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

Select Scholarship

Journal Paper
MV, Osier. "VitisPathways: Gene Pathway Analysis for V. Vinifera." Vitis 55. (2016): 129-133. Print.
Osier, Michael V. "A Board Game for Undergraduate Genetics Vocabulary and Concept Review: The Pathway Shuffle." Journal of Microbiology & Biology Education. (2014) Web.
Wu, X., et al. "Genes and Biochemical Pathways in Human Skeletal Muscle Affecting Resting Energy Expenditure and Fuel Partitioning." Journal of Applied Physiology 110. (2011): 746-755. Print.
Taylor, S.L., et al. "Urine Metabolomic Analysis Identifies Potential Biomarkers and Pathogenic Pathways in Kidney Cancer." OMICS: A Journal of Integrative Biology 15. (2011): 293-303. Print.
Invited Keynote/Presentation
Osier, Michael. "Curriculum Reflections Spawned by Semester Conversion." Undergraduate Bioinformatics Education Conference. St. Vincent College. Latrobe, PA. 30 May 2013. Keynote Speech.
Osier, Michael. "CNVs in Autism and Schizophrenia? Hype or Hope?" TIGR. University of Rochester. Rochester, NY. 20 Nov. 2013. Guest Lecture.
Published Article
Taylor S.L., S. Ganti, N.O. Bukanov, A. Chapman, O. Fiehn, M. Osier, K. Kim, and R.H. Weiss. “A metabolomics approach using juvenile cystic mice to identify urinary biomarkers and altered pathways in polycystic kidneydisease.” American Journal of Physiology Renal Physiology, 298 (2010):F909-F922. Print.

Currently Teaching

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-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-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-798
1 - 4 Credits
This course is a faculty-directed, graduate level tutorial of appropriate topics that are not part of the formal curriculum.
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-791
0 Credits
Continuation of Thesis
BIOL-389
1 - 3 Credits
This is an advanced course on a topic that is not part of the formal curriculum. This course is structured as an ordinary course and has specific prerequisites, contact hours, and examination procedures. The level of study is appropriate for students in their final two years of study.
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-790
1 - 6 Credits
Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
BIOL-321
3 Credits
Introduction to the principles of inheritance; the study of genes and chromosomes at molecular, cellular, organismal, and population levels.
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-671
3 Credits
Students will learn to create and maintain efficient relational databases for use in modeling and analysis in the sciences. Topics will include an introduction to relational algebra, SQL, and advanced relational designs.
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-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-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.