Nicolas Traut

This study shows that neocortical geometry at birth predicts adult cortical folding patterns and sulcal-gyral fate, suggesting geometry provides positional information alongside molecular signals.

The paper introduces a multiscale resource integrating genetics, brain imaging, and clinical data from autistic individuals and their relatives to explore genetic and neurobiological patterns in autism.

The study uses MRI data from 70 primate species to show that neocortical folding and organisation depend on mechanical morphogenesis, not just genetics and experience.

This study evaluates multitrait GWAS for brain MRI phenotypes, showing predictable gains over univariate GWAS and proposing data-driven strategies for phenotype selection.

The paper uses multitrait GWAS to identify genetic links between MRI brain volume phenotypes and psychiatric disorders, finding significant associations with ADHD and schizophrenia.

The paper studies cerebellar folding diversity and evolution across 56 mammalian species using histological data and phylogenetic methods, finding stabilizing selection and correlations between cerebellar and cerebral anatomy.

BioConvert simplifies life science data format conversion by aggregating tools and providing a unified interface, supporting 50 formats and 100 conversions.

This paper replicates previous findings of differences in grey-white matter contrast in autism spectrum disorders using open data and finds no significant differences.

The paper maps the odds ratio for autism associated with rare LoF variants in autism-associated genes and shows sub-diagnostic effects in undiagnosed individuals.

This study examines the genomic architecture of neuroanatomical diversity using SNP data and MRI, finding polygenic influences and environmental factors affecting brain asymmetry.

This paper conducts a meta-analysis and ABIDE cohort analysis to investigate cerebellar volume differences in autism, finding weak associations and potential publication bias.

The paper presents a meta-analytic approach to combine variance ratios from different studies to produce more robust estimates, addressing the issue of wide confidence intervals in small studies.