@article{f5b3d065e35442479acb814530e92daf,
title = "An integrative machine learning approach to discovering multi-level molecular mechanisms of obesity using data from monozygotic twin pairs",
keywords = "machine learning, big data, obesity, monozygotic twins, BODY-MASS INDEX, ARYL-HYDROCARBON RECEPTOR, SUBCUTANEOUS ADIPOSE-TISSUE, TIME PHYSICAL-ACTIVITY, GENE-EXPRESSION, DNA METHYLATION, INSULIN-RESISTANCE, WIDE ASSOCIATION, GUT MICROBIOME, DRUG RESPONSE, 3121 General medicine, internal medicine and other clinical medicine",
author = "Milla Kibble and Khan, {Suleiman A.} and Muhammad Ammad-ud-din and Sailalitha Bollepalli and Teemu Palviainen and Jaakko Kaprio and Pietil{\"a}inen, {Kirsi H.} and Miina Ollikainen",
year = "2020",
month = oct,
day = "21",
doi = "10.1098/rsos.200872",
language = "English",
volume = "7",
journal = "Royal Society Open Science",
issn = "2054-5703",
publisher = "ROYAL BELGIAN SOC EAR, NOSE, THROAT, HEAD & NECK SURGERY",
number = "10",
}