Chromosomes are masters of organization. These long strings of DNA fold down into an ensemble of compact structures that keep needed parts of the genome accessible while tucking away those that aren't ...

Discover the leading database management systems for enterprises in 2026. Explore key features, pricing, and implementation tips for selecting the best DBMS software to harness your data effectively.

(MENAFN- GlobeNewsWire - Nasdaq) San Francisco, CA, Jan. 12, 2026 (GLOBE NEWSWIRE) -- Java World Mag is issuing this follow-up report to provide additional factual and legal context regarding its ...

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 ...

Abstract: Federated Graph Learning (FGL) demonstrates tremendous potential in distributed graph data analysis and modeling. The rapid growth of graph data and the increasing awareness of privacy ...

A TechRadar article noted that nearly 90% of enterprise information (documents, emails, videos) lies dormant in unstructured systems. This "dark data" isn't just neglected; it's a liability. GenAI ...

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 ...

Neo4j Inc. today announced a new serverless offering that dramatically simplifies the deployment of its graph database offering, making it easier to use with artificial intelligence applications. Most ...

Enterprises have long grappled with data dilemmas, from access management to security and hygiene. Those challenges are now amplified by the rush to add AI, a technology that hinges on a solid data ...

1 School of Biomedical Engineering, Tianjin Medical University, Tianjin, China 2 State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang ...

Abstract: In recent years, Graph Neural Networks (GNNs) have achieved significant success in graph-based tasks. However, they still face challenges in complex scenarios, particularly in integrating ...