Ligand-based virtual screening using deep learning attention mechanism and learning representation

dc.contributor.author	Amri, Younes
dc.contributor.author	Akkache, Lounis
dc.contributor.author	Hentabli, Hamza (Encadreur)
dc.date.accessioned	2023-11-26T10:19:46Z
dc.date.available	2023-11-26T10:19:46Z
dc.date.issued	2023
dc.description.abstract	virtual screening techniques have emerged as computational methods for efficient chemical compund screening in the traditional drug production proccess. ligand based virtual screening (LBVS) has been success ful in capturing biological similarity between test compounds and known target ligands	fr
dc.identifier.citation	Ingénierie des Systèmes et Technologie du Web	fr
dc.identifier.govdoc	M62398
dc.identifier.uri	https://dspace.univ-medea.dz/handle/123456789/11094
dc.language.iso	en	fr
dc.relation.ispartofseries	M62398;
dc.subject	Traditional drug production	fr
dc.subject	virtual screening	fr
dc.subject	siamese network	fr
dc.subject	similarity searching	fr
dc.title	Ligand-based virtual screening using deep learning attention mechanism and learning representation	fr
dc.type	Thesis	fr

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