Michael Osier Headshot

Michael Osier

Associate Professor

Thomas H. Gosnell School of Life Sciences
College of Science

585-475-4392
Office Location
Office Mailing Address
08-1338

Michael Osier

Associate Professor

Thomas H. Gosnell School of Life Sciences
College of Science

Education

BS, University of Vermont; Ph.D., Yale University

Bio

For more information please visit the Osier Lab at RIT website.

585-475-4392

Personal Links
Areas of Expertise

Currently Teaching

BIOL-135
3 Credits
Computer programming in the life sciences is used for modeling and data analysis across all fields. In this course, students will learn the fundamentals of computer programming and apply it to solve real problems in the life sciences. Breaking down problems, common syntax, and thoughtful decisions on proper use of data structures will be emphasized.
BIOL-235
3 Credits
Computer programming in the life sciences is used for modeling and data analysis across all fields. In this course, students will learn more advanced techniques to solve life sciences modeling problems efficiently using parallelization and distributed computing. Common methods and thoughtful decisions on proper use of tools will be emphasized.
BIOL-295
1 - 4 Credits
This course is a faculty-directed student project or research involving laboratory work, computer modeling, or theoretical calculations that could be considered of an original nature. The level of study is appropriate for students in their first three years of study.
BIOL-298
1 - 4 Credits
This course is a faculty-directed tutorial of appropriate topics that are not part of the formal curriculum. The level of study is appropriate for student in their first three years of study.
BIOL-301
1 - 4 Credits
This course allows students to assist in a class or laboratory for which they have previously earned credit. The student will assist the instructor in the operation of the course. Assistance by the student may include fielding questions, helping in workshops, and assisting in review sessions. In the case of labs, students may also be asked to help with supervising safety practices, waste manifestation, and instrumentation.
BIOL-321
3 Credits
Introduction to the principles of inheritance; the study of genes and chromosomes at molecular, cellular, organismal, and population levels.
BIOL-495
1 - 4 Credits
This course is a faculty-directed student project or research involving laboratory or field work, computer modeling, or theoretical calculations that could be considered of an original nature. The level of study is appropriate for students in their final two years of study.
BIOL-498
1 - 4 Credits
This course is a faculty-directed tutorial of appropriate topics that are not part of the formal curriculum. The level of study is appropriate for student in their final two years of study.
BIOL-530
3 Credits
Bioinformatics Algorithms will focus on the types of analyses, tools, and databases that are available and commonly used in Bioinformatics. The labs will apply the lecture material in the analysis of real data through computer programming.
BIOL-550
3 Credits
Students will utilize commonly used bioinformatics tools to analyze a real High Throughput Sequencing data set starting with raw data, proceeding with quality control, either aligning to a reference genome or performing de novo assembly, assessing differential gene expression determination, and finally annotating their results. Weekly lab reports will be required, and a group manuscript is expected at the end of the semester.
BIOL-601
3 Credits
The identification of genetic causes of disease has been one of the major modern scientific breakthroughs. This course examines a range of inherited diseases, how causative genetic variations were or are being identified, and what this means for the treatment of the diseases. Scientific literature will be utilized, both current and historical.
BIOL-630
3 Credits
Bioinformatics Algorithms will focus on the types of analyses, tools, and databases that are available and commonly used in Bioinformatics. The labs will apply the lecture material in the analysis of real data through computer programming.
BIOL-650
3 Credits
Students will utilize commonly used bioinformatics tools to analyze a real High Throughput Sequencing data set starting with raw data, proceeding with quality control, either aligning to a reference genome or performing de novo assembly, assessing differential gene expression determination, and finally annotating their results. Weekly lab reports will be required, and a group manuscript is expected at the end of the semester.
BIOL-790
1 - 6 Credits
Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
BIOL-791
0 Credits
Continuation of Thesis
BIOL-798
1 - 4 Credits
This course is a faculty-directed, graduate level tutorial of appropriate topics that are not part of the formal curriculum.