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Full-Text Articles in Medical Genetics
Cocaine Enhances Hiv-1 Infectivity In Monocyte Derived Dendritic Cells By Suppressing Microrna-155, Jessica Napuri, Sudheesh Pilakka-Kanthikeel, Andrea Raymond, Marisela Agudelo, Adriana Yndart-Arias, Madhavan Nair, Shailendra K. Saxena
Cocaine Enhances Hiv-1 Infectivity In Monocyte Derived Dendritic Cells By Suppressing Microrna-155, Jessica Napuri, Sudheesh Pilakka-Kanthikeel, Andrea Raymond, Marisela Agudelo, Adriana Yndart-Arias, Madhavan Nair, Shailendra K. Saxena
HWCOM Faculty Publications
Cocaine and other drugs of abuse increase HIV-induced immunopathogenesis; and neurobiological mechanisms of cocaine addiction implicate a key role for microRNAs (miRNAs), single-stranded non-coding RNAs that regulate gene expression and defend against viruses. In fact, HIV defends against miRNAs by actively suppressing the expression of polycistronic miRNA cluster miRNA-17/92, which encodes miRNAs including miR-20a. IFN-g production by natural killer cells is regulated by miR-155 and this miRNA is also critical to dendritic cell (DC) maturation. However, the impact of cocaine on miR-155 expression and subsequent HIV replication is unknown. We examined the impact of cocaine on two miRNAs, miR-20a and …
Transcription Factor Binding Profiles Reveal Cyclic Expression Of Human Protein-Coding Genes And Non-Coding Rnas, Chao Cheng, Matthew Ung, Gavin D. Grant, Michael L. Whitfield
Transcription Factor Binding Profiles Reveal Cyclic Expression Of Human Protein-Coding Genes And Non-Coding Rnas, Chao Cheng, Matthew Ung, Gavin D. Grant, Michael L. Whitfield
Dartmouth Scholarship
Cell cycle is a complex and highly supervised process that must proceed with regulatory precision to achieve successful cellular division. Despite the wide application, microarray time course experiments have several limitations in identifying cell cycle genes. We thus propose a computational model to predict human cell cycle genes based on transcription factor (TF) binding and regulatory motif information in their promoters. We utilize ENCODE ChIP-seq data and motif information as predictors to discriminate cell cycle against non-cell cycle genes. Our results show that both the trans- TF features and the cis- motif features are predictive of cell cycle genes, and …