diArk – a resource for eukaryotic genome research

<p>Abstract</p> <p>Background</p> <p>The number of completed eukaryotic genome sequences and cDNA projects has increased exponentially in the past few years although most of them have not been published yet. In addition, many microarray analyses yielded thousands of sequenced EST and cDNA clones. For the researcher interested in single gene analyses (from a phylogenetic, a structural biology or other perspective) it is therefore important to have up-to-date knowledge about the various resources providing primary data.</p> <p>Description</p> <p>The database is built around 3 central tables: species, sequencing projects and publications. The species table contains commonly and alternatively used scientific names, common names and the complete taxonomic information. For projects the sequence type and links to species project web-sites and species homepages are stored. All publications are linked to projects. The web-interface provides comprehensive search modules with detailed options and three different views of the selected data. We have especially focused on developing an elaborate taxonomic tree search tool that allows the user to instantaneously identify e.g. the closest relative to the organism of interest.</p> <p>Conclusion</p> <p>We have developed a database, called diArk, to store, organize, and present the most relevant information about completed genome projects and EST/cDNA data from eukaryotes. Currently, diArk provides information about 415 eukaryotes, 823 sequencing projects, and 248 publications.</p

diArk 2.0 provides detailed analyses of the ever increasing eukaryotic genome sequencing data

<p>Abstract</p> <p>Background</p> <p>Nowadays, the sequencing of even the largest mammalian genomes has become a question of days with current next-generation sequencing methods. It comes as no surprise that dozens of genome assemblies are released per months now. Since the number of next-generation sequencing machines increases worldwide and new major sequencing plans are announced, a further increase in the speed of releasing genome assemblies is expected. Thus it becomes increasingly important to get an overview as well as detailed information about available sequenced genomes. The different sequencing and assembly methods have specific characteristics that need to be known to evaluate the various genome assemblies before performing subsequent analyses.</p> <p>Results</p> <p>diArk has been developed to provide fast and easy access to all sequenced eukaryotic genomes worldwide. Currently, diArk 2.0 contains information about more than 880 species and more than 2350 genome assembly files. Many meta-data like sequencing and read-assembly methods, sequencing coverage, GC-content, extended lists of alternatively used scientific names and common species names, and various kinds of statistics are provided. To intuitively approach the data the web interface makes extensive usage of modern web techniques. A number of search modules and result views facilitate finding and judging the data of interest. Subscribing to the RSS feed is the easiest way to stay up-to-date with the latest genome data.</p> <p>Conclusions</p> <p>diArk 2.0 is the most up-to-date database of sequenced eukaryotic genomes compared to databases like GOLD, NCBI Genome, NHGRI, and ISC. It is different in that only those projects are stored for which genome assembly data or considerable amounts of cDNA data are available. Projects in planning stage or in the process of being sequenced are not included. The user can easily search through the provided data and directly access the genome assembly files of the sequenced genome of interest. diArk 2.0 is available at <url>http://www.diark.org</url>.</p

Peakr: simulating solid-state NMR spectra of proteins.

International audienceWhen analyzing solid-state nuclear magnetic resonance (NMR) spectra of proteins, assignment of resonances to nuclei and derivation of restraints for 3D structure calculations are challenging and time-consuming processes. Simulated spectra that have been calculated based on, for example, chemical shift predictions and structural models can be of considerable help. Existing solutions are typically limited in the type of experiment they can consider and difficult to adapt to different settings. Here, we present Peakr, a software to simulate solid-state NMR spectra of proteins. It can generate simulated spectra based on numerous common types of internuclear correlations relevant for assignment and structure elucidation, can compare simulated and experimental spectra and produces lists and visualizations useful for analyzing measured spectra. Compared with other solutions, it is fast, versatile and user friendly. Peakr is maintained under the GPL license and can be accessed at http://www.peakr.org. The source code can be obtained on request from the authors