Glaucia Maria de Mendonça Fernandes is a translational researcher focused on glioblastoma and meningioma. Her current projects integrate advanced imaging, 3D genome architecture (Hi-C), and machine learning to identify molecular signatures and predictive biomarkers in brain tumors. She also develops computational pipelines for integrating omics and histopathological data, aiming to improve diagnostic accuracy and stratification in neuro-oncology.
Fernandes has authored 19 peer-reviewed publications reflecting her interest in interdisciplinary innovation at the intersection of neuroscience, cancer biology, and data science.
Areas of Expertise
- MicroRNAs, circRNA and epitranscriptomics (m6A modifications)
- Bioinformatics and co-expression networks (WGCNA)
- Machine learning applied to oncology
- Imaging analysis
- Integration of clinical and molecular data
- Cellular and molecular biology analysis
- Tumor stem cells (CSCs)
- 2D and 3D cell biology models
Research Interests
- Molecular characterization of brain tumors (glioblastoma, meningioma)
- Investigation of cancer stem cells and mechanisms of treatment resistance
- Epigenetic regulation in neuro-oncology (RNA methylation, non-coding RNAs)
- Integration of histopathological imaging with omics data
- Development of machine learning pipelines for biomarker discovery
- Application of R programming for data analysis and visualization
- Use of 3D genome architecture (Hi-C) to explore chromatin organization in tumors
- Translational neuroscience and precision medicine approaches
- Innovation at the intersection of computational biology, pathology, and cancer research
See research publications and more on FIU Discovery.
Honors & Awards
- Best abstract for R13 Grant Travel Awards, American Association of Neuropathology, 2025
- Best project, V INTERONCO – USP/São Paulo, 2017
- Honor, VII CAIC – Annual Scientific Initiation Congress, FAMERP, 2010
Committees & Professional Organizations
- Postdoctoral Program Committee – FIU, 2025
- Human Research Ethics Committee – FAMERP, 2019-2022
Education
- MBA, Data Sciences and Analytics, Universidade de São Paulo (ESALQ/USP), São Paulo, SP, Brazil, 2022
- Ph.D., Health Sciences, Faculdade de Medicina de São José do Rio Preto-FAMERP, São José do Rio Preto, SP, Brazil, 2019
- M.S., Health Sciences, Faculdade de Medicina de São José do Rio Preto-FAMERP, São José do Rio Preto, SP, Brazil, 2013
- B.S., Biological Sciences, Centro Universitário do Norte Paulista, São José do Rio Preto, SP, Brazil, 2008