MOTIVATION: The selection of a single nucleotide polymorphism (SNP) using bibliographic methods can be a very time-consuming task. Moreover, a SNP selected in this way may not be easily visualized in its genomic context by a standard user hoping to correlate it with other valuable information. Here we propose a web form built on top of Circos that can assist SNP-centered screening, based on their location in the genome and the regulatory modules they can disrupt. Its use may allow researchers to prioritize SNPs in genotyping and disease studies. RESULTS: SiNoPsis is bundled as a web portal. It focuses on the different structures involved in the genomic expression of a gene, especially those found in the core promoter upstream region. These structures include transcription factor binding sites (for promoter and enhancer signals), histones and promoter flanking regions. Additionally, the tool provides eQTL and linkage disequilibrium (LD) properties for a given SNP query, yielding further clues about other indirectly associated SNPs. Possible disruptions of the aforementioned structures affecting gene transcription are reported using multiple resource databases. SiNoPsis has a simple user-friendly interface, which allows single queries by gene symbol, genomic coordinates, Ensembl gene identifiers, RefSeq transcript identifiers and SNPs. It is the only portal providing useful SNP selection based on regulatory modules and LD with functional variants in both textual and graphic modes (by properly defining the arguments and parameters needed to run Circos). AVAILABILITY AND IMPLEMENTATION: SiNoPsis is freely available at https://compgen.bio.ub.edu/SiNoPsis/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

We contribute to recent efforts in relating two approaches to automatic synthesis, namely, automated planning and discrete reactive synthesis. First, we develop a declarative characterization of the standard "fairness" assumption on environments in non-deterministic planning, and show that strong-cyclic plans are correct solution concepts for fair environments. This complements, and arguably completes, the existing foundational work on non-deterministic planning, which focuses on characterizing (and computing) plans enjoying special "structural" properties, namely loopy but closed policy structures. Second, we provide an encoding suitable for reactive synthesis that avoids the naive exponential state space blowup. To do so, special care has to be taken to specify the fairness assumption on the environment in a succinct manner.

The Delaunay triangulation is the standard choice for building triangulated irregular networks (TINs) to represent terrain surfaces. However, the Delaunay triangulation is based only on the 2D coordinates of the data points, ignoring their elevation. It has long been recognized that sometimes it may be beneficial to use other, non-Delaunay, criteria to build TINs. Data-dependent triangulations were introduced decades ago to address this. However, they are rarely used in practice, mostly because the optimization of data- dependent criteria often results in triangulations with many thin and elongated triangles. Recently, in the field of computational geometry, higher order Delaunay triangulations (HODTs) were introduced, trying to tackle both issues at the same time-data-dependent criteria and good triangle shape. Nevertheless, most previous studies about them have been limited to theoretical aspects. In this work we present the first extensive experimental study on the practical use of HODTs, as a tool to build data-dependent TINs. We present experiments with two USGS terrains that show that HODTs can give significant improvements over the Delaunay triangulation for the criteria identified as most important for data-dependent triangulations. The resulting triangulations have data-dependent values comparable to those obtained with pure data-dependent approaches, without compromising the shape of the triangles, and are faster to compute.