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1.
Müller, G. & Müller, T.D.: Transfer of membrane(s) matter(s)-non-genetic inheritance of (metabolic) phenotypes? Front. Mol. Biosci. 11:1347397 (2024)
2.
D'Angelo, D.* ; Vecellio Reane, D. & Raffaello, A.*: Neither too much nor too little: Mitochondrial calcium concentration as a balance between physiological and pathological conditions. Front. Mol. Biosci. 10:1336416 (2023)
3.
Kolonko-Adamska, M.* et al.: Interaction patterns of methoprene-tolerant and germ cell-expressed Drosophila JH receptors suggest significant differences in their functioning. Front. Mol. Biosci. 10:1215550 (2023)
4.
Amara, A.* et al.: Networks and graphs discovery in metabolomics data analysis and interpretation. Front. Mol. Biosci. 9:841373 (2022)
5.
Apaolaza Gallegos, S.P. ; Petropoulou, P.-I. & Rodriguez-Calvo, T.: Whole-slide image analysis of human pancreas samples to elucidate the immunopathogenesis of type 1 diabetes using the QuPath software. Front. Mol. Biosci. 8:689799 (2021)
6.
Schlieben, L.D. ; Prokisch, H. & Yépez, V.A.*: How machine learning and statistical models advance molecular diagnostics of rare disorders via analysis of RNA sequencing data. Front. Mol. Biosci. 8:647277 (2021)
7.
Sillner, N. et al.: Longitudinal profiles of dietary and microbial metabolites in formula- and breastfed infants. Front. Mol. Biosci. 8:660456 (2021)
8.
Witting, M. et al.: Modeling meets metabolomics— the WormJam consensus model as basis for metabolic studies in the model organism Caenorhabditis elegans. Front. Mol. Biosci. 5:96 (2018)
9.
Delaforge, E.* et al.: Investigating the role of large-scale domain dynamics in protein-protein interactions. Front. Mol. Biosci. 3, 54 (2016)
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