Johannes Hingerl

Scooby-2: fine-tuning AlphaGenome for single-cell genomic track prediction

Scooby-2 fine-tunes AlphaGenome to predict single-cell genomic tracks, improving correlation and variant effect prediction compared to Scooby and AlphaGenome.

Phenotypes of ultra-rare variant carriers benchmark variant effect scores

The paper benchmarks variant effect scores using UK Biobank data on ultra-rare variant carriers, showing coding and splicing scores better predict protein abundance and traits than transcriptional regulation models.

Nona: A unifying multimodal masking framework for functional genomics

Nona is a multimodal masking framework that unifies sequence-to-function models, language models, and generative models for functional genomics, improving predictions and revealing privacy vulnerabilities in ATAC-seq data.

scooby: Modeling multi-modal genomic profiles from DNA sequence at single-cell resolution

scooby models scRNA-seq and scATAC-seq data from DNA sequence to capture cell-specific gene regulation and variant effects.

Flashzoi: An enhanced Borzoi model for accelerated genomic analysis

Flashzoi improves the Borzoi model by using rotary positional encodings and FlashAttention-2, achieving faster training and inference with reduced memory usage while maintaining accuracy in genomic analysis.

Nucleotide dependency analysis of DNA language models reveals genomic functional elements

This paper introduces nucleotide dependency analysis to identify genomic functional elements, showing it outperforms existing methods in detecting regulatory elements and RNA structures.

Species-aware DNA language models capture regulatory elements and their evolution

This paper introduces species-aware DNA language models that capture regulatory elements and their evolution across 800 species, showing improved prediction and motif discovery.

Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing

This paper introduces Spectralis, a deep learning method for de novo peptide sequencing that improves sensitivity and precision in tandem mass spectrometry.