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As the research field of genomics and bioinformatics is very interdisciplinary and fast-moving, students from different background may need to strengthen different areas of knowledge. We are in the process of forming a Biostatistics PhD degree with emphasis in "Statistical Genetics and Genomics" (in effort with Dr. Eleanor Feingold, Dr. Daniel Weeks and Dr. Yan Lin). The course listing and curriculum will be better restructured in the near future. The "Joint CMU-Pitt PhD Program in Computational Biology" provides another degree program for solid computational biology training.
Before any formal curriculum can be formed in the Department of Biostatistics. Below is a list of courses I require for students in my group. Please note this is not the general requirement of Biostatistics PhD program but a requirement in our bioinformatics group to better train our students.
(1) BIOST 2058 Scientific Communication Skills (2 credits): This course trains students with their oral, visual and written communication skills. The skills will benefit your thesis development and your entire career. Our students should take this course as early as possible.
(2) For students with no or little biological background, they are required to take one of the following courses:
Molecular Biology (e.g. Pitt BIOSC 1940 or CMU 03-742) or
Advanced Genetics (CMU 03-730). These bio courses can count towards Biostatistics PhD degree requirement of courses outside the department.
(3) Students are required to take the following two courses offered by myself: BIOST2055 Introductory high-throughput genomic data analysis I: data mining and applications, and BIOST 2078 Introductory high-throughput genomic data analysis II: theories and algorithms. These two courses count towards the eight elective courses in the Biostatistics PhD requirement.
(4) Courses listed in this item can be counted towards the eight elective courses in the Biostatistics PhD requirement (count up to three).
Students are required to take one of the following courses: CMU 10-701 - Machine Learning; HUGEN 2080 : Statistical Genetics; HUGEN 2070 : Bioinformatics for Human Genetics
Students are encouraged to take at least one of the following advanced genetics, computational biology or machine learning courses.
BIOINF 2051 Foundations of Bioinformatics.
CMU 10-702 - Statistical Machine Learning
CMU 10-708 - Probabilistic Graphical Models
MSCBIO/CMPBIO 2070; CMU 02-710 Computational Genomics
CMU 02-715 - Advanced Topics in Computational Genomics
CMU 02-711 - Computational Molecular Biology and Genomics
Pitt MSCBIO 2020 - Bioinformatics of Gene Regulation
Other relevant courses include HuGen 2022 Population Genetics and HuGen 2029 'Introduction to Gene Mapping.
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