Systems biology and the availability of genomic data have revolutionized our ability to identify the underlying biological mechanisms of diverse diseases and disorders of behavior. Indeed it is becoming within our reach to reclassify diseases based on biological substrate, rather than external manifestation. Using combinatorial, graph-centered approaches, we are able to infer relations among behavioral disorders, addiction-related phenotypes and causative pathways based on gene-phenotype associations. We integrate knowledge of biological functions based on associated molecular networks using The Ontological Discovery Environment, our web based software system designed to enable biologists to perform integrated analysis of phenotype centered genomic data. We make use of advances in database design, algorithms, and advanced mouse resources. In this proposal, we address all three of these areas, and propose to demonstrate our tools for the study of relations among stress, anxiety, psychological disorders and the sensitivity toward and use of drugs and alcohol. Our findings will be validated through the use of mouse models. The three aims of the project are to develop a large data repository for behavioral neuroscience and data structures that more efficiently enable the use of databases to represent graphical network data, to develop algorithms for the analysis of integrated gene centered data across species and experimental platforms to incorporate these developments into a Web-based software system, and to use this tool to find genes underlying relationships between multiple abused substances and behavior.
A wealth of data is being generated that associates multiple genes to multiple behavioral disorders and addiction-related phenotypes. The Ontological Discovery Environment project enables the integration of this data across species and experimental systems based on gene-phenotype associations. The methods and software we develop will enable enhanced understanding of the relationships among behavioral traits and disorders of addiction and of the underlying molecular mechanisms underlying classes of diseases. We will identify and test the role of specific genes in drug addiction. Our methods will also facilitate the mapping of research in non-human model organisms onto human disease. A major component of this effort is software development and training to ensure that the technical advances are translated into deliverable tools for the research community to perform similar analyses.
|Hagan, Ronald D; Langston, Michael A; Wang, Kai (2016) Lower Bounds on Paraclique Density. Discrete Appl Math 204:208-212|
|Young, E E; Bryant, C D; Lee, S E et al. (2016) Systems genetic and pharmacological analysis identifies candidate genes underlying mechanosensation in the von Frey test. Genes Brain Behav 15:604-15|
|Bubier, Jason A; Wilcox, Troy D; Jay, Jeremy J et al. (2016) Cross-Species Integrative Functional Genomics in GeneWeaver Reveals a Role for Pafah1b1 in Altered Response to Alcohol. Front Behav Neurosci 10:1|
|McGuier, Natalie S; Griffin 3rd, William C; Gass, Justin T et al. (2016) Kv7 channels in the nucleus accumbens are altered by chronic drinking and are targets for reducing alcohol consumption. Addict Biol 21:1097-1112|
|Clark, Ryan S; Pellom, Samuel T; Booker, Burthia et al. (2016) Validation of research trajectory 1 of an Exposome framework: Exposure to benzo(a)pyrene confers enhanced susceptibility to bacterial infection. Environ Res 146:173-84|
|Baker, Erich; Bubier, Jason A; Reynolds, Timothy et al. (2016) GeneWeaver: data driven alignment of cross-species genomics in biology and disease. Nucleic Acids Res 44:D555-9|
|Wang, Kai; Phillips, Charles A; Saxton, Arnold M et al. (2015) EntropyExplorer: an R package for computing and comparing differential Shannon entropy, differential coefficient of variation and differential expression. BMC Res Notes 8:832|
|Bubier, Jason A; Phillips, Charles A; Langston, Michael A et al. (2015) GeneWeaver: finding consilience in heterogeneous cross-species functional genomics data. Mamm Genome 26:556-66|
|Padula, Audrey E; Griffin 3rd, William C; Lopez, Marcelo F et al. (2015) KCNN Genes that Encode Small-Conductance Ca2+-Activated K+ Channels Influence Alcohol and Drug Addiction. Neuropsychopharmacology 40:1928-39|
|Schoenrock, Andrew; Samanfar, Bahram; Pitre, Sylvain et al. (2014) Efficient prediction of human protein-protein interactions at a global scale. BMC Bioinformatics 15:383|
Showing the most recent 10 out of 30 publications