Understanding molecular variations of cattle genome by machine learning

在具备大规模组学数据的前提下，本博士项目将培养具有新时代将信息学与动物遗传与基因组研究相结合的创新思路的博士研究员。学生将整合遗传学和机器学习方法来识别牛基因组的分子变异，并评估分子变异与复杂表型（例如，健康，生产，效率，适应性）的关联。成功的候选人将有机会处理大规模的牛组学数据，包括全基因组序列，rna序列，英国牛种群的复杂表型。除了数据之外，学生还可以使用我们已经建立的方法，软件和高性能计算资源（例如，Nvidia DGX工作站，集群，Jupyter Notebook）来解决研究问题。将使用序列数据和机器/深度学习方法对数据进行联合分析，以确定牛基因组的分子变异（例如，eQTL）。鉴定出的具有功能意义的变异将与牛的复杂表型相关联，以研究功能变异与牛的健康、适应性、产量和效率之间的联系。博士项目是一个跨学科的研究项目，该项目由上海大学和爱丁堡大学通过交叉监督进行了强有力的合作。该学生将在定量遗传学、统计建模和机器学习方面获得上海科学大学和爱丁堡大学卓有成效的研究培训。学生还将在科学写作、项目管理技能和职业发展技能方面获得宝贵的培训。学生是EASTBIO培训计划的一部分，将接受强化的特定学科、核心生物科学和通用技能培训，并在学术界进行为期3个月的专业实习（PIPS）。学生将在4年内提交一篇博士论文。

With large-scale omics data available, this PhD project will train a PhD researcher with innovative ideas of integrating informatics into animal genetic and genomic research in the new era. The student will integrate genetics and machine learning methods to identify molecular variations of the cattle genome and assess the association of molecular variants with complex phenotypes (e.g., health, production, efficiency, fitness). The successful candidate will have the opportunity to work with large-scale cattle omics data including whole-genome sequence, RNA-sequence, complex phenotypes of UK cattle population. In addition to the data, the student will have access to methodology, software, and high-performance computational resources (e.g., Nvidia DGX Workstation, clusters, Jupyter Notebook) that have been well-established by us to address the research questions. The data will be jointly analyzed to identify molecular variations of cattle genome (e.g., eQTL) using sequence data and machine/deep learning methods. The identified variants with functional significance will be associated with cattle complex phenotypes to investigate the links between functional variants and cattle health, fitness, production, and efficiency. The PhD project offers interdisciplinary research and the project has strong collaborative efforts between SRUC and University of Edinburgh through cross-supervision. The student will obtain fruitful research training from both SRUC and University of Edinburgh on quantitative genetics, statistical modelling, and machine learning. The student will also obtain valuable training in scientific writing, project management skills, and career development skills. Students are part of the EASTBIO training programme and will undertake enhanced subject-specific, core bioscience and generic skills training and a 3-month professional internship (PIPS) outwith academia. The students are expected to submit a PhD thesis in 4 years.