Project Overview

The use of pesticides in agriculture is essential to protect crops from harmful insects, diseases, and weeds, and to increase food production. However, the potential risks posed by these chemical compounds to human health and the environment have raised concerns. The traditional approach to evaluating the toxicity of pesticides involves animal testing, which is expensive, time-consuming, and ethically challenging. Furthermore, the large number of emerging chemicals for crop protection makes it difficult to assess their potential toxicity using traditional methods. To address these challenges, this project focuses on developing a software tool that can effectively analyze toxicological data sets within the Adverse Outcome Pathway (AOP) framework. In particular, transcriptomics data will be used to develop a multidisciplinary workflow that allows the link between transcriptomics and phenotype to be established, integrating toxicological data with interactomics and pathological endpoints. The project is structured around three main objectives: the development of a new model for the identification of key events, integrating toxicogenomic and protein-protein interaction data; the development of a literature framework for the identification of gene-gene networks and hub genes associated with each compound exposure and adverse endpoint; and the development of a web interface that integrates transcriptomics, interactomics, and pathological endpoints. The project aims to promote understanding of complex cellular and organismal responses to toxic substances, identifying causal networks and associating them with pathological endpoints. This will allow the development of robust tools for integration into the AOP framework, generating existing knowledge that links molecular-level perturbation of a biological system and an adverse biological outcome with predictive or regulatory relevance.”


  • BSc Biotechnology Università degli studi di Sassari, Italy

  • Bioinformatics and Biostatistics Certificate, QUB