Joseph A. Marsh

The paper describes a structured curation process for the Gene2Phenotype project to systematically evaluate and organize genomic disease-gene relationships.

This study shows that whole genome sequencing (WGS) can achieve a high diagnostic rate for primary ciliary dyskinesia by identifying structural variants and novel disease genes.

This study benchmarks 55 variant effect predictors using deep mutational scanning data from 26 human proteins, finding that unsupervised methods like EVE and ESM-1v perform best, while supervised methods like VARITY show improved handling of data circularity.

This study investigates EZH2 variants linked to Weaver syndrome, showing they cause dominant negative effects on H3K27 methylation, altering chromatin states and contributing to developmental disorders.

The paper shows that cotranslational protein complex assembly is less common for subunits with dominant-negative mutations and develops a model to predict such mutations.

The paper compares protein stability predictors with DMS-derived functional scores, finding FoldX and Rosetta show strong correlations, especially when considering intermolecular interactions.

The paper investigates tubulin mutations' molecular mechanisms and their phenotypic effects, finding that current computational methods poorly predict their pathogenicity due to dominant-negative and gain-of-function mechanisms.

The paper shows that large protein interfaces evolve to facilitate cotranslational assembly by comparing interface sizes in bacterial, yeast, and human complexes.

The paper examines how mutations at different protein interfaces correlate with disease, finding significant variation in pathogenicity across interface types and highlighting discrepancies in computational prediction tools.

The paper examines how different mutation types affect protein structure and finds that non-LOF mutations are underpredicted by current tools.

This study evaluates 12 protein stability predictors for identifying pathogenic missense mutations and finds FoldX performs best, though structural predictors are less effective than variant effect predictors overall.

This study benchmarks 46 variant effect predictors using deep mutational scanning data, finding DMS superior to top predictors and highlighting DeepSequence's effectiveness.

The paper analyzes how homomer symmetry relates to protein function, finding distinct functional associations with different symmetry groups, particularly highlighting metabolic enzymes forming dihedral complexes linked to allosteric regulation.