Abstract: Graph-based approaches have been widely adopted in biomedical applications for modeling multimodal data, particularly in the accurate diagnosis and effective treatment of brain disorders.

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Every year, designers at Pew Research Center create hundreds of charts, maps and other data visualizations. We also help make a range of other digital products, from “scrollytelling” features to ...

Structure Therapeutics’ stock soared toward an 18-month high in early Monday trading, after mid-stage data for its oral daily GLP-1 receptor appeared comparable to that of one of Eli Lilly’s ...

Structure Therapeutics is developing a daily GLP-1 receptor pill called aleniglipron. Structure Therapeutics' stock soared toward an 18-month high in early Monday trading, after mid-stage data for its ...

Placebo-adjusted mean weight loss of 11.3% (27.3 lbs) with 120 mg dose in the 36-week Phase 2b ACCESS study with a 10.4% adverse event-related treatment discontinuation Placebo-adjusted mean weight ...

Graphs are everywhere. From technology to finance, they often model valuable information such as people, networks, biological pathways and more. Often, scientists and technologists need to come up ...

CrowdStrike Holdings Inc.’s Enterprise Graph solution is the company’s latest defense against cyberattacks fueled by agentic artificial intelligence. The innovation is part of the company’s new ...

1 School of Big Data and Statistics, Guizhou University of Finance and Economics, Guiyang, China 2 Audit Office, Guizhou University of Finance and Economics, Guiyang, China The performance of Dynamic ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...