RCytoscape: Tools for Exploratory Network Analysis

Background: Biomolecular pathways and networks are dynamic and complex, and the perturbations to them which cause disease are often multiple, heterogeneous and contingent. Pathway and network visualizations, rendered on a computer or published on paper, however, tend to be static, lacking in detail, and ill-equipped to explore the variety and quantities of data available today, and the complex causes we seek to understand. Results: RCytoscape integrates R (an open-ended programming environment rich in statistical power and datahandling facilities) and Cytoscape (powerful network visualization and analysis software). RCytoscape extends Cytoscape\u27s functionality beyond what is possible with the Cytoscape graphical user interface. To illustrate the power of RCytoscape, a portion of the Glioblastoma multiforme (GBM) data set from the Cancer Genome Atlas (TCGA) is examined. Network visualization reveals previously unreported patterns in the data suggesting heterogeneous signaling mechanisms active in GBM Proneural tumors, with possible clinical relevance. Conclusions: Progress in bioinformatics and computational biology depends upon exploratory and confirmatory data analysis, upon inference, and upon modeling. These activities will eventually permit the prediction and control of complex biological systems. Network visualizations -- molecular maps -- created from an open-ended programming environment rich in statistical power and data-handling facilities, such as RCytoscape, will play an essential role in this progression

Sleight of Hand: Identifying Concealed Information by Monitoring Mouse-Cursor Movements

Organizational members who conceal information about adverse behaviors present a substantial risk to that organization. Yet the task of identifying who is concealing information is extremely difficult, expensive, error-prone, and time-consuming. We propose a unique methodology for identifying concealed information: measuring people’s mouse-cursor movements in online screening questionnaires. We theoretically explain how mouse-cursor movements captured during a screening questionnaire differ between people concealing information and truth tellers. We empirically evaluate our hypotheses using an experiment during which people conceal information about a questionable act. While people completed the screening questionnaire, we simultaneously collected mouse-cursor movements and electrodermal activity—the primary sensor used for polygraph examinations—as an additional validation of our methodology. We found that mouse-cursor movements can significantly differentiate between people concealing information and people telling the truth. Mouse-cursor movements can also differentiate between people concealing information and truth tellers on a broader set of comparisons relative to electrodermal activity. Both mouse-cursor movements and electrodermal activity have the potential to identify concealed information, yet mouse-cursor movements yielded significantly fewer false positives. Our results demonstrate that analyzing mouse-cursor movements has promise for identifying concealed information. This methodology can be automated and deployed online for mass screening of individuals in a natural setting without the need for human facilitators. Our approach further demonstrates that mouse-cursor movements can provide insight into the cognitive state of computer users

APPL1 Associates with TrkA and GIPC1 and is Required for Nerve Growth Factor-Mediated Signal Transduction

The neurotrophin receptor TrkA plays critical roles in the nervous system by recruiting signaling molecules that activate pathways required for the growth and survival of neurons. Here, we report APPL1 as a TrkA-associated protein. APPL1 and TrkA coirnmunoprecipitated in sympathetic neurons. We have identified two routes through which this association can occur. APPL1 was isolated as a binding partner for the TrkA-interacting protein GIPC1 from rat brain lysate by mass spectrometry. The PDZ domain of GIPC1 directly engaged the C-terminal sequence of APPL1. This interaction provides a means through which APPL1 may be recruited to TrkA. In addition, the APPL1 PTB domain bound to TrkA, indicating that APPL1 may associate with TrkA independently of GIPC1. Isolation of endosomal fractions by high-resolution centrifugation determined that APPL1, GIPC1, and phosphorylated TrkA are enriched in the same fractions. Reduction of APPL1 or GIPC1 protein levels suppressed nerve growth factor (NGF)-dependent MEK, extracellular signal-regulated kinase, and AM activation and neurite outgrowth in PC12 cells. Together, these results indicate that GIPC1 and APPL1 play a role in TrkA function and suggest that a population of endosomes bearing a complex of APPL1, GIPC1, and activated TrkA may transmit NGF signals