BT507 Statistical Analysis of Microarray Data

6 ECTS - 3-0 Duration (T+A)- . Semester- 3 National Credit

Information

Code BT507
Name Statistical Analysis of Microarray Data
Term 2024-2025 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
1


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

No prerequisites

Resources

Brazma, A., Causton, H. C., & Quackenbush, J. (2003). Microarray Gene Expressions Data Analysis: A Beginner's Guide. Blackwell Pub.. Cebeci, Z. (2020). Data Preprocessing in Data Science with R. Nobel Akademik Yayıncılık, ISBN: 9786254060755

Notes

Lei, G. (2008). Tutorial: analysing Microarray data using BioConductor. URL http://www.mas.ncl.ac.uk/~ngl9/topics/inotes/TutorialMicroarrayAnalysis.pdf


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.
LO04 Interprets the results of microarray experiments.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Based on the undergraduate level qualifications, develops and deepens the knowledge in the same or different field at the level of expertise and analyzes and interprets them using statistical methods.
PLO02 Beceriler - Bilişsel, Uygulamalı To identifiy the interdisciplinary interaction of the field and to solve use of the methods. 1
PLO03 Beceriler - Bilişsel, Uygulamalı Interpret the knowledge gained in the field by integrating the information from different disciplines and creates new information 3
PLO04 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Develops new strategic approaches for solving complex problems that are encountered in applications related to the field. 1
PLO05 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.
PLO06 Yetkinlikler - İletişim ve Sosyal Yetkinlik To solve the problems encountered in the field and cominicate by using research methods. 4
PLO07 Yetkinlikler - Alana Özgü Yetkinlik To gain the ability to develop and deepen the knowledge in the field of biotechnology 5
PLO08 Yetkinlikler - Alana Özgü Yetkinlik Establishes functional interaction by using strategic decision-making processes in solving the problems encountered in the field.
PLO09 Yetkinlikler - Öğrenme Yetkinliği Knows the ethical rules to be considered while obtaining biotechnological products.
PLO10 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.


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. Öğretim Yöntemleri:
Alıştırma ve Uygulama, Anlatım
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. Öğretim Yöntemleri:
Alıştırma ve Uygulama, Anlatım
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. Öğretim Yöntemleri:
Alıştırma ve Uygulama, Anlatım
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. Öğretim Yöntemleri:
Alıştırma ve Uygulama, Anlatım
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. Öğretim Yöntemleri:
Alıştırma ve Uygulama, Anlatım
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. Öğretim Yöntemleri:
Alıştırma ve Uygulama, Anlatım
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. Öğretim Yöntemleri:
Gösterip Yaptırma, Anlatım
8 Mid-Term Exam Preparation for the exam Ölçme Yöntemleri:
Ödev, Sözlü Sınav
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. Öğretim Yöntemleri:
Alıştırma ve Uygulama, Gösterip Yaptırma, Anlatım
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. Öğretim Yöntemleri:
Alıştırma ve Uygulama, Gösterip Yaptırma, Anlatım
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. Öğretim Yöntemleri:
Alıştırma ve Uygulama, Gösterip Yaptırma, Anlatım
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. Öğretim Yöntemleri:
Alıştırma ve Uygulama, Gösterip Yaptırma, Anlatım
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. Öğretim Yöntemleri:
Alıştırma ve Uygulama, Anlatım
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. Öğretim Yöntemleri:
Alıştırma ve Uygulama, Anlatım
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. Öğretim Yöntemleri:
Alıştırma ve Uygulama, Anlatım
16 Term Exams Preparation for the exam Ölçme Yöntemleri:
Ödev
17 Term Exams Preparation for the exam Ölçme Yöntemleri:
Ödev


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

Update Time: 14.05.2024 04:49