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DC Field | Value | Language |
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dc.contributor.author | Belouadi Meriem | - |
dc.contributor.author | MelleHazam Khaoula | - |
dc.contributor.author | Melle Khaldi aicha | - |
dc.contributor.author | MOGHTIT Fatima Zohra | - |
dc.date.accessioned | 2024-02-15T10:25:20Z | - |
dc.date.available | 2024-02-15T10:25:20Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | http://dspace.univ-temouchent.edu.dz/handle/123456789/2345 | - |
dc.description.abstract | The EGFR gene is a tumor suppressor gene and its molecular alteration may increase the risk of branch cancer. In order to contribute to the molecular study, we were interested in thestudy of the deleterious effects of three mutations of the EGFR gene, namely the c.2155G>A mutation, the c.2156G>C mutation and c. 2155G>T. Thus, the deleterious effects of the three mutations were predicted using an in silico protocol consisting of different software (I-Mutant 2.0; SIFT; Polyphen-2; Project HOPE). The mutations c.2155G>A, c.2156G>C, c.2155G>T are predicted to be deleterious altering the EGFR protein. In fact, physicochemical changes between wild-type and mutated amino acids can disrupt protein stability and lead to loss of interactions with other molecules. Our results show that theses different softwares are consistent and that their combination can improve the performance of predicting the effects of these mutations. This study allows us to better understand the impact of mutations and highlights the importance of predictive research in bioinformatics software. | en_US |
dc.language.iso | fr | en_US |
dc.subject | EGFR protein, Mutation, effect, in silico, Bioinformatic | en_US |
dc.subject | ProtéineEGFR, Mutation,effet,in silico, Bioinformatique | en_US |
dc.title | Etude in silico d'une mutation:application à la mutation fonctionnelle G719X du gène EGFR retrouvée dans les cancers bronchiques non à petites cellules | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Sciences Biologiques |
Files in This Item:
File | Description | Size | Format | |
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_Mémoire_EGFR In silico_2022.pdf | 2,04 MB | Adobe PDF | View/Open |
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