The mzTab Data Exchange Format: Communicating Mass-spectrometry-based Proteomics and Metabolomics Experimental Results to a Wider Audience.

The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R. We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online.

Studies on Procamallanus (Spirocamallanus) pereirai Annereaux, 1946 (Nematoda: Camallanidae), with new host records and new morphological data on the larval stages

Larval stages and adults of Procamallanus (Spirocamallanus) pereirai Annereaux, 1946 are described from naturally infected Paralonchurus brasiliensis (Steindachner) (Sciaenidae) from the coast of the State of Rio de Janeiro, Brazil. The translucent first-stage larvae have a denticulate process at the anterior end, no buccal capsule or esophagus undifferentiated into anterior muscular and posterior glandular parts and an elongate tail; third-stage larvae have a tail with three terminal projections, a buccal capsule divided into an anterior portion with 12-20 ridges running to the left and a posterior smooth portion, and an esophagus with muscular and glandular regions. Fourth-stage larvae exhibit a buccal capsule lacking a distinct basal ring with ridges running to the right and a tail with two terminal processes, as in adults. New host records are reported and their role in its life-cycle are discussed.

All-Ireland Health Data Inventory. Part 1: Metadata for key data sources, version 1.0

The All-Ireland Health Data Inventory. Part 1 is a catalogue of key sources of health data in the Republic and Northern Ireland. It includes relevant datasets from the major information reviews, conducted in the North and South, in the past few years. Information is essential for informed decision making and service provision. This inventory draws together information sources to facilitate such decision making. The inventory is intended as a resource for health professionals, researchers and the general public, providing the first phase of a ‘one-stop’ catalogue of health data. The datasets have been catalogued using an expanding numbering system which will allow for the inclusion of future resources. The Institute of Public Health in Ireland is in the process of expanding the Inventory to include further data sources.

Extra healthy years or just extra years? What can we know from the data we have on the island of Ireland?

As life expectancy continues to rise, the prevalence of chronic conditions is increasing in our society. However, we do not know if the extra years of life gained are being spent with disability and illness, or in good health. Furthermore, it is unclear if all groups in society experience their extra years of life in the same way. This report examines patterns of health expectancies across the island of Ireland, examining any North-South and socio-economic differences as well looking at differences in data sources. The older population (aged 65 or over) on the island of Ireland is growing and becoming a larger percentage of the total  population. Republic of Ireland Census 2011 revealed that 12% of the RoI population was aged 65 or over (CSO, 2012), and Northern Ireland Census 2011 revealed that 13% of the NI population was aged 65 or over (NISRA, 2012). By 2041 the population aged 65 or over is projected to reach 22% in RoI and 24% in NI (McGill, 2010). It is unclear, however, if this increasing longevity will be enjoyed equally by all strata of society.

Des données aux connaissances, un chemin difficile: réflexion sur la place du data mining en analyse criminelle

Le "data mining", ou "fouille de données", est un ensemble de méthodes et de techniques attractif qui a connu une popularité fulgurante ces dernières années, spécialement dans le domaine du marketing. Le développement récent de l'analyse ou du renseignement criminel soulève des problèmatiques auxqwuelles il est tentant de d'appliquer ces méthodes et techniques. Le potentiel et la place du data mining dans le contexte de l'analyse criminelle doivent être mieux définis afin de piloter son application. Cette réflexion est menée dans le cadre du renseignement produit par des systèmes de détection et de suivi systématique de la criminalité répétitive, appelés processus de veille opérationnelle. Leur fonctionnement nécessite l'existence de patterns inscrits dans les données, et justifiés par les approches situationnelles en criminologie. Muni de ce bagage théorique, l'enjeu principal revient à explorer les possibilités de détecter ces patterns au travers des méthodes et techniques de data mining. Afin de répondre à cet objectif, une recherche est actuellement menée au Suisse à travers une approche interdisciplinaire combinant des connaissances forensiques, criminologiques et computationnelles.