Publication:
Editorial: Mathematical and computational methods in physiology.

dc.contributor.authorFemia, Pedro
dc.contributor.authorMelchor, Juan
dc.contributor.authorCarmona-Saez, Pedro
dc.contributor.funderMinisterio de Ciencia e Innovación
dc.contributor.funderFEDER/Junta de Andalucía-Consejería de Transformación Econímica, Industria, Conocimiento y Universidades
dc.contributor.funderEuropean Regional Development Fund (ERDF)
dc.date.accessioned2023-05-03T13:44:54Z
dc.date.available2023-05-03T13:44:54Z
dc.date.issued2022-07-07
dc.description.abstractPhysiology constitutes a broad discipline that covers the study of the different hierarchical levels of living organisms, from the cellular one to higher levels, such as tissues or organs. The articles of this monography provide an excellent example of the telescopic capacity of this discipline. A common nexus among all these levels is that physiological systems are epistemologically complex. This implies that their study requires a necessary reduction of the complexity in order to elaborate a formal and manageable description of the system, giving rise to a model. Therefore, we need to develop mathematical models that represent the original system instead of studying it. Nevertheless, even this representation can present an unmanageable degree of complexity. Typically, the description of the physiological processes relies on non-linear relationships among a high number of variables that involve many parameters of unknown value.
dc.description.sponsorshipPS acknowledges funding from Ministerio de Ciencia e Innovación (grant PID 2020-119032RB-I00) and FEDER/Junta de Andalucía-Consejería de Transformación Econímica, Industria, Conocimiento y Universidades (grants P20-00335 and B-CTS-40- UGR20), JM acknowledges funding from Ministerio de Ciencia e Innovación (grant PID 2019-106947RA-C22) and PRE 2018-086085 (Co-funded by European Social Fund “Investing in your future”); Consejería de economía, conocimiento, empresas y universidad and European Regional Development Fund (ERDF) SOMM17/6109/ UGR and P18-RT-1653.
dc.description.versionSi
dc.identifier.citationFemia P, Melchor J, Carmona-Saez P. Editorial: Mathematical and computational methods in physiology. Front Physiol. 2022 Aug 8;13:975075.
dc.identifier.doi10.3389/fphys.2022.975075
dc.identifier.issn1664-042X
dc.identifier.pmcPMC9393705
dc.identifier.pmid36003655
dc.identifier.pubmedURLhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9393705/pdf
dc.identifier.unpaywallURLhttps://www.frontiersin.org/articles/10.3389/fphys.2022.975075/pdf
dc.identifier.urihttp://hdl.handle.net/10668/20717
dc.journal.titleFrontiers in physiology
dc.journal.titleabbreviationFront Physiol
dc.language.isoen
dc.organizationCentro Pfizer-Universidad de Granada-Junta de Andalucía de Genómica e Investigación Oncológica-GENYO
dc.organizationInstituto de Investigación Biosanitaria de Granada (ibs.GRANADA)
dc.page.number2
dc.publisherFrontiers Research Foundation
dc.pubmedtypeEditorial
dc.relation.projectIDPID 2020-119032RB-I00
dc.relation.projectIDP20-00335
dc.relation.projectIDB-CTS-40- UGR20
dc.relation.projectIDPID 2019-106947RA-C22
dc.relation.projectIDPRE 2018-086085
dc.relation.projectIDSOMM17/6109/ UGR
dc.relation.projectIDP18-RT-1653
dc.relation.publisherversionhttps://doi.org/10.3389/fphys.2022.975075
dc.rightsAttribution 4.0 International
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectbiostatistical methods
dc.subjectcomputational methods
dc.subjectmachine learning
dc.subjectmathematical physiology
dc.subjectmodelling
dc.subjectomics integration
dc.subject.decsAprendizaje automático
dc.subject.decsFisiología
dc.subject.decsMétodos
dc.titleEditorial: Mathematical and computational methods in physiology.
dc.typeresearch article
dc.type.hasVersionVoR
dc.volume.number13
dspace.entity.typePublication

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