A Framework for Comparative Analysis of Gene Expressions and Mutations Linked to Cancer Analysis of the aberrations occurring at the functional sites of genes and proteins is essential to understanding the genomic basis of human disease. There are many data sources that offer rich repository of information on sequence features, but their heterogeneity poses a challenge to developing an intuitive and high-confidence workflow for next-generation sequencing (NGS) data analysis. Moreover, the failure of existing repositories to incorporate results from both small-scale and large-scale studies has inhibited the identification of many novel non-synonymous single-nucleotide variations (nsSNVs). The HIVE (High-performance Integrated Virtual Environment) platform offers integrated and curated sources of nsSNVs and gene expression data from trusted genomic and proteomic repositories and publications. We demonstrate a data-driven functional genomics approach primarily leveraging the HIVE framework to identify priority targets for further investigation in the lab. Additionally, we developed the HIVE Genecast mobile app for Android devices that is annotated with our priority target results to provide scientists with access to gene sequence information while away from their workspaces.
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|School:||The George Washington University|
|Department:||Genomics and Bioinformatics|
|School Location:||United States -- District of Columbia|
|Source:||MAI 53/01M(E), Masters Abstracts International|
|Subjects:||Genetics, Biochemistry, Bioinformatics|
|Keywords:||Cancer, Genomics, Hive, Human disease, Mobile app, Mutations|
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