BİS514

4 ECTS - 1-2 Duration (T+A)- . Semester- 2 National Credit
Information About Course

Information
Goal, Content & Resources
Course Learning Outcomes
Relation with Program Learning Outcome
Week Plan
Student Workload - ECTS

Information

Code BİS514
Name
Semester . Semester
Duration (T+A) 1-2 (T-A) (17 Week)
ECTS 4 ECTS
National Credit 2 National Credit
Teaching Language Türkçe
Level Yüksek Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator


Course Goal

To provide an approach to the basic problems of bioinformatics such as genetic data analysis

Course Content

Computational techniques for mining large amounts of information generated by biological experiments will be introduced

Course Precondition

Basic knowledge of genetics and statistics

Resources

Shortliffe, E. H., Perreault, L. E., Wiederhold, G., & Fagan, L. M. (Eds.). (1990). Medical informatics: computer applications in health care. Addison-Wesley Longman Publishing Co., Inc..

Notes

Shortliffe, E. H., Perreault, L. E., Wiederhold, G., & Fagan, L. M. (Eds.). (1990). Medical informatics: computer applications in health care. Addison-Wesley Longman Publishing Co., Inc..


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Summarizes the data using descriptive methods
LO02 Students will have knowledge about statistical estimation
LO03 Models biological experimental data using probability distributions
LO04 Clusters, visualizes and summarizes multidimensional biological data


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Students comprehends the fundamentals of statistical theory related to the field of health ( probability and bayesian biostatistics). 1
PLO02 Bilgi - Kuramsal, Olgusal Students explain demographic terminologies and statistical methods in the field of health sciences.
PLO03 Beceriler - Bilişsel, Uygulamalı Students understand and use medical terminology. 3
PLO04 Beceriler - Bilişsel, Uygulamalı Students collect data from research studies, analyze, and make inferences 3
PLO05 Beceriler - Bilişsel, Uygulamalı Students knows the system of international classification of diseases, obtain and analyze hospital statistics.
PLO06 Beceriler - Bilişsel, Uygulamalı Students design scientific research studies in order to give response to the problem arising from health and clinical sciences 3
PLO07 Beceriler - Bilişsel, Uygulamalı Students select the appropriate statistical procedure for analysis , apply and make inferences. 2
PLO08 Beceriler - Bilişsel, Uygulamalı Students use the necessary statistical packages for analysis, if necessary write and develop software. 1
PLO09 Beceriler - Bilişsel, Uygulamalı Students follow the latest development in medical informatics and employ frequently used tools and methods. 4
PLO10 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Students design health survey, determine the sampling method and conduct the survey
PLO11 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Students select and use proper statistical procedure for diagnosis and in making inferences for the data in health and clinical medicine and provide consultance to clinicians in the field. 2
PLO12 Yetkinlikler - Öğrenme Yetkinliği Students develop the ability of critical thinking, make a conclusion with a critical approach to the evidence
PLO13 Yetkinlikler - Öğrenme Yetkinliği Students apply analytical procedure to frequently used survival data, multivariate procedure and regression techniques.
PLO14 Yetkinlikler - İletişim ve Sosyal Yetkinlik Students provide consulting services by using effective communication skills; take part in research teamworks; defend the ethical rules.
PLO15 Yetkinlikler - Alana Özgü Yetkinlik Students explain the fundamental terminologies in epidemiology, guide researchers conducting field survey and clinical studies, develop methodologies in determining disease risk factor and disease burden and advise for choosing proper diagnostic test.


Week Plan

Week Topic Preparation Methods
1 Introduction to medical informatics no need Öğretim Yöntemleri:
Anlatım, Tartışma
2 Genetic information Reading Öğretim Yöntemleri:
Anlatım, Tartışma
3 Genetic information2 Reading Öğretim Yöntemleri:
Anlatım, Tartışma
4 Protein structure prediction Reading Öğretim Yöntemleri:
Anlatım, Tartışma
5 RNA structure prediction Reading Öğretim Yöntemleri:
Anlatım, Tartışma
6 Phylogenetic tree Reading Öğretim Yöntemleri:
Anlatım, Tartışma
7 Microarraying Reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap
8 Mid-Term Exam - Ölçme Yöntemleri:
Yazılı Sınav, Ödev
9 Multiple regression Reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
10 Multiple regression2 Reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
11 Principal component analysis Reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
12 Principal component analysis2 Reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
13 Gibbs sampling Reading Öğretim Yöntemleri:
Anlatım
14 Metropolis-Hastings algorithm Reading Öğretim Yöntemleri:
Anlatım
15 Application no need Öğretim Yöntemleri:
Alıştırma ve Uygulama, Gösterip Yaptırma, Deney / Laboratuvar
16 Term Exams - Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams - 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 3 42
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 7 7
Final Exam 1 18 18
Total Workload (Hour) 109
Total Workload / 25 (h) 4,36
ECTS 4 ECTS