Maja Bućan

This study investigates the impact of NRXN1 intronic deletions on early cortical development using hiPSCs, finding altered isoform expression and dendritic morphology.

The paper proposes an IBD pruning algorithm using pedigree information to reduce false positives in IBD segment detection for endogamous populations.

The paper identifies sleep and activity patterns associated with autism spectrum disorder using wearable data and machine learning.

This paper introduces an algorithm called thread to reconstruct ancestral haplotypes in endogamous populations using pedigree and genotype data, finding it can reconstruct 79% of haplotypes for 224 ancestral individuals per chromosome.

Integrating expression, allelic expression and splicing across tissues identifies rare variants with relevance to traits.

The paper integrates gene essentiality data from human and mouse screens to classify genes into FUSIL categories, identifying developmental lethal genes associated with rare diseases.

The paper evaluates polygenic risk scores for psychiatric disorders in electronic health records, finding cross-trait associations and confirming genetic architecture from large consortia.

This study identifies genetic pleiotropy between bipolar disorder and metabolic/endocrine traits in a multigenerational Amish pedigree using imputed WGS and polygenic risk scores.

The paper shows that rare secondary mutations in functionally intolerant genes affect the expressivity of neurodevelopmental disorders in individuals with primary mutations.

The paper introduces PennZzz, an algorithm that estimates sleep and wake states from wrist-worn accelerometry data, showing high accuracy in detecting wake episodes compared to polysomnography.