Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions. - Anthony Culos; Amy Tsai; Natalie Stanley; Martin Becker 003; Mohammad Sajjad Ghaemi; David Mcilwain; Ramin Fallahzadeh; Athena Tanada; Huda Nassar; Camilo Espinosa; Maria Xenochristou; Edward Ganio; et al. (Nat. Mach. Intell., 2020)

Early prediction and longitudinal modeling of preeclampsia from multiomics. - Ivana Maric; Kévin Contrepois; Mira N. Moufarrej; Ina A. Stelzer; Dorien Feyaerts; Xiaoyuan Han; Andy Tang; Natalie Stanley; Ronald J. Wong; Gavin M. Traber; Mathew Ellenberger; Alan L. Chang; et al. (Patterns, 2022)

Large-scale correlation network construction for unraveling the coordination of complex biological systems. - Martin Becker 003; Huda Nassar; Camilo Espinosa; Ina A. Stelzer; Dorien Feyaerts; Eloïse Berson; Neda Hajiakhoond Bidoki; Alan L. Chang; Geetha Saarunya; Anthony Culos; Davide De Francesco; Ramin Fallahzadeh; et al. (Nat. Comput. Sci., 2023)

Deep representation learning identifies associations between physical activity and sleep patterns during pregnancy and prematurity. - Neal G. Ravindra; Camilo Espinosa; Eloïse Berson; Thanaphong Phongpreecha; Peinan Zhao; Martin Becker 003; Alan L. Chang; Sayane Shome; Ivana Maric; Davide De Francesco; Samson Mataraso; Geetha Saarunya; et al. (npj Digit. Medicine, 2023)