Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/3306
DC FieldValueLanguage
dc.contributor.authorKoutinas, Michalis-
dc.contributor.authorKiparissides, Alexandros-
dc.contributor.authorPistikopoulos, Efstratios N.-
dc.contributor.authorMantalaris, Athanasios A.-
dc.date2012en
dc.date.accessioned2014-07-09T07:21:03Z-
dc.date.accessioned2015-12-08T07:52:54Z-
dc.date.available2014-07-09T07:21:03Z-
dc.date.available2015-12-08T07:52:54Z-
dc.date.issued2012-10-
dc.identifier20010370en
dc.identifier.citationComputational and Structural Biotechnology Journal, vol.3, no.4en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14279/3306-
dc.description.abstractThe complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals. 2012 Bernstein and Carlson.en_US
dc.formatpdfen_US
dc.languageEnglishen
dc.language.isoenen_US
dc.relation.ispartofComputational and Structural Biotechnology Journalen_US
dc.rights© 2012 Bernstein and Carlsonen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectBiological systems model developmenten_US
dc.subjectGenetic circuiten_US
dc.subjectMechanistic modelen_US
dc.subjectMetabolic engineeringen_US
dc.subjectModel analysisen_US
dc.subjectSensitivity analysisen_US
dc.subject.classificationMechanical Engineering-
dc.titleBioprocess Systems Engineering: Transferring Traditional Process Engineering Principles to Industrial Biotechnologyen_US
dc.typeArticleen_US
dc.collaborationCyprus University of Technologyen_US
dc.journalsOpen Accessen_US
dc.reviewPEER-REVIEWED-
dc.countryCyprusen_US
dc.countryUnited Kingdomen_US
dc.subject.fieldNatural Sciencesen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.5936/csbj.201210022en_US
dc.identifier.pmid24688682-
dc.dept.handle123456789/77en
dc.relation.issue4en_US
dc.relation.volume3en_US
cut.common.academicyear2012-2013en_US
item.openairetypearticle-
item.grantfulltextnone-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.languageiso639-1en-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Chemical Engineering-
crisitem.author.facultyFaculty of Geotechnical Sciences and Environmental Management-
crisitem.author.orcid0000-0002-5371-4280-
crisitem.author.parentorgFaculty of Geotechnical Sciences and Environmental Management-
crisitem.journal.journalissn2001-0370-
crisitem.journal.publisherElsevier-
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