Presented by: Elissa Chesler, Ph.D.

• Disorders of the central nervous system pose many unique challenges for bioinformatics. Brain and behavioral disorders are difficult to classify and often have highly overlapping characteristics.  Biological mechanisms of behavior are shared across multiple disorders. The relationship of behavioral disorders and human behavioral traits to model organism traits is also uncertain. These challenges may hinder progress in the diagnosis and treatment of brain and behavioral disorders. Using an integrative multi-omics strategy, it is possible to find relationships among disorders, evaluate evidence across diverse experiments, and identify conservation of disease related neurobiological mechanisms across species.  As data heterogeneity increases, analyses become less quantitative and more generalizable to a greater range of experimental platforms and populations. Genomic and systems genetic studies are used to find molecular correlates of behavioral traits and neurobehavioral processes in humans and mice. Statistical and combinatorial approaches allow the discovery of common genetic and genomic mechanisms across diverse traits within and across species.  These approaches are implemented in integrative data resources and modular analysis tool sets in GeneWeaver and other systems. Together they enable data driven discovery of the shared mechanisms of behavioral traits.

Presented by: Elissa Chesler, Ph.D.

• Disorders of the central nervous system pose many unique challenges for bioinformatics. Brain and behavioral disorders are difficult to classify and often have highly overlapping characteristics.  Biological mechanisms of behavior are shared across multiple disorders. The relationship of behavioral disorders and human behavioral traits to model organism traits is also uncertain. These challenges may hinder progress in the diagnosis and treatment of brain and behavioral disorders. Using an integrative multi-omics strategy, it is possible to find relationships among disorders, evaluate evidence across diverse experiments, and identify conservation of disease related neurobiological mechanisms across species.  As data heterogeneity increases, analyses become less quantitative and more generalizable to a greater range of experimental platforms and populations. Genomic and systems genetic studies are used to find molecular correlates of behavioral traits and neurobehavioral processes in humans and mice. Statistical and combinatorial approaches allow the discovery of common genetic and genomic mechanisms across diverse traits within and across species.  These approaches are implemented in integrative data resources and modular analysis tool sets in GeneWeaver and other systems. Together they enable data driven discovery of the shared mechanisms of behavioral traits.