Gabriela is part of the recently created Integrative Bioinformatics Group at IBB-CONICET-UNER. She is also part of the the Bioinformatics Research group at sinc(i)-CONICET-UNL. Her current interests are bioinformatics and statistics algorithms to integrate biological data from multiple sources and their application in cancer research. During her PhD, she had developed several bioinformatics tools for analysing next generation sequencing data mainly applied to cancer projects. As a postdoc, she is working on the development of machine learning models for predicting functional annotation of gene and proteins. She is also focused on the use of these models for both identifying functions of unannotated entities and for predicting new functionalities of gene and proteins in the context of cancer research. 

Project summary

Gabriela's project is aimed to develop bioinformatics tools for biological function inference of genes and proteins. To achieve this, multi-omics data, clinical and/or experimental data will be integrated with functional annotations, such as those provided by Gene Ontology and UniProt databases, using deep learning algorithms. The inference of gene and protein functions will allow a deeper understanding of complex biological processes such as those related to tumor development and progress.

Project outcomes and impact

TBA