Curriculum
Computer Science for Societal Challenges and Innovation, XL series
Grant sponsor
Dip. di Scienze Biomediche (su fondi HORIZON INFRA2023-DEV-01 ELIXIR-STEERS)
Supervisor
Silvio Tosatto
Co-supervisor
to be defined
Contact
gavinmichael.farrell@studenti.unipd.it

Project description
My PhD project, entitled "Expanding the DOME Recommendations for Machine Learning in the Life Sciences," seeks to enhance the accessibility and understandability of machine learning (ML) methods in life science literature. In response to the growing use of ML in the life sciences, this project addresses the challenges of standardizing ML method descriptions in scientific publications. My project aims to automate and accelerate the annotation process of ML methods in life science papers according to the DOME (Data, Optimization, Model, Evaluation) recommendations, reducing the reliance on manual curation. This will involve developing new text-mining, ML, and natural language processing techniques to facilitate more efficient and comprehensive annotations. By expanding the DOME Registry, the project will improve the reproducibility and reusability of ML methods in life science research, lowering barriers for non-expert readers and enhancing the overall impact of ML in the domain. The outcomes will include a more extensive, standardised corpus of annotated literature and improved registry functionalities, with significant interdisciplinary contributions from computer science, life sciences, and social sciences.