An application of Genetic Algorithms for the Lead Molecule Optimisation. (Titolo provvisorio)

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dc.contributor.advisor Poli, Irene it_IT
dc.contributor.author Filippi, Andrea <1990> it_IT
dc.date.accessioned 2016-10-10 it_IT
dc.date.accessioned 2016-12-23T05:08:38Z
dc.date.issued 2016-11-03 it_IT
dc.identifier.uri http://hdl.handle.net/10579/9366
dc.description.abstract Lead Molecule Optimisation and the process of Drug Design are very difficult problems, demanding an huge investment in terms of resources and experimentation. The standard approach requires iterations of long synthesis and testing cycles as well as formulations, which are hard and complex tasks. In this thesis are presented, in the first chapters, an analysis of Nature inspired computation and the problem of Lead Molecule Optimisation; lately it is proposed a method to address such problem. It is the Genetic Algorithm Optimisation (GAO) method, which will be applied to a set of experimental data of fitness values and molecule fragments. The dataset is provided by the European Center for Living Technology (ECLT). The GAO is used to find an optimal solution for the development of a particular drug (MMP-12 inhibitors). A total of 120 molecules are tested over 6 generations; the results show that the algorithm works as intended by reaching the optimum in an acceptable amount of time, required for the computation. The good performance of the GAO method is analysed and shown in the thesis with its capacity to reach the desired optimum value using the data set provided. it_IT
dc.language.iso it_IT
dc.publisher Università Ca' Foscari Venezia it_IT
dc.rights © Andrea Filippi, 2016 it_IT
dc.title An application of Genetic Algorithms for the Lead Molecule Optimisation. (Titolo provvisorio) it_IT
dc.title.alternative it_IT
dc.type Master's Degree Thesis it_IT
dc.degree.name Informatica - computer science it_IT
dc.degree.level Laurea magistrale it_IT
dc.degree.grantor Dipartimento di Scienze Ambientali, Informatica e Statistica it_IT
dc.description.academicyear 2015/2016, sessione autunnale it_IT
dc.rights.accessrights closedAccess it_IT
dc.thesis.matricno 828746 it_IT
dc.subject.miur it_IT
dc.description.note it_IT
dc.degree.discipline it_IT
dc.contributor.co-advisor it_IT
dc.date.embargoend 10000-01-01
dc.provenance.upload Andrea Filippi (828746@stud.unive.it), 2016-10-10 it_IT
dc.provenance.plagiarycheck Irene Poli (irenpoli@unive.it), 2016-10-24 it_IT


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