This project is using machine learning and 'omics'-based approaches to investigate the molecular mechanisms and pathogens that cause newborns to be highly vulnerable to infection and sepsis.
Publications:
- An AY, Acton E, Idoko OT, Shannon CP, Blimkie TM, Falsafi R, Wariri O, Imam A, Dibbasey T, Bennike TB, Smolen KK, Diray-Arce J, Ben-Othman R, Montante S, Angelidou A, Odumade OA, Martino D, Tebbutt SJ, Levy O, Steen H, Kollmann TR, Kampmann B, Hancock REW, Lee AH; EPIC Consortium. Predictive gene expression signature diagnoses neonatal sepsis before clinical presentation. AEBioMedicine. 2024 Oct 24:105411.
- Martino D, Kresoje N, Amenyogbe N, Ben-Othman R, Cai B, Lo M, Idoko O, Odumade OA, Falsafi R, Blimkie TM, An A, Shannon CP, Montante S, Dhillon BK, Diray-Arce J, Ozonoff A, Smolen KK, Brinkman RR, McEnaney K, Angelidou A, Richmond P, Tebbutt SJ; EPIC-HIPC consortium; Kampmann B, Levy O, Hancock REW, Lee AHY, Kollmann TR. DNA Methylation signatures underpinning blood neutrophil to lymphocyte ratio during first week of human life. Nat Commun. 2024 Sep 17;15(1):8167.
- Fidanza M, Hibbert J, Acton E, Harbeson D, Schoeman E, Skut P, Woodman T, Eynaud A, Hartnell L, Brook B, Cai B, Lo M, Falsafi R, Hancock REW, Chiume-Kayuni M, Lufesi N, Popescu CR, Lavoie PM, Strunk T, Currie AJ, Kollmann TR, Amenyogbe N, Lee AH. Angiogenesis-associated pathways play critical roles in neonatal sepsis outcomes. Sci Rep. 2024 May 20;14(1):11444.