Summary Scholars worldwide leverage science gateways/virtual research environments (VREs) for a wide variety of research and education endeavors spanning diverse scientific fields. Evaluating the value of a given science gateway/VRE to its constituent community is critical in obtaining the financial and human resources necessary to sustain operations and increase adoption in the user community. In this article, we feature a variety of exemplar science gateways/VREs and detail how they define impact in terms of, for example, their purpose, operation principles, and size of user base. Further, the exemplars recognize that their science gateways/VREs will continuously evolve with technological advancements and standards in cloud computing platforms, web service architectures, data management tools and cybersecurity. Correspondingly, we present a number of technology advances that could be incorporated in next‐generation science gateways/VREs to enhance their scope and scale of their operations for greater success/impact. The exemplars are selected from owners of science gateways in the Science Gateways Community Institute (SGCI) clientele in the United States, and from the owners of VREs in the International Virtual Research Environment Interest Group (VRE‐IG) of the Research Data Alliance. Thus, community‐driven best practices and technology advances are compiled from diverse expert groups with an international perspective to envisage futuristic science gateway/VRE innovations.

Motivation: High-quality phylogenetic placement of sequence data has the potential to greatly accelerate studies of the diversity, systematics, ecology and functional biology of diverse groups. We developed the Tree-Based Alignment Selector (T-BAS) toolkit to allow evolutionary placement and visualization of diverse DNA sequences representing unknown taxa within a robust phylogenetic context, and to permit the downloading of highly curated, single- and multi-locus alignments for specific clades. Results: In its initial form, T-BAS v1.0 uses a core phylogeny of 979 taxa (including 23 outgroup taxa, as well as 61 orders, 175 families and 496 genera) representing all 13 classes of largest subphylum of Fungi-Pezizomycotina (Ascomycota)-based on sequence alignments for six loci (nr5.8S, nrLSU, nrSSU, mtSSU, RPB1, RPB2 ). T-BAS v1.0 has three main uses: (i) Users may download alignments and voucher tables for members of the Pezizomycotina directly from the reference tree, facilitating systematics studies of focal clades. (ii) Users may upload sequence files with reads representing unknown taxa and place these on the phylogeny using either BLAST or phylogeny-based approaches, and then use the displayed tree to select reference taxa to include when downloading alignments. The placement of unknowns can be performed for large numbers of Sanger sequences obtained from fungal cultures and for alignable, short reads of environmental amplicons. (iii) User-customizable metadata can be visualized on the tree. Availability and Implementation: T-BAS Version 1.0 is available online at http://tbas.hpc.ncsu.edu . Registration is required to access the CIPRES Science Gateway and NSF XSEDE's large computational resources. Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.

Over the last fifteen years, science gateways have proven to be fertile ground for cyberinfrastructure research, while at the same time dramatically increasing the usage and accessibility of cyberinfrastructure to scientists and educators. Gateway developers, however, still face many challenges in building and operating these complex infrastructures that address the dynamic and emerging challenges of computational infrastructure. Through the XSEDE Science Gateway Program, we propose to solicit information on the knowledge, experience, and software from widely used science gateways. We will compile the information into a “Science Gateway Cookbook” which will democratize the experiences in developing, operating, and sustaining science gateways. We hope this will be a good literature reference and also avoid some repetition in the development process.

This paper describes an approach to image modelling using interscale phase relationships of wavelet coefficients for use in image estimation applications. The method is based on the dual tree complex wavelet transform, but a phase rotation is applied to the coefficients to create complex "derotated" coefficients. These derotated coefficients are shown to have increased correlation compared to standard wavelet coefficients near edge and ridge features allowing improved signal estimation in these areas. The nature of the benefits brought by the derotated coefficients are analyzed and the implications for image estimation algorithm design noted. The observations and conclusions provide a basis for design of the denoising algorithm in [1].

A method for removing additive Gaussian noise from digital images is described. It is based on statistical modeling of the coefficients of a redundant, oriented, complex multiscale transform. Two types of modeling are used to model the wavelet coefficients. Both are based on Gaussian scale mixture (GSM) modeling of neighborhoods of coefficients at adjacent locations and scales. Modeling of edge and ridge discontinuities is performed using wavelet coefficients derotated by twice the phase of the coefficient at the same location and the next coarser scale. Other areas are modeled using standard wavelet coefficients. An adaptive Bayesian model selection framework is used to determine the modeling applied to each neighborhood. The proposed algorithm succeeds in providing improved denoising performance at structural image features, reducing ringing artifacts and enhancing sharpness, while avoiding degradation in other areas. The method outperforms previously published methods visually and in standard tests.

A novel method for modelling the statistics of 2D photographic images useful in image restoration is defined. The new method is based on the dual tree complex wavelet transform (DT-CWT) but a phase rotation is applied to the coefficients to create complex coefficients whose phase is shift-invariant at multiscale edge and ridge features. This is in addition to the magnitude shift invariance achieved by the DT-CWT. The increased correlation between coefficients adjacent in space and scale provides an improved, mechanism for signal estimation

The aim of seismic imaging is to reconstruct subsurface reflectivity from scattered acoustic data. In standard reconstruction techniques, the reflectivity model parameters are usually defined as a grid of point scatterers over the area or volume of the subsurface to be imaged. We propose an approach to subsurface imaging using the dual tree complex wavelet transform (DT-CWT) as a basis for the reflectivity. This basis is used in conjunction with an iterative optimization which frames the problem as a linearized inverse scattering problem. We demonstrate the method on a marine seismic data set acquired over the Gippsland Basin near Australia. The technique is shown to reduce noise and processing artifacts while preserving discontinuities. It is likely to be particularly useful in cases where the acquired data are incomplete.