Graph-Based Disease Prediction in Neuroimaging: Investigating the Impact of Feature Selection. Worldwide Congress on “Genetics, Geriatrics and Neurodegenerative Diseases Research", 223--230, 2022. [PUMA: Disease Feature Graph-Based Impact Investigating Neuroimaging Prediction Selection learning]
Federated Learning on Transcriptomic Data: Model Quality and Performance Trade-Offs. Computational Science – ICCS 2024: 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part IV, 279–293, Springer-Verlag, Berlin, Heidelberg, 2024. [PUMA: Cell Classification, Disease Federated Learning, Prognosis Type] URL
Neural network-assisted humanisation of COVID-19 hamster transcriptomic data reveals matching severity states in human disease. eBioMedicine, (108):105312, 2024. [PUMA: COVID-19, Cross-species Deep Disease Hamster RNA-seq, Single-cell analysis, learning matching, model, state] URL
Personalized structural biology reveals the molecular mechanisms underlying heterogeneous epileptic phenotypes caused by de novo KCNC2 variants. Human Genetics and Genomics Advances, (3)4:100131, 2022. [PUMA: DEE, Diseases KCNC2, Network, Undiagnosed and biology, developmental disease dynamics electrophysiology, encephalopathy, epileptic interpretation, molecular personalized rare simulations, structural variant variant,] URL
Identifying digenic disease genes via machine learning in the Undiagnosed Diseases Network. Am. J. Hum. Genet., (108)10:1946--1963, Elsevier BV, October 2021. [PUMA: Diseases Network; UDN; Undiagnosed clinical digenic disease disease; learning; machine oligogenic prediction; rare topic_lifescience]