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Application of Machine Learning in Metagenomics (2023)

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Application of Machine Learning in Metagenomics

Contributors: Luka Bulić, Lucia Crvelin, Niko Kaštelan, Mirta Krajinović, Lucija Topolko (project leader), Marko Žagar

Supervisor: Assoc. prof. Mirjana Domazet-Lošo, PhD

"Application of Machine Learning in Metagenomics" was an undergraduate machine learning project created at the Faculty of Electrical Engineering and Computing, University of Zagreb (course "Project R"). The project aimed to solve the issue of disease prediction based on the metagenomic findings in a large population of patients, using the tools of machine learning. The database used for model training and testing was made publicly available as part of the following study:

Pasolli E, Truong DT, Malik F, Waldron L, Segata N (2016) Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights. PLoS Comput Biol 12(7): e1004977. doi:10.1371/journal.pcbi.1004977

Two approaches were used, python programming to create a multiclassifier and WEKA to create a series of binary classifiers. The methods and results can be found in the uploaded technical and project documentation.

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