| dc.contributor.author | Wan, Fangping | |
| dc.contributor.author | Kontogiorgos-Heintz, Daphne | |
| dc.contributor.author | de la Fuente-Nunez, Cesar | |
| dc.date.accessioned | 2022-10-28T18:50:16Z | |
| dc.date.available | 2022-10-28T18:50:16Z | |
| dc.date.issued | 2022 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/146045 | |
| dc.description.abstract | <jats:p>We present a review of deep generative models and their applications in peptide design.</jats:p> | en_US |
| dc.language.iso | en | |
| dc.publisher | Royal Society of Chemistry (RSC) | en_US |
| dc.relation.isversionof | 10.1039/D1DD00024A | en_US |
| dc.rights | Creative Commons Attribution 3.0 unported license | en_US |
| dc.rights.uri | https://creativecommons.org/licenses/by/3.0/ | en_US |
| dc.source | Royal Society of Chemistry (RSC) | en_US |
| dc.title | Deep generative models for peptide design | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Wan, Fangping, Kontogiorgos-Heintz, Daphne and de la Fuente-Nunez, Cesar. 2022. "Deep generative models for peptide design." Digital Discovery, 1 (3). | |
| dc.relation.journal | Digital Discovery | en_US |
| dc.eprint.version | Final published version | en_US |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
| dc.date.updated | 2022-10-28T18:39:14Z | |
| dspace.orderedauthors | Wan, F; Kontogiorgos-Heintz, D; de la Fuente-Nunez, C | en_US |
| dspace.date.submission | 2022-10-28T18:39:15Z | |
| mit.journal.volume | 1 | en_US |
| mit.journal.issue | 3 | en_US |
| mit.license | PUBLISHER_CC | |
| mit.metadata.status | Authority Work and Publication Information Needed | en_US |
