Information Package / Course Catalogue
Statistical Methods For Bioinformatics
Course Code: BİS530
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 8
Objectives of the Course

The objective of this course is to provide students with an understanding of statistical methods used in bioinformatics.

Course Content

Theory and applications for classical and advanced statistical data analysis methods used in bioinformatics. Micro Array Analysis, Cluster Analysis and Trees, Classifcation Methods, Analyzing Sequences, Markov Models.

Name of Lecturer(s)
Learning Outcomes
1.Understanding the importance of statistics in bioinformatics
2.To be able to comprehend the fundamental concepts of statistics in bioinformatics
3.To be able to apply statistical techniques to analyze microarray data and interpret the results generated
4.To be able to use advanced statistical tests commonly employed in bioinformatics
5.To be able to comprehend modern statistical methods and software to solve complex problems in bioinformatics
Recommended or Required Reading
Weekly Detailed Course Contents
Week 1 - Theoretical
Hypothesis tests
Week 2 - Theoretical
Hypothesis tests
Week 3 - Theoretical
Correlation Analysis
Week 4 - Theoretical
Regression Analysis
Week 5 - Theoretical
Logistic Regression Analysis
Week 6 - Theoretical
Cluster Analysis and Trees
Week 7 - Theoretical
Microarray analysis
Week 8 - Intermediate Exam
Midterm exam
Week 9 - Theoretical
Classification Analysis-1
Week 10 - Theoretical
Classification Analysis-2
Week 11 - Theoretical
Analyses of Squences-1
Week 12 - Theoretical
Analysis of Squences-2
Week 13 - Theoretical
Markov Models-1
Week 14 - Theoretical
Markov Models-2
Week 15 - Theoretical
Literature review and discussion
Week 16 - Final Exam
Final exam
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140342
Assignment210020
Seminar215234
Reading140114
Individual Work100220
Quiz142142
Midterm Examination110111
Final Examination115217
TOTAL WORKLOAD (hours)200
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
OÇ-1
OÇ-2
5
4
5
5
3
4
4
4
5
3
OÇ-3
5
5
4
5
4
4
4
4
4
5
OÇ-4
4
5
3
5
5
4
4
3
5
4
OÇ-5
5
4
4
4
4
3
3
3
4
4
Adnan Menderes University - Information Package / Course Catalogue