Comorbidity—the co-occurrence of multiple diseases in a patient—complicates diagnosis, treatment, and prognosis. Understanding how diseases connect at a molecular level is crucial, especially in aging ...

In this tutorial, we implement Tree-KG, an advanced hierarchical knowledge graph system that goes beyond traditional retrieval-augmented generation by combining semantic embeddings with explicit graph ...

If neural networks are now making decisions everywhere from code editors to safety systems, how can we actually see the specific circuits inside that drive each behavior? OpenAI has introduced a new ...

We aim to build a pre-trained Graph Neural Network (GNN) model on molecules without human annotations or prior knowledge. Although various attempts have been proposed to overcome limitations in ...

Abstract: The rise of graph analytic systems has created a need for ways to measure and compare the capabilities of these systems. Graph analytics present unique scalability difficulties. The machine ...

Fullerenes are hollow carbon molecules where each atom is connected to exactly three other atoms, arranged in pentagonal and hexagonal rings. Mathematically, they can be combinatorially modeled as ...

This article introduces a model-based design, implementation, deployment, and execution methodology, with tools supporting the systematic composition of algorithms from generic and domain-specific ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. The “SmartGraph network-pharmacology investigation platform” (1 ...

We implemented an algorithm, that finds Density Bursting Subgraphs (DBS) in the Facebook Wall Posts dataset. In this dataset, a DBS identifies a fast emerging community of users who actively interact ...

Abstract: The rise of graph analytic systems has created a need for ways to measure and compare the capabilities of these systems. Graph analytics present unique scalability difficulties. The machine ...