Sercan Aygün

HyperSketch: de Bruijn graph sketching for genomic similarity estimation with Hyperdimensional Computing

HyperSketch provides a structure-aware genomic similarity method using de Bruijn graphs and Hyperdimensional Computing, achieving high-resolution strain clustering and deep evolutionary scaling.

Predicting the toxicity of chemical compounds via Hyperdimensional Computing

This paper uses Hyperdimensional Computing to predict chemical compound toxicity efficiently, showing it can classify compounds as toxic or non-toxic with computational advantages over traditional methods.

A novel Vector-Symbolic Architecture for graph encoding and its application to viral pangenome-based species classification

The paper introduces a Vector-Symbolic Architecture for encoding viral pangenomes and evaluates its effectiveness in species classification, finding that a flat species-level model outperforms genus-level and hierarchical approaches.