Drug Design and Discovery using Artificial Intelligence

dc.contributor.authorBenyettou, Youssouf
dc.date.accessioned2019-07-23T09:38:33Z
dc.date.available2019-07-23T09:38:33Z
dc.date.issued2019
dc.description.abstractWith the rise of deep learning models and the successful result showing in deferent domains (such as Computer vision and Natural language processing) researchers and laboratories of cheminformatics try to apply these techniques in drug design and discovery. recently, the application of Deep Learning in this area of research has made a good progress but it is in the early stage and we can’t say that the results lead us to rational drug design, which mean designing new drugs without in vivo and human trials. in this master thesis project, we applied Deep Neural network (Deep learning) in drug design and discovery dataset to predict the toxicity of molecules. After the evaluation and comparison of results we found that the big problem is the small amount of data compared with used modelen_US
dc.identifier.urihttps://repository.univ-msila.dz/handle/123456789/15685
dc.language.isoenen_US
dc.publisherUniversity of Mohamed Boudiaf Msila Department of Computer Science Master Dissertationen_US
dc.subjectDrug Design , Discovery using , Artificial Intelligenceen_US
dc.titleDrug Design and Discovery using Artificial Intelligenceen_US
dc.typeThesisen_US

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