Knowledge Discovery for Higher Education Student Retention Based on Data Mining: Machine Learning Algorithms and Case Study in Chile.

Data mining is employed to extract useful information and to detect patterns from often large data sets, closely related to knowledge discovery in databases and data science. In this investigation, we formulate models based on machine learning algorithms to extract relevant information predicting student retention at various levels, using higher education data and specifying the relevant variables involved in the modeling. Then, we utilize this information to help the process of knowledge discovery.

Evaluation of the immunogenicity of a recombinant HSV-1 vector expressing human group C rotavirus VP6 protein.

Group C Rotavirus (RVC) has been associated globally with sporadic outbreaks of gastroenteritis in children and adults. RVC also infects animals, and interspecies transmission has been reported as well as its zoonotic potential. Considering its genetic diversity and the absence of effective vaccines, it is important and necessary to develop new generation vaccines against RVC for both humans and animals.

A complete approach for recombinant protein expression training: From gene cloning to assessment of protein functionality*.

A practical course was given to undergraduate biology students enrolled in the elective course "Introduction to Genetic Engineering" at the Federal University of São Carlos (UFSCar), São Paulo, Brazil. The goal of the course was to teach current molecular biology tools applied to a real research situation that could be reported by the students themselves. The purpose was to produce a plant recombinant protein and demonstrate a heretofore unreported biological activity.