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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS MBG 6121 DATA MINING TECHNIQUES ELECTIVE 3 0 0 12

Offered By

Molecular Biology and Genetics

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

ASSISTANT PROFESSOR GÖKHAN KARAKÜLAH

Offered to

Molecular Biology and Genetics

Course Objective

This course aims to provide students with concepts of data mining, data processing, and mining techniques in the context of genomics.

Learning Outcomes of the Course Unit

1   To know concepts of data mining 2   To use fundamental data mining techniques for analyzing high-throughput genomic data 3   To be able to choose appropriate data mining method for data analysis and to extract meaningful information from genomic data 4   To be aware of challenges in data mining 5   To interpret outputs of data mining algorithms in the context of genomics

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Basics of data mining and common techniques 2 Variable types and descriptive statistics 3 Similarity, dissimilarity and data visualization 4 Data preprocessing techniques (cleaning and integration) 5 Data preprocessing techniques (reduction, transformation and discretization) 6 Mining frequent patterns, associations and correlations 7 Basic concepts of classification and decision trees 8 MIDTERM 9 Bayes and rule-based classifications 10 Support vector machines and lazy learners 11 Cluster analysis and partitioning methods 12 Hierarchical clustering 13 Outlier detection and outlier analysis 14 Data mining trends and research frontiers 15 Assignment Presentations 16 Final exam

Recomended or Required Reading

1. Han, Jiawei, Micheline Kamber, and Jian Pei. Data mining: concepts and techniques. (3rd edition) Elsevier, 2011.

Planned Learning Activities and Teaching Methods

Theoretical lectures with PowerPoint presentation and assignment presentations by students

Assessment Methods

Successful / Unsuccessful *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

gokhan.karakulah@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 15 2 30 Tutorials 15 2 30 Preparations before/after weekly lectures 15 4 60 Preparation for midterm exam 1 15 15 Preparation for final exam 1 25 25 Preparing assignments 1 30 30 Preparing assignments 1 40 40 Preparing presentations 15 5 75 Final 1 2 2 Midterm 1 3 3 TOTAL WORKLOAD (hours) 310

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 LO.1 2 LO.2 2 LO.3 2 LO.4 2 LO.5 2