在过去的十年中，高通量数据集的爆炸性增长，涵盖了从DNA序列到RNA转录丰度，单细胞蛋白质谱，蛋白质变体和代谢产物谱等所有方面的信息。这些多维组学数据集很复杂，无法集成，可视化和分析那些不熟悉系统生物学和生物信息学的人。需要新一代的科学家来利用这些资源来提出和回答免疫学中的重要新问题。CSI计划将产生一类杂种科学家，以识别免疫学中的重要问题，并制定适当的综合计算/实验计划来解决这些问题。
The past decade has seen an explosion in the availability of high-throughput datasets spanning information on everything from DNA sequences to RNA transcript abundances, single-cell protein profiles, protein variants and metabolite profiles. These multi-dimensional omics datasets are complex to integrate, visualize and analyze for those not well versed in systems biology and bioinformatics. A new generation of scientists is needed to take advantage of these resources to ask and answer novel important questions in immunology. The CSI track will generate a class of hybrid scientists to identify important problems in immunology and to devise appropriate integrated computational/experimental plans for tackling them. Students in the CSI track will be able to- develop new computational tools that use multiple large-scale publicly available omics datasets to enhance the knowledge of immunology and immunobiology, integrate of new computational omics analysis techniques into existing, well-established genomic data analysis pipelines/frameworks to better understand immunology and enable researchers/clinicians to rapidly leverage omics advancements, develop new and innovative multi-omic simulation and / or visualization methods that make systems immunology accessible to research scientists with no programming experience, thus bridging the gap between computational data mining and human knowledge to extend insight.