Maren Lang

BenchMHC reproduces and evaluates pMHC presentation models using public data, showing improvements in prediction accuracy and speed.

The paper introduces SegmentNT, a DNA foundation model for genome annotation, achieving state-of-the-art performance in identifying 14 genic and regulatory elements across species.

ChatNT is a conversational agent that understands biological sequences and achieves state-of-the-art results on genomics tasks while being accessible to non-coders.

FrameDiPT is a diffusion model for protein structure inpainting that recovers masked sections using sequence and structural context, achieving comparable accuracy to existing models with limited data.

LightMHC predicts full-atom pMHC structures from sequences using a lightweight model with attention mechanisms, achieving comparable performance to AlphaFold 2 and ESMFold with faster speed.

The paper introduces a graph neural network for peptide-MHC structure prediction, achieving accuracy comparable to AlphaFold 2 with significantly fewer parameters.