Computational Neurobiology

The immense complexity of the mammalian brain is largely reflected in the underlying molecular signatures of its billions of cells. Brain transcriptome atlases, such as the ones generated by Allen Institute for Brain Science,  provide valuable insights into gene expression patterns across different brain areas throughout the course of development. Such atlases allow researchers to probe the molecular mechanisms which define neuronal identities, neuroanatomy, and patterns of connectivity. Despite the immense effort put into generating such atlases, to answer fundamental questions in neuroscience, an even greater effort is needed to develop methods to probe the resulting high-dimensional multivariate data. DBL contributes by developing various computational methods to analyze brain transcriptome atlases.

Topics we address:

• Spatio-temporal expression pattern analysis.
• Integrating multi-omics neuro-omics data.
• Analyzing brain region- and development-specific isoform.
• Imaging-genetics: Linking SNPs and Imaging data using statistical models.
• Exploring patterns of gene expression through dimensionality reduction using t-SNE.
• Brain transcriptome atlases in translational neurobiology, applications to autism, Parkinson’s, Huntington’s, Migraine, and Duchenne muscular dystrophy.