Simulation of RF-fields in a fusion device

In this paper the problem of scattering off a fusion plasma is approached from the point of view of integral equations. Using the volume equivalence principle an integral equation is derived which describes the electromagnetic fields in a plasma. The equation is discretized with MoM using conforming basis functions. This reduces the problem to solving a dense matrix equation. This can be done iteratively. Each iteration can be sped up using FFTs

i-ADHoRe 3.0—fast and sensitive detection of genomic homology in extremely large data sets

Comparative genomics is a powerful means to gain insight into the evolutionary processes that shape the genomes of related species. As the number of sequenced genomes increases, the development of software to perform accurate cross-species analyses becomes indispensable. However, many implementations that have the ability to compare multiple genomes exhibit unfavorable computational and memory requirements, limiting the number of genomes that can be analyzed in one run. Here, we present a software package to unveil genomic homology based on the identification of conservation of gene content and gene order (collinearity), i-ADHoRe 3.0, and its application to eukaryotic genomes. The use of efficient algorithms and support for parallel computing enable the analysis of large-scale data sets. Unlike other tools, i-ADHoRe can process the Ensembl data set, containing 49 species, in 1 h. Furthermore, the profile search is more sensitive to detect degenerate genomic homology than chaining pairwise collinearity information based on transitive homology. From ultra-conserved collinear regions between mammals and birds, by integrating coexpression information and protein–protein interactions, we identified more than 400 regions in the human genome showing significant functional coherence. The different algorithmical improvements ensure that i-ADHoRe 3.0 will remain a powerful tool to study genome evolution

BLSSpeller : exhaustive comparative discovery of conserved cis-regulatory elements

Motivation: The accurate discovery and annotation of regulatory elements remains a challenging problem. The growing number of sequenced genomes creates new opportunities for comparative approaches to motif discovery. Putative binding sites are then considered to be functional if they are conserved in orthologous promoter sequences of multiple related species. Existing methods for comparative motif discovery usually rely on pregenerated multiple sequence alignments, which are difficult to obtain for more diverged species such as plants. As a consequence, misaligned regulatory elements often remain undetected. Results: We present a novel algorithm that supports both alignment-free and alignment-based motif discovery in the promoter sequences of related species. Putative motifs are exhaustively enumerated as words over the IUPAC alphabet and screened for conservation using the branch length score. Additionally, a confidence score is established in a genome-wide fashion. In order to take advantage of a cloud computing infrastructure, the MapReduce programming model is adopted. The method is applied to four monocotyledon plant species and it is shown that high-scoring motifs are significantly enriched for open chromatin regions in Oryza sativa and for transcription factor binding sites inferred through protein-binding microarrays in O. sativa and Zea mays. Furthermore, the method is shown to recover experimentally profiled ga2ox1-like KN1 binding sites in Z. mays