Ranked retrieval of Computational Biology models

<p>Abstract</p> <p>Background</p> <p>The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. Deciding for potentially suitable models, however, becomes more challenging with the increasing number of computational models available, and even more when considering the models' growing complexity. Firstly, among a set of potential model candidates it is difficult to decide for the model that best suits ones needs. Secondly, it is hard to grasp the nature of an unknown model listed in a search result set, and to judge how well it fits for the particular problem one has in mind.</p> <p>Results</p> <p>Here we present an improved search approach for computational models of biological processes. It is based on existing retrieval and ranking methods from Information Retrieval. The approach incorporates annotations suggested by MIRIAM, and additional meta-information. It is now part of the search engine of BioModels Database, a standard repository for computational models.</p> <p>Conclusions</p> <p>The introduced concept and implementation are, to our knowledge, the first application of Information Retrieval techniques on model search in Computational Systems Biology. Using the example of BioModels Database, it was shown that the approach is feasible and extends the current possibilities to search for relevant models. The advantages of our system over existing solutions are that we incorporate a rich set of meta-information, and that we provide the user with a relevance ranking of the models found for a query. Better search capabilities in model databases are expected to have a positive effect on the reuse of existing models.</p

Economic conditions, hypertension, and cardiovascular disease: analysis of the Icelandic economic collapse

Previous research has found a positive short-term relationship between the 2008 collapse and hypertension in Icelandic males. With Iceland's economy experiencing a phase of economic recovery, an opportunity to pursue a longer-term analysis of the collapse has emerged. Using data from a nationally representative sample, fixed-effect estimations and mediation analyses were performed to explore the relationship between the Icelandic economic collapse in 2008 and the longer-term impact on hypertension and cardiovascular health. A sensitivity analysis was carried out with pooled logit models estimated as well as an alternative dependent variable. Our attrition analysis revealed that results for cardiovascular diseases were affected by attrition, but not results from estimations on the relationship between the economic crisis and hypertension. When compared to the boom year 2007, our results point to an increased probability of Icelandic women having hypertension in the year 2012, when the Icelandic economy had recovered substantially from the economic collapse in 2008. This represents a deviation from pre-crisis trends, thus suggesting a true economic-recovery impact on hypertension.The project was funded by the Icelandic Research Fund (IRF grant number 130611-052) and The University of Iceland Eimskip Fund. The data collection was financed and carried out by the Directorate of Health Iceland (and formerly the Public Health Institute of Iceland). The authors would like to thank the Directorate for access to the data.Peer Reviewe