The key objectives of this thesis work are to decipher and prioritise observed variations among different phenotypes. With advancements in high throughput technology leading to a surge in biological data, it is imperative to analyse and interpret this information. Consequently, this thesis work examines epigenetic, genetic, transcriptomic and proteomic variations within different multifactorial diseases and this pivotal information is then annotated and associated to its corresponding phenotype. Childhood asthma and obesity are the two main phenotypic themes in this thesis. In the first section, Chapter 1 provides an introduction to various methodologies utilised in this thesis work. Subsequently, chapters 2, 3 and 4 in the second section, address finding causal variations in childhood asthma. Chapter 2 focuses on a genome wide association study (GWAS) performed on asthma exacerbation case cohort. This study reports a new susceptibility locus within the gene CDHR3 for exacerbation phenotype of childhood asthma. Chapter 3 of the thesis presents a pilot study, which aims at designing a candidate gene panel for childhood asthma to identify the causal variants from known asthma genes. Chapter 4 describes artificial neural network (ANN) based methodology of selecting genetic and clinical features with predictive power for childhood asthma. The goal of these studies is to understand the complex genetics of childhood asthma. The third part of this thesis (chapters 5 and 6) focuses on various mechanisms involved in adipose depots, which is a major tissue implicated in obesity. Chapter 5 sheds light on different mechanisms that result in the replacement of metabolism efficient brown fat with the storage-type white fat in large mammals (including human) especially within the first few months following birth. The project work discussed in chapter 6 is aimed towards understanding the various underlying differences in obesity responses in fat cells from different white adipose tissue depots under diet-induced and genetic obesity by decoding the global epigenetic modifications. The fourth section of this thesis work (chapter 7) comprises of two studies that are aimed towards genotype to phenotype mapping. The first section of chapter 7, details the usage of variations from the Danish pan-genome pilot project to comprehend the common phenotypes of the population and attempt to establish its kinship with European populations. Next, the second portion of this chapter describes a personalised genome study of an ancient genome which was conducted by calculating the genetic risk scores to unravel phenotypes. Appendix section (Chapter 8) comprises of an integrative functional analysis study of the changing proteome and phosphor-proteome in chemotherapy resistant breast cancer cell lines with high TIMP-1 gene expression. In summary, this thesis work demonstrates applications of various omic variations at different levels of complexity and their integration using systems biology based methodologies to associate them to multifactorial phenotypes. These studies help in revealing pivotal mechanistic details concerning the phenotypes, which can be further utilized in drug designing and disease management.