The brain doesn't merely register time—it structures it, according to new research from the Kavli Institute for Systems ...

Pipeline Graph now extends drug discovery research beyond biomedical information to include competitive intelligence – all with a single platform that fits within scientists' existing workflows.

Pursuing artificial intelligence for biomedical science, a.k.a. AI Scientist, draws increasing attention, where one common approach is to build a copilot agent driven by Large Language Models (LLMs).

The ESCARGOT model combines large language models with a dynamic "graph of thoughts" and biomedical knowledge graphs—an approach that was shown to improve output reliability and reduce inaccuracies.

The prediction of drug-target interactions (DTIs) has emerged as a vital step in drug discovery. Recently, biomedical knowledge graph enables the utilization of multi-omics resources for modelling ...

Understand the building blocks of knowledge graphs – entities, relationships and attributes – and how they relate to information retrieval.

Harvard Medical School has unveiled MedAI, a new knowledge graph-based agent set to transform the landscape of medical question-answering. This innovative tool addresses the critical shortcomings ...

Knowledge graphs (KGs) offer unique advantages in processing complex biological data and inferring new relationships. Existing biomedical KGs primarily focus on tasks such as drug repositioning and ...