Many applications work with graph-structured data. As graphs grow in size, indexing becomes essential to ensure sufficient query performance. We present the GRIPP index structure (GRaph Indexing based on Pre-and Postorder numbering) for answering reachability queries in graphs.GRIPP requires only linear time and space. Using GRIPP, we can answer reachability queries on graphs with 5 million nodes on average in less than 5 milliseconds, which is unrivaled by previous methods. We evaluate the performance and scalability of our approach on real and synthetic random and scale-free graphs and compare our approach to existing indexing schemes. GRIPP is implemented as stored procedure inside a relational database management system and can therefore very easily be integrated into existing graphoriented applications.

The microarray-based analysis of gene expression has become a workhorse for biomedical research. Managing the amount and diversity of data that such experiments produce is a task that must be supported by appropriate software tools, which led to the creation of literally hundreds of systems. In consequence, choosing the right tool for a given project is difficult even for the expert. We report on the results of a survey encompassing 78 of such tools, of which 22 were inspected in detail and seven were tested hands-on. We report on our experiences with a focus on completeness of functionality, ease-of-use, and necessary effort for installation and maintenance. Thereby, our survey provides a valuable guideline for any project considering the use of a microarray data management system. It reveals which tasks are covered by mature tools and also shows that important requirements, especially in the area of integrated analysis of different experimental data, are not yet met satisfyingly by existing systems.

Fitting of lactation curves is a common tool to obtain the entire milk yield as well as to estimate the main curve characteristic (such as day of peak milk yield) for a lactation. These models are primarily designed for dairy cattle, but have been applied to nondairy cattle breeds and also for other species. In this study we considered milk yield data of 197 F crossbred cows of Charolais and German Holstein (founder breeds) for the first and the beginning of the second lactation. The F cows showed a high variability regarding the length of lactation, which varied between 7 and 406 d in milk for the first lactation. Thus, the data also show high variation regarding the daily and overall milk yield. To obtain complete lactation curves, we evaluated the lactation models of Ali-Schaeffer and Wilmink. To compare the 2 lactation models, we evaluated the goodness of fit using 6 evaluation criteria. The results show that the model of Ali-Schaeffer performs better on these highly inhomogeneous data, in contrast to the model of Wilmink. We discuss our findings from a statistical point of view and present possible biological reasons for the high variability regarding milk yield within the F population. Hence our findings may be helpful when milk yield data of crosses between dairy and beef cows (dual purpose) are investigated, whose lactation curves may not show the typical characteristics of dairy cattle.

Background: Structural and functional research often requires the computation of sets of protein structures based on certain properties of the proteins, such as sequence features, fold classification, or functional annotation. Compiling such sets using current web resources is tedious because the necessary data are spread over many different databases. To facilitate this task, we have created COLUMBA, an integrated database of annotations of protein structures.

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