Name: Expression data analysis

Course Unit Code: (BTK4260)

Credits: 4 op / 2 ov

Objectives: The goal of this course is to introduce statistical concepts and tools to analyze expression data. The expression data will be analyzed using R-language.

Announcement:

The real lectures will start from lecture 4, or 5 , please check the video lectures 1，2，3 or 4 by yourself.

Content:

	Lectures	Labs
1	Introduction to the microarray technology video A,B	Introduction to R
2	Introduction to data analysis with R--- (B) video A,B	Introduction to Bioconductor
3	Primary (or “low-level”) analysis of data--- (B) video A,B (MDA.zip)	Noramlization: TwoColorArray (A) AffyMatrix(B)
4	Dimension reduction, clustering & visualization--- (B)	Lymphoma data analysis
5	Promoter identification & microarray annotation ---- (B)	Clustering & visualization
6	Integrated analyses: BioOntologies & Reverse Engineering--- (B)	Annotate and geneplotter Packages
	More labs could be found here, contact me with email (bairong.shen(at)uta.fi ) for more inforamtion

Modes of Study: Lectures (approx.20h) && ( Practical project || Exam || Article reviews); &&: AND; ||: or

Evaluation: 1~5

Previous Studies: Bioinformatics in Functional Genomics (BIOI4210)
Literature: eBook (http://www.csc.fi/csc/julkaisut/oppaat/arraybook_overview)

Person in charge: Assistant Professor Bairong Shen