Genotype Phenotype

Genotype-phenotype research aims to understand the complex relationships between an organism's genetic makeup (genotype) and its observable characteristics (phenotype), including disease states. Current research heavily utilizes machine learning, employing diverse architectures like neural networks (including convolutional and kernel-based variants), genetic programming, and graph neural networks to model these relationships, often integrating multi-omics data and incorporating environmental factors. These advanced computational methods are improving the prediction of phenotypic outcomes from genotypes, facilitating the discovery of disease-associated genes and potentially leading to more precise diagnostics and personalized medicine. The field is also actively addressing challenges like disentangling correlation from causation and handling high-dimensional data.