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A toolbox of machine learning software to support microbiome analysis

Marcos-Zambrano, Laura Judith; López-Molina, Víctor Manuel; Bakir-Gungor, Burcu; Frohme, Marcus; Karaduzovic-Hadziabdic, Kanita; Klammsteiner, Thomas; Ibrahimi, Eliana; Lahti, Leo; Loncar-Turukalo, Tatjana; Dhamo, Xhilda; Simeon, Andrea; Nechyporenko, Alina; Pio, Gianvito; Przymus, Piotr; Sampri, Alexia; Trajkovik, Vladimir; Lacruz-Pleguezuelos, Blanca; Aasmets, Oliver; Araujo, Ricardo; Anagnostopoulos, Ioannis; Aydemir, Önder; Berland, Magali; Calle, M. Luz; Ceci, Michelangelo; Duman, Hatice; Gündoğdu, Aycan; Havulinna, Aki S.; Kaka Bra; Kardokh Hama Najib; Kalluci, Eglantina; Karav, Sercan; Lode, Daniel; Lopes, Marta B.; May, Patrick; Nap, Bram; Nedyalkova, Miroslava; Paciência, Inês; Pasic, Lejla; Pujolassos, Meritxell; Shigdel, Rajesh; Susín, Antonio; Thiele, Ines; Truică, Ciprian-Octavian; Wilmes, Paul; Yilmaz, Ercument; Yousef, Malik; Claesson, Marcus Joakim; Truu, Jaak; Carrillo de Santa Pau, Enrique (Frontiers Media SA, 2023)

The human microbiome has become an area of intense research due to its potential impact on human health. However, the analysis and interpretation of this data have proven to be challenging due to its complexity and ...