Sherry L. Jenkins

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Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated(More)
We developed a model of 545 components (nodes) and 1259 interactions representing signaling pathways and cellular machines in the hippocampal CA1 neuron. Using graph theory methods, we analyzed ligand-induced signal flow through the system. Specification of input and output nodes allowed us to identify functional modules. Networking resulted in the(More)
The global relationship between drugs that are approved for therapeutic use and the human genome is not known. We employed graph-theory methods to analyze the Federal Food and Drug Administration (FDA) approved drugs and their known molecular targets. We used the FDA Approved Drug Products with Therapeutic Equivalence Evaluations 26(th) Edition Electronic(More)
Because of the complexity inherent in biological systems, many researchers frequently rely on a combination of global analysis and computational approaches to gain insight into both (i) how interacting components can produce complex system behaviors, and (ii) how changes in conditions may alter these behaviors. Because the biological details of a particular(More)
Signaling from G(i/o)-coupled G protein-coupled receptors (GPCRs), such as the serotonin 1B, cannabinoid 1, and dopamine D2 receptors, inhibits cAMP production by adenylyl cyclases and activates protein kinases, such as Src, mitogen-activated protein kinases 1 and 2, and Akt. Activation of these protein kinases results in stimulation of neurite outgrowth in(More)
Studies of cellular signaling indicate that signal transduction pathways combine to form large networks of interactions. Viewing protein-protein and ligand-protein interactions as graphs (networks), where biomolecules are represented as nodes and their interactions are represented as links, is a promising approach for integrating experimental results from(More)
Word-clouds recently emerged on the web as a solution for quickly summarizing text by maximizing the display of most relevant terms about a specific topic in the minimum amount of space. As biologists are faced with the daunting amount of new research data commonly presented in textual formats, word-clouds can be used to summarize and represent biological(More)
The application of proteomic techniques to neuroscientific research provides an opportunity for a greater understanding of nervous system structure and function. As increasing amounts of neuroproteomic data become available, it is necessary to formulate methods to integrate these data in a meaningful way to obtain a more comprehensive picture of neuronal(More)
Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through(More)
119 ISSN 1462-2416 10.2217/PGS.12.186 © 2013 Future Medicine Ltd Pharmacogenomics (2013) 14(2), 119–122 “[The] gene-expression signature-based approach to drug discovery adds a new dimension to drug–drug similarity networks, and such additions can potentially be used to find new connections between drugs, and molecular pathways or molecular networks, as(More)