Gian Benucci, Ph.D.

Gian Benucci

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Informational and statistical analyst II
Department of Plant, Soil and Microbial Sciences


B.S. and M.S, Agriculture Science and Technology, University of Perugia, Italy.
P.h.D., Biology and Biotechnology, University of Perugia, Italy.

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Dr. Gian Maria Niccolo’ (Nico) Benucci is a Data Analyst and Bioinformatician at the Great Lakes Bioenergy Research Center (GLBRC) and the Department of Plant, Soil and Microbial Sciences at Michigan State University (MSU). Dr. Benucci is a broadly trained biologist and mycologist with a strong passion for ecology and plant-microbe interactions. His doctoral research centered on truffles (Tuber, Ascomycota), an iconic and economically significant group of ectomycorrhizal fungi, providing a unique lens through which to examine mycorrhizal symbioses and laid the foundation for his current research trajectory, which focuses on the holobiont (the host and its microbiome). Dr. Benucci’s holistic approach addresses fundamental questions about how microbial communities' structure and function shift in response to environmental changes. His research also explores ways to manipulate these communities to enhance host health and fitness. Dr. Benucci’s research lies at the intersection of genomics, ecology, and evolution and leverages the power of big data, bioinformatics, statistics, and machine learning.
     During his research career, Dr. Benucci developed and led several research projects, obtained funding, published more than 55 peer-reviewed articles, 6 conference proceedings, and 2 invited book chapters. His scientific network involves 160+ national and international collaborators and he is involved with the National Microbiome Data Collaborative and the Global Initiative of Sustainable Agriculture and Environment projects. He also co-leads the bioinformatics support hours and bioinformatics community of practice (CoP) for the GLBRC.


STT464 – Statistics for Biologists (fall semester 2024).

PLB847 – Advanced Mycology, “Bioinformatics and Communuty Ecology with R” module (2015-2017).


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