MS-BioGraphs: Sequence Similarity Graph Datasets

Understand

Progress in High-Performance Computing in general, and High-Performance Graph Processing in particular, is highly dependent on the availability of publicly-accessible, relevant, and realistic data sets.

• To ensure continuation of this progress, we (i) investigate and optimize the process of generating large sequence similarity graphs as an HPC challenge and (ii) demonstrate this process in creating MS-BioGraphs, a new family of publicly available real-world edge-weighted graph datasets with up to $2.5$ trillion edges, that is, $6.6$ times greater than the largest graph published recently.
• The largest graph is created by matching (i.e., all-to-all similarity aligning) $1.7$ billion protein sequences.
• The MS-BioGraphs family includes also seven subgraphs with different sizes and direction types.