In tandem, graph algorithms have evolved to employ spectral methods and matrix congruence techniques that enable the analysis of complex networks and discrete structures.

Graph algorithms and network analysis form the backbone of modern computational techniques used to decode the complex structures and dynamic behaviours exhibited by diverse real-world networks.

Graph analytics is a hot topic, but what does it mean? At the DC GraphTour, I learned the difference between graph queries, graph algorithms, and graph analytics. Next up: San Francisco GraphTour.

Our research is focused on graph algorithms, from both a theoretical perspective, and a practical perspective motivated by real-world problems in Bioinformatics, such as genome sequencing technologies ...

Scalable Graph Algorithms for Bioinformatics using Structure, Parameterization and Dynamic Updates, ERC Consolidator Grant, 9/2025-8/2030 Sequencing technologies have developed to be cheap and ...

Nov. 11, 2021 — TigerGraph, provider of the leading graph analytics platform, has announced its enhanced Graph Data Science Library (previously named the GSQL Graph Algorithm Library.) This latest ...

Refining with colors Mathematicians have developed various strategies to compare graphs. Since the 1970s, algorithms have been able to test graph isomorphism, but in exponential time.

Today Memgraph, the streaming graph application platform, announced Memgraph 2.0, the public launch of its source-available platform, making it easy f ...

Graph database and analytics software company TigerGraph has expanded its data science library to more than 50 algorithms.