Browsing Bergen Open Research Archive by Author "Simeon, Andrea"

Now showing items 1-4 of 4

    • Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action 

      D’Elia, Domenica; Truu, Jaak; Lahti, Leo; Berland, Magali; Papoutsoglou, Georgios; Ceci, Michelangelo; Zomer, Aldert; Lopes, Marta B.; Ibrahimi, Eliana; Gruca, Aleksandra; Nechyporenko, Alina; Frohme, Marcus; Klammsteiner, Thomas; Pau, Enrique Carrillo-de Santa; Marcos-Zambrano, Laura Judith; Hron, Karel; Pio, Gianvito; Simeon, Andrea; Suharoschi, Ramona; Moreno-Indias, Isabel; Temko, Andriy; Nedyalkova, Miroslava; Apostol, Elena-Simona; Truică, Ciprian-Octavian; Shigdel, Rajesh; Telalović, Jasminka Hasić; Bongcam-Rudloff, Erik; Przymus, Piotr; Jordamović, Naida Babić; Falquet, Laurent; Tarazona, Sonia; Sampri, Alexia; Isola, Gaetano; Pérez-Serrano, David; Trajkovik, Vladimir; Klucar, Lubos; Loncar-Turukalo, Tatjana; Havulinna, Aki S.; Jansen, Christian; Bertelsen, Randi Jacobsen; Claesson, Marcus Joakim (Journal article; Peer reviewed, 2023)
      The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which ...

    • 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 ...

    • Overview of data preprocessing for machine learning applications in human microbiome research 

      Ibrahimi, Eliana; Lopes, Marta B.; Dhamo, Xhilda; Simeon, Andrea; Shigdel, Rajesh; Hron, Karel; Stres, Blaž; D’Elia, Domenica; Berland, Magali; Marcos-Zambrano, Laura Judith (Journal article; Peer reviewed, 2023)
      Although metagenomic sequencing is now the preferred technique to study microbiome-host interactions, analyzing and interpreting microbiome sequencing data presents challenges primarily attributed to the statistical ...

    • 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 (Journal article; Peer reviewed, 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 high ...