Publication
2025
- Parkinson, E. et al. 2025. A rapid time-resolved host gene expression signature predicts responses to antibiotic treatment in neonatal bacterial sepsis. Science Translational Medicine 17 (826) eadt1938. (10.1126/scitranslmed.adt1938)
- Parkinson, E. 2025. Improving diagnosis and monitoring of neonatal sepsis through machine learning analysis of clinical and transcriptomic data. PhD Thesis , Cardiff University.
2023
- Parkinson, E. et al. 2023. Gene filtering strategies for machine learning guided biomarker discovery using neonatal sepsis RNA-seq data. Frontiers in Genetics 14 1158352. (10.3389/fgene.2023.1158352)
- Oruganti, S. et al., 2023. Immune and metabolic markers for identifying and investigating severe Coronavirus disease and Sepsis in children and young people (pSeP/COVID ChYP study): protocol for a prospective cohort study. BMJ Open 13 e067002. (10.1136/bmjopen-2022-067002)
Articles
- Parkinson, E. et al. 2025. A rapid time-resolved host gene expression signature predicts responses to antibiotic treatment in neonatal bacterial sepsis. Science Translational Medicine 17 (826) eadt1938. (10.1126/scitranslmed.adt1938)
- Parkinson, E. et al. 2023. Gene filtering strategies for machine learning guided biomarker discovery using neonatal sepsis RNA-seq data. Frontiers in Genetics 14 1158352. (10.3389/fgene.2023.1158352)
- Oruganti, S. et al., 2023. Immune and metabolic markers for identifying and investigating severe Coronavirus disease and Sepsis in children and young people (pSeP/COVID ChYP study): protocol for a prospective cohort study. BMJ Open 13 e067002. (10.1136/bmjopen-2022-067002)
Thesis
- Parkinson, E. 2025. Improving diagnosis and monitoring of neonatal sepsis through machine learning analysis of clinical and transcriptomic data. PhD Thesis , Cardiff University.