Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/74506Registo completo
| Campo DC | Valor | Idioma |
|---|---|---|
| dc.contributor.author | Sequeira, Ana | por |
| dc.contributor.author | Lousa, Diana | por |
| dc.contributor.author | Rocha, Miguel | por |
| dc.date.accessioned | 2021-10-25T10:42:09Z | - |
| dc.date.issued | 2021 | - |
| dc.identifier.citation | Sequeira, Ana; Lousa, Diana; Rocha, Miguel, Propythia: a Python automated platform for the classification of proteins using machine learning. PACBB 2020 - 14th International Conference Practical Applications of Computational Biology & Bioinformatics. Vol. Advances in Intelligent Systems and Computing 1240, L'Aquila, Italy, Oct 7-9, Springer International Publishing, 32-41, 2021. ISBN: 978-3-030-54568-0 | por |
| dc.identifier.isbn | 978-3-030-54568-0 | por |
| dc.identifier.issn | 2194-5357 | por |
| dc.identifier.uri | https://hdl.handle.net/1822/74506 | - |
| dc.description.abstract | A challenging problem in Bioinformatics is to predict protein structure, properties, activities or interactions from their aminoacid sequences. Sequence-derived physicochemical features of proteins have been used to support the development of Machine Learning (ML) models. However, tools and platforms to calculate features from protein sequences and train ML models are scarce and have limitations in terms of performance, user-friendliness and domains of application. | por |
| dc.description.sponsorship | This study was supported by FCT through project PTDC/CCI-BIO/28200/2017 and the strategic funding of UID/BIO/04469/2020, and also by the European Regional Development Fund under the scope of Norte2020, through the projects DeepBio (ref. NORTE-01-0247-FEDER-039831). This work was also financially supported by Project LISBOA-01-0145-FEDER-007660 (Microbiologia Molecular, Estrutural e Celular) funded by FEDER funds through COMPETE2020 - Programa Operacional Competitividade e Internacionalização (POCI) and by national funds through FCT - Fundação para a Ciência e a Tecnologia. | por |
| dc.language.iso | eng | por |
| dc.publisher | Springer International Publishing | por |
| dc.relation | PTDC/CCI-BIO/28200/2017 | por |
| dc.relation | UID/BIO/04469/2020 | por |
| dc.rights | restrictedAccess | por |
| dc.subject | Bioinformatics | por |
| dc.subject | Ontologies | por |
| dc.subject | Cancer | por |
| dc.subject | Machine learning | por |
| dc.subject | Protein/Peptide classification | por |
| dc.subject | Python package | por |
| dc.title | Propythia: a Python automated platform for the classification of proteins using machine learning | por |
| dc.type | conferencePaper | por |
| dc.peerreviewed | yes | por |
| dc.relation.publisherversion | https://link.springer.com/chapter/10.1007%2F978-3-030-54568-0_4 | por |
| dc.comments | CEB53836 | por |
| oaire.citationStartPage | 32 | por |
| oaire.citationEndPage | 41 | por |
| oaire.citationConferencePlace | L'Aquila, Italy | por |
| oaire.citationVolume | 1240 AISC | por |
| dc.date.updated | 2021-10-25T08:45:04Z | - |
| dc.identifier.doi | 10.1007/978-3-030-54568-0_4 | por |
| dc.date.embargo | 10000-01-01 | - |
| dc.description.publicationversion | info:eu-repo/semantics/publishedVersion | - |
| sdum.journal | Advances in Intelligent Systems and Computing | por |
| sdum.conferencePublication | PACBB 2020 - 14th International Conference Practical Applications of Computational Biology & Bioinformatics | por |
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|---|---|---|---|---|
| document_53836_1.pdf Acesso restrito! | 448,81 kB | Adobe PDF | Ver/Abrir |
