国际学生入学条件
Students with satisfactory undergraduate or graduate training in any biological science including emphasis on basic science courses will have suitable backgrounds for graduate studies in Dairy Science.
A bachelor's degree from a regionally accredited U.S. institution or a comparable degree from an international institution is required.
A minimum undergraduate grade-point average (GPA) of 3.00 on the equivalent of the last 60 semester hours (approximately two years of work) or a master's degree with a minimum cumulative GPA of 3.00 is required. Applicants from an international institution must demonstrate strong academic achievement comparable to a 3.00 for an undergraduate or master's degree.
Minimum TOEFL requirement- 92 internet (iBT), 580 paper-based test (PBT)
Minimum IELTS requirement- 7.0
Minimum IELTS Indicator requirement- 7.0
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IDP—雅思考试联合主办方
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雅思考试总分
7.0
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雅思考试指南
- 雅思总分:7
- 托福网考总分:92
- 托福笔试总分:580
- 其他语言考试:Minimum Duolingo English Test requirement- 125
CRICOS代码:
申请截止日期: 请与IDP顾问联系以获取详细信息。
课程简介
动物遗传学研究生课程是跨部门的,攻读乳科学理学硕士或博士学位的学生与动物科学的教职员工,研究生和博士后研究人员紧密合作。目前的主要研究重点是基因组选择,学生研究的主题包括:使用单核苷酸多态性(SNP)标记预测育种价值的方法,评估基因组预测与未来后代表现之间的关系,使用基因组预测未来表型数据和健康史信息,控制现代育种计划中的近亲繁殖,开发具有成本效益的基因分型策略,使用统计模型和机器学习算法来识别优良的育种种群,以及使用全基因组范围的发现和鉴定具有重大影响的特定基因关联研究。使用遗传和基因组信息改善诸如生育
The goal of animal breeding and genetics is to optimize the genetic improvement of economically and socially important traits in livestock and companion animals. We investigate the genetic and epigenetic mechanisms underlying phenotypic traits using gene mapping and functional genomics tools, and we develop statistical and computational methods to integrate multiple sources of information, including pedigree, genomic and phenotypic data. In addition, we develop tools for recording novel phenotypes such as feed efficiency and animal behavior and the use of genomic information to optimize management decisions. Some specific topics of interest include genomic selection, i.e. the prediction of genetic merit using single nucleotide polymorphism (SNP) markers, the relationship between genomic predictions and future progeny performance, the prediction of future phenotypes using both genetic and non-genetic data, the control of inbreeding in modern breeding programs, the development of cost-effective genotyping strategies, the use of statistical models and machine learning algorithms to identify superior breeding stock, and the discovery and characterization of specific genes with large effects using genome-wide association studies.
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