Data integration continues to remain a difficult and escalating problem in bioinformatics. The goal of this thesis is to develop a data integration platform that addresses two recurring issues in current data integration methods: 1) the issue of naming and identity and 2) the barrier of entry for general researchers to contribute and perform analysis of data. We have developed a web tool and warehousing system, Booly, that features a simple yet flexible data model coupled with the ability to perform powerful comparative analysis, including the use of Boolean logic to merge datasets together, and an integrated aliasing system to decipher differing names of the same gene or protein. We applied Booly across heterogeneous data sources and identified genes useful in comparing avian and mammalian brain architecture, which were validated by comprehensive in situ hybridization experiments. The Booly paradigm for data storage and analysis should facilitate integration between disparate biological and medical fields and result in novel discoveries that can then be validated experimentally

Abstract Background Data integration is an escalating problem in bioinformatics. We have developed a web tool and warehousing system, Booly, that features a simple yet flexible data model coupled with the ability to perform powerful comparative analysis, including the use of Boolean logic to merge datasets together, and an integrated aliasing system to decipher differing names of the same gene or protein. Furthermore, Booly features a collaborative sharing system and a public repository so that users can retrieve new datasets while contributors can easily disseminate new content. Results We illustrate the uses of Booly with several examples including: the versatile creation of homebrew datasets, the integration of heterogeneous data to identify genes useful for comparing avian and mammalian brain architecture, and generation of a list of Food and Drug Administration (FDA) approved drugs with possible alternative disease targets. Conclusions The Booly paradigm for data storage and analysis should facilitate integration between disparate biological and medical fields and result in novel discoveries that can then be validated experimentally. Booly can be accessed at http://booly.ucsd.edu.

In Down syndrome (DS) or trisomy of chromosome 21, the β-amyloid (Aβ) peptide product of the amyloid precursor protein (APP) is present in excess. Evidence points to increased APP gene dose and Aβ as playing a critical role in cognitive difficulties experienced by people with DS. Particularly, Aβ is linked to the late-life emergence of dementia as associated with neuropathological markers of Alzheimer's disease (AD). At present, no treatment targets Aβ-related pathogenesis in people with DS. Herein we used a vaccine containing the Aβ 1-15 peptide embedded into liposomes together with the adjuvant monophosphoryl lipid A (MPLA). Ts65Dn mice, a model of DS, were immunized with the anti-Aβ vaccine at 5 months of age and were examined for cognitive measures at 8 months of age. The status of basal forebrain cholinergic neurons and brain levels of APP and its proteolytic products were measured. Immunization of Ts65Dn mice resulted in robust anti-Aβ IgG titers, demonstrating the ability of the vaccine to break self-tolerance. The vaccine-induced antibodies reacted with Aβ without detectable binding to either APP or its C-terminal fragments. Vaccination of Ts65Dn mice resulted in a modest, but non-significant reduction in brain Aβ levels relative to vehicle-treated Ts65Dn mice, resulting in similar levels of Aβ as diploid (2N) mice. Importantly, vaccinated Ts65Dn mice showed resolution of memory deficits in the novel object recognition and contextual fear conditioning tests, as well as reduction of cholinergic neuron atrophy. No treatment adverse effects were observed; vaccine did not result in inflammation, cellular infiltration, or hemorrhage. These data are the first to show that an anti-Aβ immunotherapeutic approach may act to target Aβ-related pathology in a mouse model of DS.