Max Schubach

Uniform processing and analysis of IGVF massively parallel reporter assay data with MPRAsnakeflow

The paper introduces standardized formats and tools for processing MPRA data to improve reproducibility and integration across studies.

Massively parallel characterization and predictive modelling of neuronal regulatory variation

The paper characterizes regulatory variants in human neurons using lentiMPRA and shows that variant effects are influenced by regulatory element activity and sequence context, not population frequency.

Massively parallel characterization of transcriptional regulatory elements in three diverse human cell types

The paper identifies functional cis-regulatory elements in three human cell types using lentiMPRAs and develops predictive models for CRE function.

Evaluation and optimization of sequence-based gene regulatory deep learning models

The paper evaluates and optimizes sequence-based gene regulatory deep learning models using a DREAM Challenge dataset, showing improvements through architectural and training strategy refinements.

The Regulatory Mendelian Mutation score for GRCh38

The paper updates the Regulatory Mendelian Mutation score for GRCh38 and provides a website and API for variant scoring.

The impact of different negative training data on regulatory sequence predictions

This study evaluates how different negative training data affect regulatory sequence prediction models, finding that genomic backgrounds yield better results than shuffled sequences.

parSMURF, a High Performance Computing tool for the genome-wide detection of pathogenic variants

parSMURF is a parallel machine learning tool for detecting pathogenic variants in genomic data, achieving state-of-the-art results with an 80x speed-up over sequential versions.

PEDIA: Prioritization of Exome Data by Image Analysis

The paper introduces an AI-driven method that uses facial images to prioritize exome data, achieving 99% top-10 accuracy in identifying disease-causing genes.

Saturation mutagenesis of disease-associated regulatory elements

The paper performs saturation mutagenesis on disease-associated regulatory elements to assess the functional effects of mutations, revealing variability in transcription factor binding site density and predictive power of conservation scores.

Characterization of Glycosylphosphatidylinositol Biosynthesis Defects by Clinical Features, Flow Cytometry, and Automated Image Analysis

The paper evaluates clinical features, flow cytometry, and facial image analysis to classify GPIBDs and identify gene-specific patterns, finding that facial recognition software is most effective for gene prediction.