drugdiscoveryandgenomics(編輯修改稿)
2024-10-22 22:37 本頁面
【文章內容簡介】 s ? Pharmacogenomics B i o p h a r m a c e u t i c a l s L t d. Functional Genomics: Motifs ? Gene families – Super families of related activities such as dehydrogenases, glucocorticoid receptorlike etc. – Bioinformatic tools。 data mining B i o p h a r m a c e u t i c a l s L t d. Functional Genomics: Microarrays of Gene Expression Normal tissue cDNA Diseased Diseased associated normal B i o p h a r m a c e u t i c a l s L t d. Functional Genomics: Model Organisms “Genes are just chunks of software that can Run on any system: they use the same code And do the same jobs.” Matt Ridley in Genome 1999 Perennial Example: Homeotic genes which determine macro form of animal Fly mouse B i o p h a r m a c e u t i c a l s L t d. Functional Genomics: Proteomics Differential display of protein expression in diseased and normal tissue May be a better approach to target identification than microarrays of gene expression Not all expressed genes produce proteins B i o p h a r m a c e u t i c a l s L t d. Functional Genomics: Pharmacogenomics Geic differences between individuals (SNP) can cause large differences in drug effects both agonist and antagonist and toxic Stratification of patients into genotypes may increase the probability of drug
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