Organizing research data.

Research relies on ever larger amounts of data from experiments, automated production equipment, questionnaries, times series such as weather records, and so on. A major task in science is to combine, process and analyse such data to obtain evidence of patterns and correlations.Most research data are on digital form, which in principle ensures easy processing and analysis, easy long-term preservation, and easy reuse in future research, perhaps in entirely unanticipated ways. However, in practice, obstacles such as incompatible or undocumented data formats, poor data quality and lack of familiarity with current technology prevent researchers from making full use of available data.This paper argues that relational databases are excellent tools for veterinary research and animal production; provides a small example to introduce basic database concepts; and points out some concerns that must be addressed when organizing data for research purposes.

Semiautomated improvement of RNA alignments.

We have developed a semiautomated RNA sequence editor (SARSE) that integrates tools for analyzing RNA alignments. The editor highlights different properties of the alignment by color, and its integrated analysis tools prevent the introduction of errors when doing alignment editing. SARSE readily connects to external tools to provide a flexible semiautomatic editing environment. A new method, Pcluster, is introduced for dividing the sequences of an RNA alignment into subgroups with secondary structure differences. Pcluster was used to evaluate 574 seed alignments obtained from the Rfam database and we identified 71 alignments with significant prediction of inconsistent base pairs and 102 alignments with significant prediction of novel base pairs. Four RNA families were used to illustrate how SARSE can be used to manually or automatically correct the inconsistent base pairs detected by Pcluster: the mir-399 RNA, vertebrate telomase RNA (vert-TR), bacterial transfer-messenger RNA (tmRNA), and the signal recognition particle (SRP) RNA. The general use of the method is illustrated by the ability to accommodate pseudoknots and handle even large and divergent RNA families. The open architecture of the SARSE editor makes it a flexible tool to improve all RNA alignments with relatively little human intervention. Online documentation and software are available at (http://sarse.ku.dk).

Modeling the kinetics of the competitive adsorption and desorption of glyphosate and phosphate on goethite and gibbsite and in soils.

The herbicide glyphosate and inorganic phosphate compete for adsorption sites in soil and on oxides. This competition may have consequences for the transport of both compounds in soil and hence for the contamination of groundwater. We present and evaluate six simple, kinetic models that only take time and concentrations into account. Three of the models were found suitable to describe the competition in soil. These three models all assumed both competitive and additive adsorption, but with different equations used to describe the adsorption. For the oxides, three additional models assuming only competitive adsorption were also found suitable. This is in accordance with the observation that the adsorption in soil is both competitive and additive, whereas the adsorption on oxides is competitive. All models can be incorporated in transport models such as the convection-dispersion equation.