Functional genomics of fungal disease
Genetic analysis of molecular and functional traits in immune cells, such as gene and protein expression and effector functions, offers a promising strategy for investigating phenotypic variation and dissecting the molecular mechanisms underlying propensity to infection. We propose a global approach to elucidate the genetic architecture of antifungal immunity to major fungal pathogens by investigating the molecular processes of immune function at the cellular level during fungal infection and in human patients suffering from fungal disease. Our major goals include the identification of interindividual genetic variation that modulates fungal-sensing transcriptional and functional responses, the annotation of molecular and functional phenotypes whereby genetic variants control antifungal immune responses, and the dissection of the contribution of genetic variants to the development of fungal infection in human patients at risk. Using cutting-edge research tools that combine genome-wide genotyping, transcriptomic profiling, advanced cellular model systems, and studies in human patients, we propose to establish an unprecendented understanding of the genetic, molecular and biological processes that define an individual’s susceptibility to fungal disease.
Funding Agency
“la Caixa” Foundation; European Commission (H2020); Gilead Sciences
Project Reference
LCF/PR/HR17/52190003, H2020-SC1-2019-847507, and Gilead Research Scholars – Anti-Fungals
Project Members
Cristina Cunha
Fernando Rodrigues
Rita Silva-Gomes
Samuel M Gonçalves
Inês Caldeira
Raquel Fernandes
Main Project Outcomes
S. Queirós, “Right ventricular segmentation in multi-view cardiac MRI using a unified U-net model”, in E. Puyol Antón et al. (eds) Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge. STACOM 2021. Lecture Notes in Computer Science, vol 13131, pp. 287-295, Springer, Cham, 2022.
“Best Paper Award in the M&Ms-2 Challenge”, by M&Ms2 Challenge organizers and the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society.
Contact us
Phone: +351 253 604 967
Fax: +351 253 604 809
Email: icvs.sec@med.uminho.pt
Address
Life and Health Sciences
Research Institute (ICVS)
School of Medicine,
University of Minho,
Campus de Gualtar
4710-057 Braga
Portugal
Copyright ©2022 ICVS. All Rights Reserved
Copyright ©2022 ICVS. All Rights Reserved
Address
Life and Health Sciences
Research Institute (ICVS)
School of Medicine,
University of Minho,
Campus de Gualtar
4710-057 Braga
Portugal
Copyright ©2022 ICVS. All Rights Reserved
Address
Life and Health Sciences
Research Institute (ICVS)
School of Medicine,
University of Minho,
Campus de Gualtar
4710-057 Braga
Portugal