Molecular biology (genomic and evolutionary analysis implemented on life sciences)

The field of molecular biology studies and analyses genomic and evolutionary processes to answer questions that do not yet have a clear definition.

Research fields

DNA and entropy
It is sometimes difficult to explain the evolution of DNA, especially when there is not yet complete knowledge about it. DNA is formed by specific numerical symmetries between adenine and timine and between citosine and guanine that cannot be explained by the theory of evolution by natural selection alone. Entropy is applied in this research to study and theorise new models of evolution. At the base of the concept is: step by step the system gets to a new equilibrium, different from the previous one, reaching an increasing disorder status. Therefore, our research studies how the concept of entropy can be applied to explain different rules that help bring understanding to genome evolution.

Genomic comparison
This branch of study investigates the animal model genome using an evolutionary and comparative approach. It involves the creation and development of public databases for the collection and subsequent analysis of genomic data for all sequencing vertebrates. The field will provide specific information about the genotypic and phenotypic differences of animal species.

NGS Analysis
Next-generation sequencing (NGS) provides millions of DNA fragments in less time than the traditional method. The aim of the research is to conduct analysis that provides answers to whole genome sequencing, CHiP-sequencing, RNA-sequencing, and to consider tumour samples in animal models.

Development of bioinformatics software
This consists in studying and applying new software using data obtained with next-generation sequencing technology. The main purpose of this research field is scanning and graphically viewing, eventually interactive, model organisms. To achieve this, the research team uses Python and PostregreSQL languages and MongoDB and Django databases.

Machine learning algorithms for biological data analysis
This involves the implementation of machine learning algorithms to develop new platforms that can complete and observe different types of omics data simultaneously. Omics data sometimes differ in origin and typology, such as in a human or living being. The intention is to insert them into unique software to match their expected outcomes.

Population genetics
This study relates to populations—biological units that are much more limited than species. It consists of both the investigation of genetics and genomics.

Transposable elements analysis
Transposable elements are segments of DNA that can move to many positions in the genome. This field of study concerns the evolutionary dynamic in terms of both evolutionary and speciation processes (the foundation of a new species) in mammals.