Genomics is the study of the structure and organization of genes and genomes of any type of living organism, in terms of how they regulate, what their functions are, what their structure is, etc.
This study has two research paths. One is a more experimental approach of genomics where scientists, in order to answer their research questions, work in the laboratory to try to modificate the genome of a specific organism, and how this modification implies changes in his phenotype, for example.
The other path is the one that CBIB has taken, which is a mix of both laboratory and experimental work focused on analysis of genomics through computers.
This means that with computational tools, investigators look for genetic variations in genomes and try to infer processes through patterns that they discover and analyze in these genomes.
And since these patterns are complex, researchers need to use computers as an aid to the analysis. There are several cases in which the data amount is so big, that it´s known as Big Data Genomics.
CBIB has developed several projects based on Computer Genomics that -in two or three steps- seek to solve public health issues, both locally and globally.
This helps decision makers to create new public policies, and improving society in general.
Some examples are:
-Evaluation Of Computational Methods For Human Microbiome Analysis: A Case Study On Oral Microbiome And Childhood Asthma.
-Determination of possible causal agents of leaf damage in Araucaria araucana through a comparative study of the microbial structure and its association with environmental variables.
-Revealing Spatial And Seasonal Patterns Of Microbial Genetic Diversity Through Metagenomics In A Human Impacted Ecosystem.
-Bioinformatics and computational biology are permeating all aspects of biology, transforming it into a more qualitative and exact science thanks to the capacity to analyse big amounts of data.
In this matter, the work of CBIB is essential to train new generations of scientists who are able to read these large amount of available data and use computational genomics to carry out better investigations.