Apuã César de Miranda Paquola

I am a computational biologist dedicated to analyzing multiple types of biomedical data to gain insight onbrain development and brain disorders. My research group at the Lieber Institute for Brain Developmentfocuses on developing new analytical approaches using machine learning and graph theory to analyzelarge datasets on genotype, gene expression, epigenomics, behavior and clinical data. My group works inclose collaboration with experimentalists, designing experiments to test hypotheses and to generateinformative datasets. We performed a comprehensive analysis of caudate nucleus transcriptome andidentified a genetic link between DRD2 autoreceptor expression and schizophrenia risk (NatureNeuroscience 2022). In the same article, we also developed a deep learning approach based onvariational autoencoders to construct caudate nucleus gene expression networks that highlightinteractions involving schizophrenia risk. My group participates on the Brain Somatic Mosaicism Networkstudying the relationship between somatic mosaicism and brain disorders (Science 2017).My previous work as a postdoctoral researcher in the Gage Lab at the Salk Institute focused on somaticmosaicism in the brain associated with LINE-1 retrotransposons, where my colleagues and I developed anew targeted sequencing and analysis approach for LINE-1 associated variants, and discovered a newclass of somatic deletions associated with LINE-1 in neurotypical brains (Nature Neuroscience 2016, co-first author). In my postdoc, I also participated with experimental design and data analysis on studiesabout brain aging and evolution (Nature 2013). (Source: Lattes Curriculum)