Research Lab

Computational Multi-Omics

Research Interests

Our mission is to understand the (epi)genome biology and its impact on pathological conditions using computational multi-omics approaches. Such methods rely on the statistical analysis and integration of big data (high-throughput sequencing, microarrays, proteomics, high-throughput screening) and clinical/phenotypic data.


The regulation of (epi)genome and transcriptome networks is a crucial component of a healthy cell, but it is relatively unknown the molecular mechanisms underlying its misregulation in diseases: from cancer to age-related disorders. We have been deciphering pathological conditions through multiomics approaches, identifying molecular events to be further used as biomarkers and therapeutic targets.

Research Highlights
Unveiling the complexity of cell biology and underlying disregulation of diseases by deciphering multi-omics data


Given the accumulation of a huge amount of genomic data and biological information, handling and mining big data is becoming increasingly mandatory for major research. In such line, we have contributed for the development of pipelines to process high-throughput sequencing profiles of nascent transcripts, mNET-seq.


Furthermore, we won a grant to organize an EMBO practical course to take place in FCTNOVA focused on “Deciphering Tumor Heterogeneity and Evolution by integration of multi-omics data”.


We have also demonstrated how Big Data Science can contribute for Technology and Biomedicine in the “Sci & Tech for Society” Webinars from NOVA.FCT.


highlight 2020

Representative Projects

  • “Decoding pseudogene transcriptional regulation during cell differentiation” – FCT-MCTES, Total and Unit Funding: € 50,000. Ana Rita Grosso (PI)
  • “Targeting Intra-Tumor heterogeneity as a promising therapeutic strategy for cancer”, FCT-MTES, Total and Unit Funding € 239,478. Ana Rita Grosso, (PI)

Selected Publications

Sabino, JC; de Almeida, MR; Abreu, PL; Ferreira, AM; Caldas, P; Domingues, MM; Santos, NC; Azzalin, CM; Grosso, AR; de Almeida, SF. 2022. Epigenetic reprogramming by TET enzymes impacts co-transcriptional R-loops. eLife, 11, DOI: 10.7554/eLife.69476
Sobral, D; Francisco, R; Duro, L; Videira, PA; Grosso, AR. 2022. Concerted Regulation of Glycosylation Factors Sustains Tissue Identity and Function. BIOMEDICINES, 10, DOI: 10.3390/biomedicines10081805
Sobral, Daniel; Martins, Marta; Kaplan, Shannon; Golkaram, Mahdi; Salmans, Michael; Khan, Nafeesa; Vijayaraghavan, Raakhee; et al. 2022. Genetic and microenvironmental intra-tumor heterogeneity impacts colorectal cancer evolution and metastatic development. Communications Biology, 5, DOI: 10.1038/s42003-022-03884-x
Yu Ting Ong, Jorge Andrade and Max Armbruster, Chenyue Shi, Marco Castro, Ana S. H. Costa, Toshiya Sugino, Guy Eelen, Barbara Zimmermann, Kerstin Wilhelm, Joseph Lim, Shuichi Watanabe, Stefan Guenther, Andre Schneider, Francesca Zanconato, Manuel Kaulich, Duojia Pan and Thomas Braun, Holger Gerhardt, Alejo Efeyan, Peter Carmeliet, Stefano Piccolo, Ana Rita Grosso, Michael Potente. 2022. A YAP/TAZ-TEAD signalling module links endothelial nutrient acquisition to angiogenic growth. Nature Metabolism, 4, DOI: 10.1038/s42255-022-00584-y
Vanda Póvoa; Cátia Rebelo de Almeida; Mariana Maia-Gil; Daniel Sobral; Micaela Domingues; Mayra Martinez-Lopez; Miguel de Almeida Fuzeta; Carlos Silva; Ana Rita Grosso; Rita Fior. 2021. Innate immune evasion revealed in a colorectal zebrafish xenograft model. Nature Communications, DOI: 10.1038/s41467-021-21421-y