Davide Chiarugi, MSc, PhD
Davide holds a Masters Degree in Molecular Biology and a PhD in Computer Science.
He is a Computational Biologist with extensive experience in scientific computing and data science.
His competences include the analysis and integration of -omics and multivariate data (genomics, transcriptomics, metabolomics and proteomics), biostatistics (including clinical trials design, design and analysis of precision medicine trials), statistical data analysis, modelling simulation of (bio)chemical systems, machine learning.
His research interests range from (applied) statistics to the study of the translational control of gene expression.
Sherine Awad, MSc, PhD
Sherine got her PhD in Computer Science from Michigan State University. She had her postdoctoral training in Bioinformatics at the University of California Davis. She has a broad expertise in the study of gene regulatory networks and in the analysis of omics data, especially genomics and metagenomics. She has a professional-level knowledge in the design and implementation of reproducible pipelines, new algorithms, and tools for the analysis and integration of complex datasets.
Sherine’s research interests include the development of computational methods for the identification and characterisation of germline variants and structural variations. She is also interested in the study of the translational control of gene expression.
Alexander Mörseburg, MPhil, PhD
Alexander is a computational biologist with a background in population genomics and evolutionary biology. He holds a PhD in Biological Anthropology from the University of Cambridge. His key competencies are the analysis of large-scale genomics data and the application of advanced statistical techniques such as multilevel modelling and machine learning to biological data.
Alexander’s research interests lie in using computational methods to improve our understanding and treatments of metabolic and age-related diseases in close collaboration with experimental and clinical researchers. He is particularly enthusiastic about investigating the geroscience hypothesis in humans, which posits that therapeutically addressing ageing physiology directly will prevent the onset or mitigate the severity of many chronic diseases.
Ryan Patterson-Cross, MSc(Res)
Ryan is a computational biologist with a background in single-cell RNA sequencing. He holds a MSc by Research in Clinical Medicine from the University of Oxford, where he studied mitochondrial turnover in Parkinson’s Disease. His key competencies include the integration and analysis of diverse transcriptomics data and the application of machine learning methods to these data.
Ryan has a broad range of research interests, from transcription factor-mediated re-programming of iPSCs to the design of tools that reduce bias and increase reproducibility in analysis pipelines. He also has a passion for developing good documentation to improve the usability of computational tools.
Giorgia Giacomini, MSc
Giorgia is a visiting student at the Bio2 Core.
She is a PhD student in Biochemistry and Molecular Biology at the University of Siena, Italy. She holds a bachelor’s degree in Biological Sciences and a Masters Degree in Cellular and Molecular Biology.
Her PhD project focuses on the translational control of gene expression through studying a data analysis approach, with particular attention to Ribo-seq data to gain insights on translational dysregulation in cancer.
Giorgia’s more general research interests lie in the computational analysis of -omics data, (bio)statistics, cancer genomics and machine learning. She is also a member of the Siena Artificial Intelligence Lab (SAILAb) at the Information Engineering and Mathematics Department.