Publication
Classification of recombinant Saccharomyces cerevisiae cells using PLS-DA modelling based on MIR spectroscopy
| dc.contributor.author | Sampaio, Pedro | |
| dc.contributor.author | Calado, Cecília | |
| dc.date.accessioned | 2019-05-20T11:49:42Z | |
| dc.date.available | 2019-05-20T11:49:42Z | |
| dc.date.issued | 2019-04-18 | |
| dc.description.abstract | Towards the optimization and control of bioprocesses, as the culture step of recombinant microorganisms, it is crucial to develop high-throughput monitoring techniques enabling the acquisition of a large data sets of information, as the ones based on mid infrared (MIR) spectroscopy. To maximize the knowledge associated to this this new large-scale data, it is also relevant to apply machine learning techniques, as Partial Least-Squares Discriminant Analysis (PLS-DA). In the present work, Principal Component Analysis followed by PLS-DA were applied to discriminate different growth phases of recombinant Saccharomyces cerevisiae along the production of an heterologous protein, conducted in bioreactor and monitored by high-throughput MIR spectroscopy. It was possible to derive PLS-DA models enabling to discriminate, from the MIR spectra, the yeast cells according to its metabolic status associated to the culture growth phase with an accuracy, sensitivity, and specificity between 83% and 100%. The optimised PLS-DA presented very low calibration errors, of 97% and 100% based on a cross-validation and an independent data-set, respectively. In conclusion, it was possible to build a PLS-DA model discriminating the cells metabolic status that will promote the knowledge of the bioprocess and future better control and optimization procedures. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | SAMPAIO, Pedro N.; CALADO, Cecília R. C. – Classification of recombinant Saccharomyces cerevisiae cells using PLS-DA modelling based on MIR spectroscopy. In 2019 IEEE 6th Portuguese Meeting on Bioengineering (ENBENG). Lisbon, Portugal: IEEE, 2019. ISBN 978-1-5386-8506-8. Pp. 1-4 | pt_PT |
| dc.identifier.doi | 10.1109/ENBENG.2019.8692463 | pt_PT |
| dc.identifier.isbn | 978-1-5386-8506-8 | |
| dc.identifier.isbn | 978-1-5386-8507-5 | |
| dc.identifier.uri | http://hdl.handle.net/10400.21/10048 | |
| dc.language.iso | eng | pt_PT |
| dc.publisher | Institute of Electrical and Electronics Engineers | pt_PT |
| dc.relation.publisherversion | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8692463 | pt_PT |
| dc.subject | Saccharomyces cerevisiae | pt_PT |
| dc.subject | Partial Least-Squares Discriminant Analysis (PLS-DA) | pt_PT |
| dc.subject | MIR spectroscopy | pt_PT |
| dc.title | Classification of recombinant Saccharomyces cerevisiae cells using PLS-DA modelling based on MIR spectroscopy | pt_PT |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | 22-23 Feb. 2019 - Lisbon, Portugal | pt_PT |
| oaire.citation.endPage | 4 | pt_PT |
| oaire.citation.startPage | 1 | pt_PT |
| oaire.citation.title | 2019 IEEE 6th Portuguese Meeting on Bioengineering (ENBENG) | pt_PT |
| person.familyName | Sampaio | |
| person.familyName | Calado | |
| person.givenName | Pedro | |
| person.givenName | Cecília | |
| person.identifier | 1251979 | |
| person.identifier | 130332 | |
| person.identifier.ciencia-id | AF12-6ABA-43D8 | |
| person.identifier.ciencia-id | 9418-E320-3177 | |
| person.identifier.orcid | 0000-0003-2917-4904 | |
| person.identifier.orcid | 0000-0002-5264-9755 | |
| person.identifier.rid | E-2102-2014 | |
| person.identifier.scopus-author-id | 24178064100 | |
| person.identifier.scopus-author-id | 6603163260 | |
| rcaap.rights | closedAccess | pt_PT |
| rcaap.type | conferenceObject | pt_PT |
| relation.isAuthorOfPublication | 303f3e22-ec1a-4243-9ded-98c647776e6a | |
| relation.isAuthorOfPublication | e8577257-c64c-4481-9b2b-940fedb360cc | |
| relation.isAuthorOfPublication.latestForDiscovery | 303f3e22-ec1a-4243-9ded-98c647776e6a |