We present a novel system that leverages curators in the loop to develop a dataset and model for detecting structure features and functional annotations at residue-level from standard publication text. Our approach involves the integration of data fr...
Computational models have made significant progress in predicting the effect of protein variants. However, deciphering numerous variants of uncertain significance (VUS) located within intrinsically disordered regions (IDRs) remains challenging. To ad...
Patients with advanced idiopathic pulmonary fibrosis (IPF), a complex and incurable lung disease with an elusive pathology, are nearly exclusive candidates for lung transplantation. Improved identification of patient subtypes can enhance early diagno...
Cervical cancer is a common malignant tumor of the female reproductive system and the leading cause of death among women worldwide. The survival prediction method can be used to effectively analyze the time to event, which is essential in any clinica...
Cognitive dysfunction caused by diabetes has become a serious global medical issue. Diabetic kidney disease (DKD) exacerbates cognitive dysfunction in patients, although the precise mechanism behind this remains unclear. Here, we conducted an investi...
BACKGROUND: Wearable sensors are increasingly being explored in health care, including in cancer care, for their potential in continuously monitoring patients. Despite their growing adoption, significant challenges remain in the quality and consisten...
SIGNIFICANCE: Label-free multimodal imaging methods that can provide complementary structural and chemical information from the same sample are critical for comprehensive tissue analyses. These methods are specifically needed to study the complex tum...
Aedes mosquitoes, known as vectors of mosquito-borne diseases, pose significant risks to public health and safety. Modeling the population dynamics of Aedes mosquitoes requires comprehensive approaches due to the complex interplay between biological ...
Machine learning-based approaches are particularly suitable for identifying essential genes as they allow the generation of predictive models trained on features from multi-source data. Gene essentiality is neither binary nor static but determined by...
OBJECTIVE: More and more studies have found that polycystic ovary syndrome (PCOS) is significantly associated with recurrent spontaneous abortion (RSA), but the specific mechanism is not yet clear.
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