生物信息学理学硕士

生物信息学是一个快速发展的跨学科领域，将数学和计算机科学与生物学和/或医学相结合。随着生物技术的最新发展，生物学家经常被大型数据集所淹没，这些数据集需要以自动化方式进行存储和分析。生物信息学为理解复杂的生物系统提供了工具，从整个生态系统到特定的人类疾病，再到细胞和分子网络。毕业所需的总学时为36。核心课程包括：计算机科学两门课程（生物信息学，算法），统计学两门课程（概率论，应用统计学），生物学两门课程（细胞生物学，基因组学）和生物信息学研究研讨会课程（每学期修读）。剩余的学时可从孟菲斯大学的数学，计算机科
The program Bioinformatics MS is an interdisciplinary program at the intersection of the disciplines of Biology, Chemistry, Mathematics and Statistics, Computing and Informatics, and Engineering. The program is structured to provide students with the skills and knowledge to develop, evaluate, and deploy bioinformatics and computational biology applications. It is designed to prepare students for employment in the biotechnology sector, where the need for knowledgeable life scientists with quantitative and computational skills has exploded in the past decade.<br>A unique master's degree merging the biological sciences and computer technology, the M.S. in Bioinformatics is an interdisciplinary program at the intersection of the disciplines of Biology, Chemistry, Mathematics and Statistics, Computing and Informatics, and Engineering. It is expected that students entering the program will have completed an undergraduate major in either a life science or a quantitative discipline. The degree requires additional training and demonstrated competence in both life sciences and scientific programming. The M.S. program is structured to provide students with the skills and knowledge to develop, evaluate, and deploy bioinformatics and computational biology applications. The program is designed to prepare students for employment in the biotechnology sector, where the need for knowledgeable life scientists with quantitative and computational skills has exploded in the past decade.tudents seeking a degree in Bioinformatics want to be involved at the forefront of 21st century biological sciences. Students with undergraduate majors in either the life sciences or computing fields are encouraged to apply. At UNC Charlotte, we instill research, writing and critical thinking skills by teaching scholarly inquiry and research methods at a high level. Students will take courses from both computational and biological fields to develop their skills in the development, application and interpretation of bioinformatics. In addition, students complete an industry driven internship to apply their classroom skills in the workplace.