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PINNACLE, a novel computational model designed to enhance our understanding of protein function within specific cellular contexts. The paper presents a significant advancement in computational biology by applying geometric deep learning to address the limitation of existing models, which often overlook the contextual variability of protein functions. Below is a comprehensive review addressing key questions pertinent to evaluating research in computational biology, molecular biology, and deep learning. 1. What is the research question, and why is it important? The central question of this research is how to accurately model protein interactions in ways that account for the unique cellular and tissue environments where proteins operate. Unlike traditional models that generate a single, context-free protein representation, this study investigates the benefits of creating context-specific protein representations across various cell types. This question is of paramount importance in fields like molecular biology and therapeutic development, as proteins often display distinct functions in different cellular environments, influencing the success of therapeutic targets. By embedding protein interaction data within cell-specific contexts, this work aims to bridge a critical gap in understanding how proteins behave across different biological settings, providing valuable insights into precision medicine and the development of targeted therapies. ...