人类对自身和周围环境的探索推动着社会的进步。其中，集中多国力量，使用第一代测序技术完成的人类基因组计划，极大促进了现代生物医药和医疗健康科技的发展。在高质量人类基因组参考序列建立后，基因组学进入到个体的重测序阶段，即以参考基因组为标准，对不同个体的外显子甚至全基因组进行高通量测序，研究个体基因组上的各种类型的基因组变异、以及变异同各种疾病之间相关性。申请人从2008年开始接触第二代测序数据，并针对该技术特点设计开发了一系列算法软件。当前，申请人在人类结构基因组计划的国际项目合作框架下同英美德的科研人员一道研究如何综合使用第二代和第三代测序技术数据和家族性数据提高对大尺度和复杂型变异的计算灵敏度、准确度和精度，设计并编写出一个完备的计算基因组复杂变异的软件包，并运用该方法到千人基因组数据、肿瘤基因组数据和其它疾病基因组数据上，发现关于物种演化和迁移以及疾病相关的新知识，为精准医疗提供方法学。

The curiosity on mankind and environment drives the advances of human race. Among many of miraculous achievements, the human genome project was one of them, with resources from multiple nations and using the first generation sequence technology. This has revolutionized the way modern medicine and medical health as well as basic biological research. After the establishment of human reference genome, we have entered the phase of resequencing, which is characterized as sequencing more and more individuals and building a deep catalog of human variation to understand how human race evolve, migrate as well as how variations contribute to diseases. The applicant started to investigate novel algorithms for the next generation sequence data analysis in 2008 and has contributed to 1000 Genomes Project, The Cancer Genome Atlas, The International Cancer Genome Consortium and the Genome of the Netherlands. Currently the applicant is working together with human structural variation consortium to combine the second and the third generation sequencing data for a comprehensive, precise and high quality variation set from family sequence data of 3 trios. The applicant aims to apply the novel algorithms to the public population sequence data like 1000 Genomes project, disease sequencing projects like Cancer genomes and local diseases in China. With all these above, we will gain knowledge about how species evolve and migrate as well as genotype-phenotype interaction. This will provide technical support for precision medicine.