This two-volume work provides an overview on various state of the art experimental and statistical methods, modeling approaches and software tools that are available to generate, integrate and analyze multi-omics datasets in order to detect biomarkers, genetic markers and potential causal genes for improved animal production and health. The book will contain online resources where additional data and programs can be accessed. Some chapters also come with computer programming codes and example datasets to provide readers hands-on (computer) exercises. This second volume deals with integrated modeling and analyses of multi-omics datasets from theoretical and computational approaches and presents their applications in animal production and health as well as veterinary medicine to improve diagnosis, prevention and treatment of animal diseases. This book is suitable for both students and teachers in animal sciences and veterinary medicine as well as to researchers in this discipline.