Ylenia Giarratano

Research Fellow

Background

Ylenia is a Research Fellow at the University of Edinburgh. Her research focuses on using image processing and machine learning to study biomarkers that can detect changes in the eye caused by ocular and systemic diseases. By detecting these changes early, we can better understand and treat conditions like cardiovascular disease, neurodegenerative disease, and diabetes. This will help us achieve the full potential of patient-specific approaches to eye care.

Qualifications

- Doctor of Philosophy (PhD), The University of Edinburgh(UK): A computational framework for the discovery of retinal microvascular biomarkers of diabetes and renal disease

- Master of Science,  University of Trento (IT), Mathematics for Life Sciences: modelling statistics, and analysis of biosystems

- Bachelor of Science, University of Palermo (IT): Mathematics

Undergraduate teaching

Course tutor: Quantitative Skills for Biologists 1 (2018-2019) (2019-2020)[SV1-SEM1]

Lab demonstrator: Molecules to Society 2a ((2019-2020-2022)MBChB]

  • Giarratano Y, Pugh D, Farrah T et al. (2022): Novel retinal vascular phenotypes for the potential assessment of long-term risk in living kidney donors. Kidney International (2022) 102, 661–665;  https://doi.org/10.1016/j.kint.2022.06.019
  • Barbacena P, Dominguez-Cejudo M, Fonseca CG, Gómez-González M, Faure LM, Zarkada G, Pena A, Pezzarossa A, Ramalho D, Giarratano Y, Ouarné M, Barata D, Fortunato IC, Misikova LH, Mauldin I, Carvalho Y, Trepat X, Roca-Cusachs P, Eichmann A, Bernabeu MO, Franco CA. Competition for endothelial cell polarity drives vascular morphogenesis in the mouse retina. Dev Cell. 2022 Oct 10;57(19):2321-2333.e9. doi: 10.1016/j.devcel.2022.09.002. PMID: 36220082; PMCID: PMC9552591. 10.1016/j.devcel.2022.09.002
  • Gabriele Beltramo, Primoz Skraba, Rayna Andreeva, Rik Sarkar, Ylenia Giarratano, Miguel O. Bernabeu. Euler characteristic surfaces. Foundations of Data Science, 2022, 4(4): 505-536. 10.3934/fods.2021027

  • Ylenia Giarratano, Eleonora Bianchi, Calum Gray, Andrew Morris, Tom MacGillivray, Baljean Dhillon, Miguel O. Bernabeu; Automated Segmentation of Optical Coherence Tomography Angiography Images: Benchmark Data and Clinically Relevant Metrics. Trans. Vis. Sci. Tech. 2020;9(13):5 https://doi.org/10.1167/tvst.9.13.5.
  • Giarratano, Y., Pavel, A., Lian, J., Andreeva, R., Fontanella, A., Sarkar, R., .. Bernabeu, M. O. (2020). A Framework for the Discovery of Retinal Biomarkers in Optical Coherence Tomography Angiography (OCTA) In: Fu H., Garvin M.K., MacGillivray T., Xu Y., Zheng Y. (eds) Ophthalmic Medical Image Analysis. OMIA 2020. Lecture Notes in Computer Science, vol 12069. Springer, Cham. https://doi.org/10.1007/978-3-030-63419-3_16
  • Andreeva R., Fontanella A., Giarratano Y., Bernabeu M.O. (2020) DR Detection Using Optical Coherence Tomography Angiography (OCTA): A Transfer Learning Approach with Robustness Analysis. In: Fu H., Garvin M.K., MacGillivray T., Xu Y., Zheng Y. (eds) Ophthalmic Medical Image Analysis. OMIA 2020. Lecture Notes in Computer Science, vol 12069. Springer, Cham. https://doi.org/10.1007/978-3-030-63419-3_2
  • Dataset: Optical Coherence Tomography Angiography retinal scans and segmentations (2020) :https://doi.org/10.7488/ds/2729.
  • Diego Fioravanti, Ylenia Giarratano, Valerio Maggio, Claudio Agostinelli, Marco Chierici, Giuseppe Jurman, Cesare Furlanello: Phylogenetic convolutional neural networks in metagenomics. BMC Bioinformatics 19-S(2): 49:1-49:13 (2018) doi: 10.1186/s12859-018-2033-5
  • Giulio Caravagna, Ylenia Giarratano, Daniele Ramazzotti, Trevor A. Graham, Guido Sanguinetti, Andrea Sottoriva: Detecting repeated cancer evolution in human tumors from multi-region sequencing data. Nature Methods volume 15, pages707–714 (2018) doi: 10.1038/s41592-018-0108-x

2021: Travel Grant ARVO2021

2021: SINAPSE Image of the Month (January 2021)

2020: Best Presentation Award Runner-Up OMIA7, MICCAI2020

2020: Best Presentation Award SINAPSE 2020 Annual Meeting 

2018: Academic Merit Award, University of Trento