Enrichment of the Phenotypic and Genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Currently there are an overwhelming number of scientific publications in Life Sciences, especially in Genetics and Biotechnology. This huge amount of information is structured in corporate Data Warehouses (DW) or in Biological Databases (e.g. UniProt, RCSB Protein Data Bank, CEREALAB or GenBank), whose main drawback is its cost of updating that makes it obsolete easily. However, these Databases are the main tool for enterprises when they want to update their internal information, for example when a plant breeder enterprise needs to enrich its genetic information (internal structured Database) with recently discovered genes related to specific phenotypic traits (external unstructured data) in order to choose the desired parentals for breeding programs. In this paper, we propose to complement the internal information with external data from the Web using Question Answering (QA) techniques. We go a step further by providing a complete framework for integrating unstructured and structured information by combining traditional Databases and DW architectures with QA systems. The great advantage of our framework is that decision makers can compare instantaneously internal data with external data from competitors, thereby allowing taking quick strategic decisions based on richer data.

Water polo throwing speed and body composition: an analysis by playing positions and opposition level

The aim of this study was to develop an anthropometric profile on highly skilled male water polo players by specific playing positions. Also, to identify significant relationships between these features an overhead throwing speed in highly skilled male Water Polo players by specific playing positions. Methods: A total of 94 male water polo players (24.5±5.3 yrs) who were playing in the Spanish King´s cup were studied. Subjects were grouped according to their specific playing positions: 15 goalkeepers, 45 offensive wings, 20 center backs and 14 center forwards. Anthropometric assessment was made following ISAK protocols. Hand grip and throwing speed in several situations were also assessed. A one-way analysis of variance (ANOVA) was used to determine if significant differences existed among the four playing positions. Pearson product-moment correlation coefficients (r) were used to determine the relationships of all anthropometric measures with throwing speed and hand grip. The total player’s somatotype was endomorphic-mesomorphic (2.9–5.8–2.3). Center forwards exhibit important anthropometric differences compared with the other specific playing positions in elite male water polo players, but no differences were found in throwing speed by specific playing positions in each throwing conditions. Moreover, a higher number of relationships between anthropometric and throwing speed were found in wings and also in center backs but no relationships were found in center forwards. The data reflects the importance of muscle mass and upper body in the throwing skill. Coaches can use this information in order to select players for the different specific positions.