The FAIR Guiding Principle for Scientific Data Management and Stewardship:Comment

There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community

Bridging the gap between social tagging and semantic annotation: E.D. the Entity Describer

Semantic annotation enables the development of efficient computational methods for analyzing and interacting with information, thus maximizing its value. With the already substantial and constantly expanding data generation capacity of the life sciences as well as the concomitant increase in the knowledge distributed in scientific articles, new ways to produce semantic annotations of this information are crucial. While automated techniques certainly facilitate the process, manual annotation remains the gold standard in most domains. In this manuscript, we describe a prototype mass-collaborative semantic annotation system that, by distributing the annotation workload across the broad community of biomedical researchers, may help to produce the volume of meaningful annotations needed by modern biomedical science. We present E.D., the Entity Describer, a mashup of the Connotea social tagging system, an index of semantic web-accessible controlled vocabularies, and a new public RDF database for storing social semantic annotations

Virulence- and signaling-associated genes display a preference for long 3′UTRs during rice infection and metabolic stress in the rice blast fungus

Generation of mRNA isoforms by alternative polyadenylation (APA) and their involvement in regulation of fungal cellular processes, including virulence, remains elusive. Here, we investigated genome‐wide polyadenylation site (PAS) selection in the rice blast fungus to understand how APA regulates pathogenicity. More than half of Magnaporthe oryzae transcripts undergo APA and show novel motifs in their PAS region. Transcripts with shorter 3′UTRs are more stable and abundant in polysomal fractions, suggesting they are being translated more efficiently. Importantly, rice colonization increases the use of distal PASs of pathogenicity genes, especially those participating in signalling pathways like 14‐3‐3B, whose long 3′UTR is required for infection. Cleavage factor I (CFI) Rbp35 regulates expression and distal PAS selection of virulence and signalling‐associated genes, tRNAs and transposable elements, pointing its potential to drive genomic rearrangements and pathogen evolution. We propose a noncanonical PAS selection mechanism for Rbp35 that recognizes UGUAH, unlike humans, without CFI25. Our results showed that APA controls turnover and translation of transcripts involved in fungal growth and environmental adaptation. Furthermore, these data provide useful information for enhancing genome annotations and for cross‐species comparisons of PASs and PAS usage within the fungal kingdom and the tree of life

A derivation of the Liouville equation for hard particle dynamics with non-conservative interactions

The Liouville equation is of fundamental importance in the derivation of continuum models for physical systems which are approximated by interacting particles. However, when particles undergo instantaneous interactions such as collisions, the derivation of the Liouville equation must be adapted to exclude non-physical particle positions, and include the effect of instantaneous interactions. We present the weak formulation of the Liouville equation for interacting particles with general particle dynamics and interactions, and discuss the results using an example

Dynamical Mass Estimates for the Halo of M31 from Keck Spectroscopy

The last few months have seen the measurements of the radial velocities of all of the dwarf spheroidal companions to the Andromeda galaxy (M31) using the spectrographs (HIRES and LRIS) on the Keck Telescope. This paper summarises the data on the radial velocities and distances for all the companion galaxies and presents new dynamical modelling to estimate the mass of extended halo of M31. The best fit values for the total mass of M31 are between 7 and 10 x 10^{11} solar masses, depending on the details of the modelling. The mass estimate is accompanied by considerable uncertainty caused by the smallness of the dataset; for example, the upper bound on the total mass is roughly 24 x 10^{11} solar masses, while the lower bound is about 3 x 10^{11} solar masses. These values are less than the most recent estimates of the most likely mass of the Milky Way halo. Bearing in mind all the uncertainties, a fair conclusion is that the M31 halo is roughly as massive as that of the Milky Way halo. There is no dynamical evidence for the widely held belief that M31 is more massive -- it may even be less massive.Comment: In press, The Astrophysical Journal (Letters

Robust and automatic definition of microbiome states

Analysis of microbiome dynamics would allow elucidation of patterns within microbial community evolution under a variety of biologically or economically important circumstances; however, this is currently hampered in part by the lack of rigorous, formal, yet generally-applicable approaches to discerning distinct configurations of complex microbial populations. Clustering approaches to define microbiome “community state-types” at a population-scale are widely used, though not yet standardized. Similarly, distinct variations within a state-type are well documented, but there is no rigorous approach to discriminating these more subtle variations in community structure. Finally, intra-individual variations with even fewer differences will likely be found in, for example, longitudinal data, and will correlate with important features such as sickness versus health. We propose an automated, generic, objective, domain-independent, and internally-validating procedure to define statistically distinct microbiome states within datasets containing any degree of phylotypic diversity. Robustness of state identification is objectively established by a combination of diverse techniques for stable cluster verification. To demonstrate the efficacy of our approach in detecting discreet states even in datasets containing highly similar bacterial communities, and to demonstrate the broad applicability of our method, we reuse eight distinct longitudinal microbiome datasets from a variety of ecological niches and species. We also demonstrate our algorithm’s flexibility by providing it distinct taxa subsets as clustering input, demonstrating that it operates on filtered or unfiltered data, and at a range of different taxonomic levels. The final output is a set of robustly defined states which can then be used as general biomarkers for a wide variety of downstream purposes such as association with disease, monitoring response to intervention, or identifying optimally performant populations

Stress, nutrients and genotype: understanding and managing asparagine accumulation in wheat grain

Plant stress and poor crop management strategies compromise the foundations of food security: crop yield, nutritional quality and food safety. Accumulation of high concentrations of the amino acid asparagine in its free (soluble, non-protein) form is an example of an undesirable outcome of stress for the nutritional quality and food safety of wheat because of its role as a precursor to acrylamide, a carcinogenic processing contaminant. In this review, we cover what is known about the mechanisms and functions of free asparagine accumulation in the grain during normal development and particularly during stress in wheat. Comparisons with other plant species, yeast, and mammals are drawn in order to gain deeper insight into the conserved biology underlying asparagine accumulation. Crop management strategies and practices are discussed in the context of managing asparagine accumulation, which must be balanced against other desirable goals, such as sustainability, protein content and yield