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Overview of pros and cons for each method

overview of pros and cons for each method

In this screencast, Conor summarises three primary methods used for genotype-phenotype correlations in antimicrobial resistance research: in-vitro, in-silico, and epidemiological approaches.

In-vitro studies involve controlled laboratory experiments where specific genes are knocked in or out, or bacteria are evolved in the presence of a drug to identify resistance mechanisms. These studies provide precise correlations but are costly, time-consuming, and may not always be generalizable to other strains or clinical settings.

In-silico studies utilize computational models to predict protein-drug interactions and possible resistance mechanisms. While these methods allow for hypothesis generation and exploration of unknown mutations, they require extensive information about protein structures and drug-binding sites, which is still a developing field.

Epidemiological studies focus on analyzing large clinical datasets to identify correlations between the presence of specific genes or mutations and resistance patterns. These studies are valuable for generating hypotheses and meta-analyses but require large, standardized datasets and are limited in detecting complex interactions between multiple genes or mutations. Furthermore, inconsistencies in phenotypic data collection methods can limit the comparability of results.

Conor concludes by highlighting the current strengths and limitations of these methods and hints at future advancements in genotype-phenotype studies, such as the use of AI and machine learning to improve correlation studies and leverage big data in the field.

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Antimicrobial Databases and Genotype Prediction: Data Sharing and Analysis

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