Pathway analysis is a set of widely used tools for research in life sciences intended to give meaning to high-throughput biological data. Combining biological knowledge with statistical and mathematical analysis and using computational algorithms we can generate models that allow us to link genotype with phenotype; thus; we can predict the behavior of an organism under different conditions.
In recent years, the use of next generation sequencing (NGS) has made it possible to get an enormous number of sequences at low costs. However, analysis of genomic data has become more difficult for multiple reasons. On the one hand, these technologies generate a huge amount of data that is difficult to analyze and is prone to errors. On the other hand, carrying out an analysis and a correct annotation is usually quite difficult and there is no gold standard. Performing these analyzes requires knowledge of programming and statistics, as well as biology. Therefore, performing genomic assembly and annotation requires expertise in bioinformatics and computational biology.
Despite the above, making a correct genomic annotation is of great importance since they are used in the study of the virulence of bacteria and fungi. They allow better taxonomic assignments that allow analyzing the bio-safety of organisms; They are also useful for the study of metabolic pathways, which allows performance predictions of organisms of industrial interest, among other applications.
We have experience applying bioinformatics and big data analytics to perform high-quality assemblies and annotations.
Comparative genomics is based on the analysis and comparison of complete genomic sequences from different organisms. This allowed us to discover new biomarkers, which combined with AI, made it possible to assign species with enormous precision. As well as how it allows us to discover the function of un-annotated genes and understand the mechanisms of evolution of organisms.
Among the services we provide are: Core/Pan-genome analysis, UPMGA dendrogram based on average nucleotide identity, BLAST-search against all genes or genes included in the pan-genome, Phylogenomic tree using a Machine Learning Approach.
Taxonomic profiling allows us to know the taxonomic composition and relative abundance of the organisms present in a meta-genomic sample, which is sequenced using NGS and then analyzed using bioinformatic tools.
Mariano Torres Manno