Motivation: Multiple high-throughput approaches have recently been developed and allowed the discovery of enhancers on a genome scale in a single experiment. However, the datasets generated from these approaches are not fully utilized by the research community due to technical challenges such as lack of consensus enhancer annotation and integrative analytic tools. Results: We developed an interactive database, EnhancerAtlas, which contains an atlas of 2,534,123 enhancers for 105 cell/tissue types. A consensus enhancer annotation was obtained for each cell by summation of independent experimental datasets with the relative weights derived from a cross-validation approach. Moreover, EnhancerAtlas provides a set of useful analytic tools that allow users to query and compare enhancers in a particular genomic region or associated with a gene of interest, and assign enhancers and their target genes from a custom dataset. Availability and Implementation: The database with analytic tools is available at http://www.enhan ceratlas.org/.

Exact solutions are derived for an n-dimensional radial wave equation with a general power nonlinearity. The method, which is applicable more generally to other nonlinear PDEs, involves an ansatz technique to solve a first-order PDE system of group-invariant variables given by group foliations of the wave equation, using the one-dimensional admitted point symmetry groups. (These groups comprise scalings and time translations, admitted for any nonlinearity power, in addition to space-time inversions admitted for a particular conformal nonlinearity power.) This is shown to yield not only group-invariant solutions as derived by standard symmetry reduction, but also other exact solutions of a more general form. In particular, solutions with interesting analytical behavior connected with blow-ups as well as static monopoles are obtained.  2004 Elsevier Inc. All rights reserved.

No abstract

BackgroundScaffold proteins play a critical role in an increasing number of biological signaling processes, including simple tethering mechanism, regulating selectivity in pathways, shaping cellular behaviors. While many databases document the signaling pathways, few databases are devoted to the scaffold proteins that medicate signal transduction.ResultsHere, we have developed a user-friendly database, ScaPD, to describe computationally predicted, experimentally validated scaffold proteins and associated signaling pathways. It currently contains 273 scaffold proteins and 1118 associated signaling pathways. The database allows users to search, navigate and download the scaffold protein-mediated signaling networks.ConclusionsManually curated and predicted scaffold protein data will be a foundation for further investigation of the scaffold protein in the signal transduction. With maintained up-to-date data, ScaPD (http://bioinfo.wilmer.jhu.edu/ScaPD) will be a valuable resource for understanding how individual signaling pathways are regulated.

No abstract