SCUMBLE: a method for systematic and accurate detection of codon usage bias by maximum likelihood estimation

The genetic code is degenerate—most amino acids can be encoded by from two to as many as six different codons. The synonymous codons are not used with equal frequency: not only are some codons favored over others, but also their usage can vary significantly from species to species and between different genes in the same organism. Known causes of codon bias include differences in mutation rates as well as selection pressure related to the expression level of a gene, but the standard analysis methods can account for only a fraction of the observed codon usage variation. We here introduce an explicit model of codon usage bias, inspired by statistical physics. Combining this model with a maximum likelihood approach, we are able to clearly identify different sources of bias in various genomes. We have applied the algorithm to Saccharomyces cerevisiae as well as 325 prokaryote genomes, and in most cases our model explains essentially all observed variance

Heterogeneous Organizational Arrangements in Agrifood Chains: A Governance Value Analysis Perspective on the Sheep and Goat Meat Sector of Italy

In the Italian agrifood sector, one observes heterogeneity in the types of quality certification processes. This heterogeneity cannot be explained by standard governance theories like transaction costs economics (TCE). We use the governance value analysis (GVA) perspective that synthesizes TCE and a resources-based view (RBV), to suggest that the observed heterogeneity in organizational forms is a result of heterogeneous differentiating strategies that farms have pursued in the face of competitive pricing pressures. To empirically test GVA, data are obtained using a survey methodology on lamb meat produced by local farms in the Abruzzo region of Italy, challenged by price-costs squeeze. Our empirical test evidences the relevance of the adopted approach, enlightening different organizational arrangements, strictly linked to both the strategic positioning and to the farms’ resources and core competencies