Comparison of time series and mechanistic models of vector-borne diseases.

Vector-borne disease models are widely used to understand the dynamics involved in virus transmission. The simplest version of the mechanistic SEIR-SEI model is the most widely used representation of the dynamics involved in vector-borne diseases. Modifications to the basic model can improve the complex dynamics' acuracy.

Multi-cluster and environmental dependant vector born disease models.

Vector-born disease models are extensively used for surveillance and control processes. The most simple and generally use model (SEIR-SEI model) cannot explain a variety of phenomena involved in these diseases spread and development. In order to obtain a wider insight of the vector-born disease models (and the dynamics involved in them), this work focuses into analyse the classical model, a modified versions of it, and 8 their parameters.

CodonLogo: a sequence logo-based viewer for codon patterns.

Motivation: Conserved patterns across a multiple sequence alignment can be visualized by generating sequence logos. Sequence logos show each column in the alignment as stacks of symbol(s) where the height of a stack is proportional to its informational content, whereas the height of each symbol within the stack is proportional to its frequency in the column. Sequence logos use symbols of either nucleotide or amino acid alphabets.

Codon size reduction as the origin of the triplet genetic code.

The genetic code appears to be optimized in its robustness to missense errors and frameshift errors. In addition, the genetic code is near-optimal in terms of its ability to carry information in addition to the sequences of encoded proteins. As evolution has no foresight, optimality of the modern genetic code suggests that it evolved from less optimal code variants.