GENE EXPRESSION DATA ANALYSIS Syllabus
Course Learning ObjectivesUpon successfully completing this course, students will be able to define gene expression measurement technology, basic microarray informatics, array normalization and bias adjustment; assess survey methods for genome wide analysis
Introduces statistical concepts and tools necessary to analyze gene expression array data. Topics covered are basic data analysis, including background on gene expression measurement technology, basic microarray informatics, array normalization and bias adjustment, methods for computing gene expression indicators in oligonucleotide arrays, and methods for identifying genes that are differentially expressed across experiments. Also introduces survey methods for genome-wide analysis of expression patterns, including clustering, principal components, and binary classification algorithms such as discriminant analysis, recursive partitioning, and support vector machines.
JHSPH students and Summer Institute participants
Methods of Assessment
Grading Policy: class exercises
Grading Restrictions: Letter grade
Students must have a basic understanding of biostatistical principles, including regression.
Academic Ethics Code
The code, discussed in the Policy and Procedure Memorandum for Students, March 31, 2002, will be adhered to in this class:
Students enrolled in the Bloomberg School of Public Health of The Johns Hopkins University assume an obligation to conduct themselves in a manner appropriate to the University's mission as an institution of higher education. A student is obligated to refrain from acts which he or she knows, or under the circumstances has reason to know, impair the academic integrity of the University. Violations of academic integrity include, but are not limited to: cheating; plagiarism; knowingly furnishing false information to any agent of the University for inclusion in the academic record; violation of the rights and welfare of animal or human subjects in research; and misconduct as a member of either School or University committees or recognized groups or organizations.
Disability Support Services
If you are a student with a documented disability who requires an academic accommodation, please contact Betty H. Addison in the Office of Student Life Services: email@example.com, 410-955-3034, or 2017 E. Monument Street.