Global economic shocks such as the 2008 financial crisis or recent trade escalations between the United States and China have exposed the complexity of interdependent economies and the need for systemic, multi-agent analysis. However, most regional e... read more
Monotherapy cancer drug response prediction (DRP) models predict the response of a cell line to a given drug. Analyzing these models' performance includes assessing their ability to predict the response of cell lines to new drugs, i.e., drugs that ar... read more
Our ability to generalize abstract rules to new situations is a cognitive hallmark, yet its neural basis is unclear. We identified a thalamocortical circuit essential for this process in mice. During a cross-modal rule transfer task, medial prefronta... read more
CO2 emissions from lakes play a crucial role in the global carbon cycle, yet their long-term dynamics remain poorly constrained. Here, leveraging a compiled lake CO2 flux dataset, machine learning model, and lake area data, we demonstrated a nationwi... read more
Coastal flooding is increasing, with accelerating impacts ahead. Its impact, however, can be mitigated through proactive risk management, requiring comprehensive risk assessment. Using the US Gulf and Atlantic Coasts (USGAC) as a test bed, this study... read more
Analyses of brain sizes across mammalian taxonomic groups reveal a consistent pattern of covariation between major brain components, including a robust inverse relationship between the limbic system and the neocortex. To find the functional basis of ... read more
Human fingers exhibiting remarkable dexterity are ideal for natural human-machine interaction. Traditional methods require at least one device per finger and extensive labeled data, often limiting models to a single user and task. Here, we propose a ... read more
Weather forecasting plays a vital role in today's society, from agriculture and logistics to predicting the output of renewable energies and preparing for extreme weather events. Deep learning weather forecasting models trained with the next state pr... read more
Accurately modeling noncovalent interactions (NCIs) involving charged systems remains an outstanding challenge in density functional theory (DFT), with implications across natural and life sciences, engineering, e.g., in biochemistry, catalysis, and ... read more
Cryptic binding sites offer opportunities to modulate targets previously considered "undruggable." However, the scarcity of validated examples limits the development of predictive tools. Here, we introduce CryptoBank, a large-scale database of crypti... read more
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