Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/181404
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Campo DCValorIdioma
dc.contributor.advisorVanneschi, Leonardo-
dc.contributor.advisorRocha, Isabel-
dc.contributor.authorBernardino, Rodrigo António Correia Tavares-
dc.date.accessioned2025-03-26T16:17:51Z-
dc.date.available2025-03-26T16:17:51Z-
dc.date.issued2024-02-12-
dc.identifier.urihttp://hdl.handle.net/10362/181404-
dc.description.abstract"The biosphere solution to the protein design problem is akin to a planetwide computational machine running a simple stochastic algorithm. The root of its success lies in the open endedness and diversity of its search, willing to extend across all possible niches over time. Nature’s work produces living transient DNA artifacts that are stored in the biosphere, and, at an increasing rate, being read by sequencing technology and transfered to large datasets now hosting millions of raw samples. This data can be leveraged by the use of increasingly large pLM(protein Language models), that have been shown to essentially function as unsupervised protein structure learners. (...)"pt_PT
dc.language.isoengpt_PT
dc.publisherInstituto de Tecnologia Química e Biológica António Xavier. Universidade NOVA de Lisboa.pt_PT
dc.rightsopenAccesspt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectΔΔ𝐺pt_PT
dc.subjectOmegafoldpt_PT
dc.subjectPythiapt_PT
dc.subjectpLMpt_PT
dc.titleEXPERIMENTS IN THE USE OF ΔΔ𝐺 PREDICTIONS FOR DENOVO IN-SILICO PROTEIN DESIGNpt_PT
dc.typemasterThesispt_PT
degois.publication.locationOeiras, Portugalpt_PT
dc.peerreviewedyespt_PT
dc.identifier.tid203618769-
dc.description.versionN/Apt_PT
Aparece nas colecções:ITQB: LA - Master Dissertations

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