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Information
| Unit | INSTITUTE OF NATURAL AND APPLIED SCIENCES |
| BIOTECHNOLOGY (MASTER) (WITH THESIS) (INTERDISCIPLINARY) | |
| Code | BT507 |
| Name | Statistical Analysis of Microarray Data |
| Term | 2018-2019 Academic Year |
| Term | Fall |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. ZEYNEL CEBECİ |
| Course Instructor |
The current term course schedule has not been prepared yet.
|
Course Goal / Objective
This course aims to teach the topics on handling, processing, and statistical analysis of microarray data.
Course Content
This course includes the topics on handling, processing, and statistical analysis of microarray data.
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Learns the basic concepts and terminology related with microarrays. |
| LO02 | Learns the microarray technologies. |
| LO03 | Analyze and interpret the microarray data. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Based on undergraduate level qualifications, they develop their knowledge at the level of expertise in the same or a different field. | |
| PLO02 | Bilgi - Kuramsal, Olgusal | Knows the ethical rules to be considered while obtaining biotechnological products. | |
| PLO03 | Beceriler - Bilişsel, Uygulamalı | To identifiy the interdisciplinary interaction of the field and to solve use of the methods. | 1 |
| PLO04 | Beceriler - Bilişsel, Uygulamalı | Interpret the knowledge gained in the field by integrating the information from different disciplines and creates new information | 3 |
| PLO05 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Develops new strategic approaches for solving complex problems that are encountered in applications related to the field. | |
| PLO06 | Yetkinlikler - Öğrenme Yetkinliği | To teach the social, scientific, cultural and ethical values during the collection, interpretation, implementation and announcement of the data related to the field. | |
| PLO07 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | To solve the problems encountered in the field and cominicate by using research methods. | 4 |
| PLO08 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Establishes functional interaction by using strategic decision-making processes in solving the problems encountered in the field. | |
| PLO09 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | He / she defends his / her original opinions in discussing the subjects in his / her field and establishes an effective communication showing his / her competence in the field. | |
| PLO10 | Yetkinlikler - Alana Özgü Yetkinlik | To gain the ability to develop and deepen the knowledge in the field of biotechnology | 5 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to microarray data analysis | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | |
| 2 | Types of microarrays | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | |
| 3 | Pre-processing microarray data | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | |
| 4 | Normalization of microarray data. | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | |
| 5 | Visualization of microarray data. | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | |
| 6 | Reading and writing microarray data files. | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | |
| 7 | Data cleaning for missing values/outliers | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | |
| 8 | Mid-Term Exam | Preparation for the exam | |
| 9 | Introduction to microarray analysis with R | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | |
| 10 | Search for the R packages in Bioconductor | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | |
| 11 | Microarray analysis with marray | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | |
| 12 | Microarray analysis with limma | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | |
| 13 | Linear models for selecting differentially expressed genes | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | |
| 14 | Multiple testing in large-scale gene expression experiments | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | |
| 15 | Searching for patterns in genes or samples | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | |
| 16 | Term Exams | Preparation for the exam | |
| 17 | Term Exams | Preparation for the exam |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||