• Multiscale networks in multiple sclerosis 

      Kennedy, Keith E.; de Rosbo, Nicole Kerlero; Uccelli, Antonio; Cellerino, Maria; Ivaldi, Federico; Contini, Paola; De Palma, Raffaele; Harbo, Hanne-Cathrin Flinstad; Berge, Tone; Bos, Steffan Daniel; Høgestøl, Einar August; Brune-Ingebretsen, Synne; de Rodez Benavent, Sigrid Aune; Paul, Friedemann; Brandt, Alexander U.; Bäcker-Koduah, Priscilla; Behrens, Janina; Kuchling, Joseph; Asseyer, Susanna; Scheel, Michael; Chien, Claudia; Zimmermann, Hanna; Motamedi, Seyedamirhosein; Kauer-Bonin, Josef; Saez-Rodriguez, Julio; Rinas, Melanie; Alexopoulos, Leonidas G.; Andorra, Magi; Llufriu, Sara; Saiz, Albert; Blanco, Yolanda; Martinez-Heras, Eloy; Solana, Elisabeth; Pulido-Valdeolivas, Irene; Martinez-Lapiscina, Elena H.; Garcia-Ojalvo, Jordi; Villoslada, Pablo (Peer reviewed; Journal article, 2024)
      Complex diseases such as Multiple Sclerosis (MS) cover a wide range of biological scales, from genes and proteins to cells and tissues, up to the full organism. In fact, any phenotype for an organism is dictated by the ...
    • Predicting disease severity in multiple sclerosis using multimodal data and machine learning 

      Andorra, Magi; Freire, Ana; Zubizarreta, Irati; de Rosbo, Nicole Kerlero; Bos, Steffan Daniel; Rinas, Melanie; Høgestøl, Einar August; de Rodez Benavent, Sigrid Aune; Berge, Tone; Brune, Synne; Ivaldi, Federico; Cellerino, Maria; Pardini, Matteo; Vila, Gemma; Pulido-Valdeolivas, Irene; Martinez-Lapiscina, Elena H.; Llufriu, Sara; Saiz, Albert; Blanco, Yolanda; Martinez-Heras, Eloy; Solana, Elisabeth; Bäcker-Koduah, Priscilla; Behrens, Janina; Kuchling, Joseph; Asseyer, Susanna; Scheel, Michael; Chien, Claudia; Zimmermann, Hanna; Motamedi, Seyedamirhosein; Kauer-Bonin, Josef; Brandt, Alex; Saez-Rodriguez, Julio; Alexopoulos, Leonidas G.; Paul, Friedemann; Harbo, Hanne-Cathrin Flinstad; Shams, Hengameh; Oksenberg, Jorge; Uccelli, Antonio; Baeza-Yates, Ricardo; Villoslada, Pablo (Peer reviewed; Journal article, 2023)
      Background Multiple sclerosis patients would benefit from machine learning algorithms that integrates clinical, imaging and multimodal biomarkers to define the risk of disease activity. Methods We have analysed a prospective ...