Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions

Isabel Moreno-Indias, Leo Lahti, Miroslava Nedyalkova, Ilze Elbere, Gennady Roshchupkin, Muhamed Adilovic, Onder Aydemir, Burcu Bakir-Gungor, Enrique Carrillo-de Santa Pau, Domenica D’Elia, Mahesh S. Desai, Laurent Falquet, Aycan Gundogdu, Karel Hron, Thomas Klammsteiner, Marta B. Lopes, Laura Judith Marcos-Zambrano, Cláudia Marques, Michael Mason, Patrick MayLejla Pašić, Gianvito Pio, Sándor Pongor, Vasilis J. Promponas, Piotr Przymus, Julio Saez-Rodriguez, Alexia Sampri, Rajesh Shigdel, Blaz Stres, Ramona Suharoschi, Jaak Truu, Ciprian-Octavian Truică, Baiba Vilne, Dimitrios Vlachakis, Ercument Yilmaz, Georg Zeller, Aldert L. Zomer, David Gómez-Cabrero, Marcus J. Claesson

Research output: Contribution to journal › Article › Academic › peer-review

Fingerprint

Dive into the research topics of 'Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions'. Together they form a unique fingerprint.

Keyphrases

Immunology and Microbiology