Genome sequences hot and cold: a database of organisms with defined optimal growth temperatures

Despite the rapidly increasing number of organisms with sequenced genomes, there is no existing resource that simultaneously contains information about genome sequences and the optimal growth conditions for a given species. In the absence of such a resource, we cannot immediately sort genomic sequences by growth conditions, making it difficult to study how organisms and biological molecules adapt to distinct environments. To address this problem, we have created a database called GSHC (Genome Sequences: Hot, Cold, and everything in between). This database, available at http://melnikovlab.com/gshc, brings together information about the genomic sequences and optimal growth temperatures for 25,324 species, including ~89% of the bacterial species with known genome sequences. Using this database, it is now possible to readily compare genomic sequences from thousands of species and correlate variations in genes and genomes with optimal growth temperatures, at the scale of the entire tree of life. The database interface allows users to retrieve protein sequences sorted by optimal growth temperature for their corresponding species, providing a tool to explore how organisms, genomes, and individual proteins and nucleic acids adapt to certain temperatures. We hope that this database will contribute to medicine and biotechnology by helping to create a better understanding of molecular adaptations to heat and cold, leading to new ways to preserve biological samples, engineer useful enzymes, and develop new biological materials and organisms with the desired tolerance to heat and cold.

Empowering Natural Language Interfaces to Databases with Aggregations

A Natural Language Interface to Database (NLIDB) refers to a database interface that translates a question asked in natural language into a structured query. Aggregation questions express aggregation functions, such as count, sum, average, minimum and maximum, and optionally a group by clause and a having clause. NLIDBs deliver good results for standard questions but usually do not deal with aggregation questions. The main contribution of this article is a generic module, called GLAMORISE (GeneraL Aggregation MOdule using a RelatIonal databaSE), that extends NLIDBs to cope with aggregation questions. GLAMORISE covers aggregations with ambiguities, timescale differences, aggregations in multiple attributes, the use of superlative adjectives, basic recognition of measurement units, and aggregations in attributes with compound names.

Matching Pragmatic Lithic Analysis and Proper Data Architecture

The documentation and analysis of archaeological lithics must navigate a basic tension between examining and recording data on individual artifacts or on aggregates of artifacts. This poses a challenge both for artifact processing and for database construction. We present here an R Shiny solution that enables lithic analysts to enter data for both individual artifacts and aggregates of artifacts while maintaining a robust yet flexible data structure. This takes the form of a browser-based database interface that uses R to query existing data and transform new data as necessary so that users entering data of varying resolutions still produce data structured around individual artifacts. We demonstrate the function and efficacy of this tool (termed the Queryable Artifact Recording Interface [QuARI]) using the example of the Stelida Naxos Archaeological Project (SNAP), which, focused on a Paleolithic and Mesolithic chert quarry, has necessarily confronted challenges of processing and analyzing large quantities of lithic material.

A surprise in the updated list of stellar perturbers of long-period comet motion

Context. The second Gaia data release (Gaia DR2) provided us with the precise five-parameter astrometry for 1.3 billion of sources. As stars passing close to the Solar System are thought to influence the dynamical history of long-period comets, we update and extend the list of stars that could potentially perturb the motion of these comets. Aims. We announce a publicly available database containing an up-to-date list of stars and stellar systems potentially perturbing the motion of long-period comets. We add new objects and revise previously published lists. Special emphasis is placed on stellar systems. A discussion of mass estimation is included. Methods. Using the astrometry, preferably from Gaia DR2, augmented with data from other sources, we calculate nominal spatial positions and velocities for each star. To filter studied objects on the basis of their nominal minimum heliocentric distances we numerically integrate the motion of stars under the Galactic potential and their mutual interactions. Results. We announce the updated list of stellar perturbers of cometary motion, including the masses of perturbers along with the publicly available database interface. These data are ready to be used with the observed long-period comets orbits to study an individual influence of a whole sample of perturbers, or specific stars, on a dynamical past or future of a specific comet. New potential perturbers were added; there are 138 more than in the previously published sources. Conclusions. We demonstrate that a new set of prospective perturbers is an important tool in studies of cometary dynamics. The use of our data changes the results of the past and future cometary motion analysis. We point out a puzzling object in our list, star ALS 9243. The Gaia DR2 astrometry suggests a very close encounter of this star with the Sun; however, its astrophysical parameters result in a completely different current distance of ALS 9243 and its high mass.