.: CausalXtract, a flexible pipeline to extract causal effects from live-cell time-lapse imaging data. eLife 13, RP95485 (2025). https:\/\/doi.org\/10.7554\/eLife.95485","DOI":"10.7554\/eLife.95485"},{"key":"15_CR32","doi-asserted-by":"publisher","unstructured":"SRN-Regional Observation and Monitoring Program For Phytoplankton And Hydrology in the Eastern English Channel: SRN dataset - Regional Observation and Monitoring Program for Phytoplankton and Hydrology in the eastern English Channel (2025). https:\/\/doi.org\/10.17882\/50832. https:\/\/www.seanoe.org\/data\/00397\/50832\/","DOI":"10.17882\/50832"},{"key":"15_CR33","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1111\/geb.12387","volume":"25","author":"M Thomas","year":"2016","unstructured":"Thomas, M., Kremer, C., Litchman, E.: Environment and evolutionary history determine the global biogeography of phytoplankton temperature traits. Glob. Ecol. Biogeogr. 25, 75\u201386 (2016). https:\/\/doi.org\/10.1111\/geb.12387","journal-title":"Glob. Ecol. Biogeogr."},{"key":"15_CR34","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1005662","volume":"13","author":"L Verny","year":"2017","unstructured":"Verny, L., Sella, N., Affeldt, S., Singh, P., Isambert, H.: Learning causal networks with latent variables from multivariate information in genomic data. PLoS Comput. Biol. 13, e1005662 (2017). https:\/\/doi.org\/10.1371\/journal.pcbi.1005662","journal-title":"PLoS Comput. Biol."},{"key":"15_CR35","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2021.145681","volume":"773","author":"S \u015aliwi\u0144ska Wilczewska","year":"2021","unstructured":"\u015aliwi\u0144ska Wilczewska, S., et al.: The current state of knowledge on taxonomy, modulating factors, ecological roles, and mode of action of phytoplankton allelochemicals. Sci. Total Environ. 773, 145681 (2021). https:\/\/doi.org\/10.1016\/j.scitotenv.2021.145681","journal-title":"Sci. Total Environ."}],"container-title":["Lecture Notes in Computer Science","Computational Methods in Systems Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-01436-8_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T03:24:41Z","timestamp":1755487481000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-01436-8_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,19]]},"ISBN":["9783032014351","9783032014368"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-01436-8_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025,8,19]]},"assertion":[{"value":"19 August 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors\u00a0have no competing interests to declare.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"CMSB","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Methods in Systems Biology","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lyon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cmsb2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/cmsb2025.sciencesconf.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}