Computational prediction of blood-brain barrier (BBB) permeability has emerged as a vital alternative to traditional experimental assays, which are often resource-intensive and low-throughput to meet the demands of early-stage drug discovery. While e... read more
Foundational models that learn the language of molecules are essential for accelerating the material and drug discovery. These self-learning models can be trained on a large number of unlabelled molecules, enabling applications like property predicti... read more
Understanding continuous conformational variability of biomolecular complexes at atomic resolution is essential for linking structure to function, but remains challenging for cryo-electron tomography (cryo-ET) data due to high noise and missing-wedge... read more
Recent advances in spatial omics enable high-resolution, multiplexed in situ imaging of gene and protein expression. A major challenge in analyzing these data is cell annotation, especially in complex tissues with limited molecular markers, overlappi... read more
Signal detection theory posits that subjects in two-stimulus, two-choice discrimination tasks decide by comparing random samples of an evidence variable to a static decision criterion. While the core assumptions of the theory have received ample expe... read more
Accurately predicting chemotherapy response remains a major challenge in precision oncology. Although machine-learning models based on tumour omics data have shown promise, the majority of existing studies are trained and evaluated on pre-clinical ce... read more
Accurate identification of CRISPR arrays is essential for studying prokaryotic adaptive immunity, yet existing tools struggle with short-read sequencing data and arrays containing degenerate repeats. These limitations restrict CRISPR analysis in meta... read more
This dataset contains electroencephalography (EEG) and electromyography (EMG) recordings acquired during the execution of specific motor tasks aimed at eliciting movement-related cortical potentials (MRCP). The goal is to provide an accessible resour... read more
Nitrite (NO2-) and copper (Cu2+) ions are widespread environmental pollutants that threaten both ecosystem integrity and human health, yet their simultaneous on-site detection remains challenging. To address this, we developed a dual-emissive lumines... read more
PURPOSE OF REVIEW: Trauma care demands rapid decision-making under uncertainty and time pressure, where maintaining situational awareness becomes challenging. Artificial intelligence offers potential to augment clinical judgment by processing complex... read more
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