Author

Federico Baldini

University of LuxembourgORCID 0000-0001-9079-8869Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Organism:human· 2 Assay:metagenomics· 2 Approach:statistical model· 2 Research Focus:differential expression· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Almut HeinkeniD· 2 shared Ines ThieleiD· 2 shared Laurent HeirendtiD· 2 shared Ronan M. T. FlemingiD· 2 shared Dmitry A. RavcheeviD· 1 shared Harry H. LeeiD· 1 shared Jacques RaveliD· 1 shared Jingqiu Liao· 1 shared

Activity by Year

2017-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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2 shared papersSystems Biology

Almut HeinkenORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Preterm birth is associated with xenobiotics and predicted by the vaginal metabolome

William F. Kindschuh, Federico Baldini, Martin C. Liu, Kristin D. Gerson, Jingqiu Liao, Harry H. Lee, Lauren Anton, Pawel Gajer, Jacques Ravel, Maayan Levy, Michal A. Elovitz, Tal Korem

This study identifies vaginal metabolites associated with spontaneous preterm birth and shows they can predict risk with high accuracy using machine learning.

Nature Microbiology · Jan 12, 2023Peer-reviewedSystems Biology

The Microbiome Modeling Toolbox: from microbial interactions to personalized microbial communities

Federico Baldini, Almut Heinken, Laurent Heirendt, Stefanía Magnúsdóttir, Ronan M. T. Fleming, Ines Thiele

The paper introduces a toolbox for modeling microbial interactions and communities using metagenomic data and extends the COBRA Toolbox.

Bioinformatics · Nov 19, 2018Peer-reviewedSystems Biology

Personalized modeling of the human gut microbiome reveals distinct bile acid deconjugation and biotransformation potential in healthy and IBD individuals

Almut Heinken, Dmitry A. Ravcheev, Federico Baldini, Laurent Heirendt, Ronan M. T. Fleming, Ines Thiele

The paper uses personalized microbial community models to analyze bile acid metabolism in healthy and IBD individuals, revealing distinct metabolic potentials and strain contributions.

bioRxiv · Dec 4, 2017 · PreprintSystems Biology