Financial convergence in transition economies: EU enlargement

This paper analyses the financial impact of the enlargement of the European Union (EU) to include 10 new Central and Eastern European Nations (CEEN) on firms’ business and financial structures. To this end, we employ quantitative analytic techniques and financial ratios. In this context, we hope to discover whether firms in the new EU member States tend to converge with business in the Europe of the 15 in terms of the structure of firms’ financial statements. We examine the extent to which the increasing integration of the former may foster the convergence of productive structures. The methodology followed consists of an analysis of the evolution of 12 financial ratios in a sample of firms obtained from the AMADEUS data base. To that end, we perform a Dynamic Factor Analysis that identifies the determining factors of the joint evolution of deviations in the financial ratios with respect to the average value of firms in the EU-15. This analysis allows us to analyse the convergence in each of the CEEN nations with respect to the EU-15.

The transcriptional network activated by Cln3 cyclin at the G1-to-S transition of the yeast cell cycle

Background: The G1-to-S transition of the cell cycle in the yeast Saccharomyces cerevisiae involves an extensive transcriptional program driven by transcription factors SBF (Swi4-Swi6) and MBF (Mbp1-Swi6). Activation of these factors ultimately depends on the G1 cyclin Cln3. Results: To determine the transcriptional targets of Cln3 and their dependence on SBF or MBF, we first have used DNA microarrays to interrogate gene expression upon Cln3 overexpression in synchronized cultures of strains lacking components of SBF and/or MBF. Secondly, we have integrated this expression dataset together with other heterogeneous data sources into a single probabilistic model based on Bayesian statistics. Our analysis has produced more than 200 transcription factor-target assignments, validated by ChIP assays and by functional enrichment. Our predictions show higher internal coherence and predictive power than previous classifications. Our results support a model whereby SBF and MBF may be differentially activated by Cln3. Conclusions: Integration of heterogeneous genome-wide datasets is key to building accurate transcriptional networks. By such integration, we provide here a reliable transcriptional network at the G1-to-S transition in the budding yeast cell cycle. Our results suggest that to improve the reliability of predictions we need to feed our models with more informative experimental data.