TRAINING GRANT IN COMPUTATIONAL GENOMICS

宾夕法尼亚大学旨在创建一个计算基因组学项目，扩展现有的计算生物学和生物信息学项目。目前，宾夕法尼亚大学的三所学校-艺术与科学，工程与应用科学和医学-已经加入创建一个全面的计划，该计划涵盖了本科生培训，导致计算/数学生物学的BS或BE，生物信息学硕士学位，博士学位。在计算生物学，并在计算生物学和生物信息学博士后培训。所有这些课程的合并招生人数超过20名学生，申请人数和质量持续快速增长。在计算基因组学的计划将建立在现有的计划，博士和博士后学员在计算生物学，并增加了一个独特的新的培训组成部分-结合博士后的经验和职业转换计划博士。学生在生物学导致硕士学位的科学和工程在计算机和信息科学。职业转换计划对功能基因组学尤其重要，因为它利用了大量熟练生物学家的人才库，这些生物学家对于理解生物系统的复杂性至关重要。宾大在基因组学的广泛领域有着不断扩大的影响力，从拟南芥的基因组序列到mRNA转录表达分析再到多态性分析。计算基因组学计划将补充基因组学的地方努力和基因组注释等领域的国家努力，让学生接触到一系列计算和实验基因组学的培训。

The University of Pennsylvania aims to create a program in Computational Genomics that extends existing Computation Biology and Bioinformatics programs. Currently, three schools at Penn-Arts and Sciences, Engineering and Applied Science, and Medicine- have joined to create a comprehensive program that spans undergraduate training leading to a BS or BE in Computational/Mathematical Biology, a Master's degree in Bioinformatics, a Ph.D. in Computational Biology, and Post-Doctoral training in Computational Biology and Bioinformatics. The combined enrollment in all of these programs numbers more than 20 students with a sustained rapid growth in the number and quality of applicants. The program in Computational Genomics will build on the existing programs for doctoral and post-doctoral trainees in Computational Biology, and add a unique new training component-a combined post-doctoral experience and career conversion program for Ph.D. students in biology leading to a Master's of Science and Engineering in Computer and Information Sciences. The career conversion program is especially important for functional genomics because it taps into a large talent pool of skilled biologists who will be essential for understanding the intricacies of biological systems. Penn has an expanding presence in broad areas of genomics from genomic sequence of Arbidopsis thaliana to mRNA transcription expression analysis to polymorphism analysis. The Computational Genomics Program will complement both local efforts in genomics and national efforts in areas such as genome annotation, giving students exposure to a range of training in both computational and experimental genomics.