• Applications of Machine Learning in Human Microbiome Studies: A Review on Feature Selection, Biomarker Identification, Disease Prediction and Treatment 

      Marcos-Zambrano, Laura Judith; Hadziabdic, Kanita Karaduzovic; Turukalo, Tatjana Loncar; Przymus, Piotr; Trajkovik, Vladimir; Aasmets, Oliver; Berland, Magali; Gruca, Aleksandra; Hasic, Jasminka; Hron, Karel; Klammsteiner, Thomas; Kolev, Mikhail; Lahti, Leo; Lopes, Marta B.; Moreno, Victor; Naskinova, Irina; Org, Elin; Paciencia, Ines; Papoutsoglou, Georgios; Shigdel, Rajesh; Stres, Blaz; Vilne, Baiba; Yousef, Malik; Zdravevski, Eftim; Tsamardinos, Ioannis; Carrillo de Santa Pau, Enrique; Claesson, Marcus J.; Moreno-Indias, Isabel; Truu, Jaak (Journal article; Peer reviewed, 2021)
      The number of microbiome-related studies has notably increased the availability of data on human microbiome composition and function. These studies provide the essential material to deeply explore host-microbiome associations ...
    • Machine learning approaches in microbiome research: challenges and best practices 

      Papoutsoglou, Georgios; Tarazona, Sonia; Lopes, Marta B.; Klammsteiner, Thomas; Ibrahimi, Eliana; Eckenberger, Julia; Novielli, Pierfrancesco; Tonda, Alberto; Simeon, Andrea; Shigdel, Rajesh; Béreux, Stéphane; Vitali, Giacomo; Tangaro, Sabina; Lahti, Leo; Temko, Andriy; Claesson, Marcus J.; Berland, Magali (Journal article; Peer reviewed, 2023)
      Microbiome data predictive analysis within a machine learning (ML) workflow presents numerous domain-specific challenges involving preprocessing, feature selection, predictive modeling, performance estimation, model ...