Hierarchy is widely observed in biological systems. In this thesis, evidence from nature is presented to show that protein interactions have became increasingly modular as evolution has proceeded over the last four billion years. The evolution of animal body plan development is considered. Results show the genes that determine the phylum and superphylum characters evolve slowly, while those genes that determine classes, families, and speciation evolve more rapidly. This result furnishes support to the hypothesis that the hierarchical structure of developmental regulatory networks provides an organizing structure that guides the evolution of aspects of the body plan. Next, the world trade network is treated as an evolving system. The theory of modularity predicts that the trade network is more sensitive to recessionary shocks and recovers more slowly from them now than it did 40 years ago, due to structural changes in the world trade network induced by globalization. Economic data show that recession-induced change to the world trade network leads to an increased hierarchical structure of the global trade network for a few years after the recession. In the study of influenza virus evolution, an approach for early detection of new dominant strains is presented. This method is shown to be able to identify a cluster around an incipient dominant strain before it becomes dominant. Recently, CRISPR has been suggested to provide adaptive immune response to bacteria. A population dynamics model is proposed that explains the biological observation that the leader-proximal end of CRISPR is more diversified and the leader-distal end of CRISPR is less diversifed. Finally, the creation of diversity of antibody repertoire is investigated. It is commonly believed that a heavy chain is generated by randomly combining V, D and J gene segments. However, using high throughput sequence data in this study, the naive VDJ repertoire is shown to be strongly correlated between individuals, which suggest VDJ recombination involves regulated mechanisms.

High-throughput technologies in biological sciences have led to an exponential growth in the amount of data generated over the past several years. This data explosion is forcing scientists to search for innovative computational designs to reduce the time-scale of biological system simulations, and enable rapid study of larger and more complex biological systems. In the field of immunobiology, one such simulation is known as DNA recombination. It is a critical process for investigating the correlation between disease and immune system responses, and discovering the immunological changes that occur during aging through T-cell repertoire analysis. In this project we design and develop a massively parallel method tailored for Graphics Processing Unit (GPU) processors by identifying novel ways of restructuring the flow of the repertoire analysis. The DNA recombination process is the central mechanism for generating diversity among antigen receptors such as T-cell receptors (TCRs). This diversity is crucial for the development of the adaptive immune system. However, modeling of all the α β TCR sequences is encumbered by the enormity of the potential repertoire, which has been predicted to exceed 10¹⁵ sequences. Prior modeling efforts have, therefore, been limited to extrapolations based on the analysis of minor subsets of the overall TCR β repertoire. In this study, we map the recombination process completely onto the GPU hardware architecture using the CUDA programming environment to circumvent prior limitations. For the first time, a model of the mouse TCRβ is presented to an extent which enabled the evaluation of the Convergent Recombination Hypothesis (CRH) comprehensively at a peta-scale level on a single GPU. Understanding the recombination process will allow scientists to better determine the likelihood of transplant rejections, immune system responses to foreign antigens and cancers, and plan treatments based on the genetic makeup of a given patient.

The process of generating the vast diversity of immunoglobulin receptors and secreted antibodies begins with the recombination of the joining (JH), diversity (DH) and variable (VH) genes in the immunoglobulin heavy chain locus. The ability to produce antibodies is restricted to the B cell lineage and is tightly regulated, starting with the temporal separation of the recombination process, in which DH-JH precedes VH-DHJH recombination. Successful recombination of both heavy and light chain loci results in the expression of an antigen receptor on the cell surface. Subsequent selection stages remove non‑functional and autoreactivity receptors from the final pool of antigen responding B cells that ultimately give rise to antibody secreting plasma cells. Understanding the complexity of the recombination processes and the diversity of the resulting antibody repertoire has been a major focus of academic and industrial research alike. Therapeutic monoclonal antibodies have seen many successful applications within the clinic and they constitute a billion-dollar industry. However, limitations therein have resulted in the emergence of antibody engineering approaches and the use of natural sources of alternative heavy chain only antibodies (HCAbs/nanobodies). The biotechnology company Crescendo Biologics has taken the highly desired characteristics of HCAbs a step further with the creation of a mouse platform capable of producing fully humanized HCAbs. The Crescendo platform presents a unique opportunity to expand our understanding of how mouse B cell development functions by exploiting the features of heavy chain only antibody production. Furthermore, the platform enables the expansion of our limited knowledge of the epigenetic mechanisms involved in the recombination of the human immunoglobulin heavy chain locus. Using flow cytometry, with dimensionality reduction analysis approaches, I investigated B cell development in the context of HCAbs. These studies revealed a previously uncharacterised developmentally intermediate B cell population. Due to ethical and availability limitations to studies of human bone marrow, the primary pre-selection human B cell repertoire has not been studied in detail. The isolation of several B cell developmental stages and the use of our novel DNA-based high-throughput unbiased repertoire quantification technique, VDJ-seq, allowed me to study recombination of the human IGH locus sequence and observe HCAb repertoire selection within the mouse environment. The adaptation of next generation sequencing techniques to antigen receptor repertoire quantification has provided an unprecedented insight into repertoire diversity and the alterations it undergoes during infection or ageing. Our VDJ-seq assay is unique in its ability to interrogate DNA recombinants. To expand its capabilities, I investigated several limitations of the technique, including mispriming and PCR/sequencing errors, and implemented experimental and bioinformatics solutions to overcome them, which included the creation of a comprehensive analysis workflow. Finally, I have developed and applied a novel network visualisation method for genome-wide promoter interaction data generated by promoter capture Hi-C. The availability of high quality human pluripotent stem cell datasets allowed me to utilise the new techniques to further our understanding of the dynamics of genome organisation during early human embryonic development. This visualisation approach will be directly applicable to understanding B cell development.