Marc Sturm

Long-read genome sequencing resolves complex structural variants in exome-negative developmental and epileptic encephalopathy

This study evaluates the diagnostic value of long-read genome sequencing in DEE patients, finding it particularly effective for resolving complex structural variants not detected by short-read sequencing.

aiDIVA - Diagnostics of Rare Genetic Diseases Using Large Language Models

aiDIVA uses AI and LLMs to prioritize causal genetic variants in rare diseases, achieving high accuracy in identifying top candidates.

Comprehensive reanalysis for CNVs in exome sequencing data from unsolved rare disease cases results in new diagnoses

The paper reanalyzes exome sequencing data from rare disease cases to identify previously undetected copy number variants, resulting in diagnoses for 51 families and partial explanations for 34 individuals.

Advancing molecular, phenotypic and mechanistic insights of FGF14 pathogenic expansions (SCA27B)

This study identifies the complete sequences of pathogenic and non-pathogenic FGF14 repeat expansions in patients with cerebellar ataxia, revealing a lower pathogenic threshold and providing mechanistic insights into disease causation.

Limitations in next-generation sequencing-based genotyping of breast cancer polygenic risk score loci

This study evaluates the accuracy of next-generation sequencing in capturing allele frequencies for polygenic risk score loci in breast cancer, finding significant deviations affecting risk prediction.

BRAIN-MAGNET: A novel functional genomics atlas coupled with convolutional neural networks facilitates clinical interpretation of disease relevant variants in non-coding regulatory elements

The paper develops BRAIN-MAGNET, a convolutional neural network that predicts non-coding regulatory element activity and helps prioritize disease-causing variants in neurogenetic disorders.

Multiomic ALS signatures highlight sex differences and molecular subclusters and identify the MAPK pathway as therapeutic target

The paper performs a multiomic analysis of ALS patients and mouse models to identify sex differences, molecular subclusters, and the MAPK pathway as a therapeutic target.

Genome sequencing and transcriptome profiling in twins discordant for Mayer-Rokitansky-Kuester-Hauser syndrome

This study analyzes genome and transcriptome data from discordant monozygotic twins with Mayer-Rokitansky-Kuster-Hauser syndrome to identify genetic and transcriptional differences.

ClinCNV: multi-sample germline CNV detection in NGS data

ClinCNV detects germline CNVs in NGS data using multi-sample normalization and an algorithm combining circular binary segmentation and Hidden Markov models.