FiatFlux - a software for metabolic flux analysis from 13C-glucose experiments. - Nicola Zamboni; Eliane Fischer; Uwe Sauer (BMC Bioinform., 2005)

An analytic and systematic framework for estimating metabolic flux ratios from 13C tracer experiments. - Ari Rantanen; Juho Rousu; Paula Jouhten; Nicola Zamboni; Hannu Maaheimo; Esko Ukkonen (BMC Bioinform., 2008)

anNET: a tool for network-embedded thermodynamic analysis of quantitative metabolome data. - Nicola Zamboni; Anne Kümmel; Matthias Heinemann (BMC Bioinform., 2008)

Metabolite identification and molecular fingerprint prediction through machine learning. - Markus Heinonen; Huibin Shen; Nicola Zamboni; Juho Rousu (Bioinform., 2012)

SUMOFLUX: A Generalized Method for Targeted 13C Metabolic Flux Ratio Analysis. - Maria Kogadeeva; Nicola Zamboni (PLoS Comput. Biol., 2016)

Metabolic network segmentation: A probabilistic graphical modeling approach to identify the sites and sequential order of metabolic regulation from non-targeted metabolomics data. - Andreas Kühne; Urs Mayr; Daniel C. Sévin; Manfred Claassen; Nicola Zamboni (PLoS Comput. Biol., 2017)

SPHN/PHRT: Forming a Swiss-Wide Infrastructure for Data-Driven Sepsis Research. - Adrian Egli; Manuel Battegay; Andrea C. Büchler; Peter Bühlmann; Thierry Calandra; Philippe Eckert; Hansjakob Furrer; Gilbert Greub; Stephan M. Jakob; Laurent Kaiser; Stephen L. Leib; Stephan Marsch; et al. (MIE, 2020)

Computational Metabolomics: From Cheminformatics to Machine Learning (Dagstuhl Seminar 20051). - Sebastian Böcker; Corey Broeckling; Emma Schymanski; Nicola Zamboni (Dagstuhl Reports, 2020)

Comparing representations of biological data learned with different AI paradigms, augmenting and cropping strategies. - Andrei Dmitrenko; Mauro M. Masiero; Nicola Zamboni (MIDL, 2022)

Self-supervised learning for analysis of temporal and morphological drug effects in cancer cell imaging data. - Andrei Dmitrenko; Mauro M. Masiero; Nicola Zamboni (MIDL, 2022)

Computational Metabolomics: From Spectra to Knowledge (Dagstuhl Seminar 22181). - Corey Broeckling; Timothy M. D. Ebbels; Ewy A. Mathé; Nicola Zamboni; Cecilia Wieder (Dagstuhl Reports, 2022)

Regularized adversarial learning for normalization of multi-batch untargeted metabolomics data. - Andrei Dmitrenko; Michelle Reid; Nicola Zamboni (Bioinform., 2023)

Flows on convex polytopes. - Tomek Diederen; Nicola Zamboni (CoRR, 2025)