COURSE UNIT TITLE

: GENOMICS DATA ANALYSES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
BYL 5089 GENOMICS DATA ANALYSES ELECTIVE 2 2 0 5

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ERGIN ŞAHIN

Offered to

Ph.D. in Biology
Biology

Course Objective

The purpose of this course is to bring graduate students the ability to do bioinformatic and genome data analysis, to teach different methods of DNA and Protein sequence analysis, to promote interdisciplinary studies, to get used to different software programs to analyze DNA-Protein data, and carry out sample analysis of different kinds

Learning Outcomes of the Course Unit

1   1. Describe bioinformatics in general and the interdisciplinary science
2   2. Tell the history of the genome project, its rise and progress and also tell the benefits of the human genome project
3   3. Explain how to get DNA and Protein sequences with examples
4   4. Using ChromasLite software package for checking the DNA sequences, aligning sequences and preparing data files for analysis
5   5. Using Clustal X software package, align pairwise or multiple DNA and Protein sequences.
6   6. Using GenBank, can do BLAST , obtain DNA or Protein sequences from the databases and use them in the analysis.
7   7. Using different computer software, can analyze DNA or Protein sequences.
8   8. During manuscript preparation, can analyze the data and evaluate the results.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Molecular Biological terminology and bioinformatics: General Molecular Biological terminology and the introduction to bioinformatics
2 Genom projects and DNA sequencing analysis: The rise of the genome projects, Human Genome Project, DNA sequencing methodologies
3 DNA sequence databases: GenBank, DDJB, EMBL databases, downloading and uploading DNA sequences to databases
4 Protein sequence databases: Protein data, primary, secondary, tertiary structures, motifs and the databases that they can be found-SWISSPROT, PDB.
5 GenBank: General knowledge about the databases, reaching to database items and the programs to deposit to databases, for example depositing DNA sequences using SEQUIN
6 Opening and correcting Chromatogram files using ChromasLite: Opening DNA sequence chromatogram files. Checking the DNA sequences, Creating reverse complement and FASTA files
7 Aligning sequences with Clustal X: Pairwise or multiple sequence alignments of DNA or Protein sequences
8 BLAST (Basic Local Alignment Search Tool): Searching sequences in GenBank database and finding similar sequences
9 Protein 3-D structures: Visualisation of 3-D Protein structures with different softwares, for example, Ras Mol software and its usage
10 Constructing phylogenies: Finding the distance matrices using different data and constructing the genetic relationship
11 MEGA (Molecular Evolutionary Genetic Analysis): The usage of computer software packages for DNA and Protein sequences
12 Data analysis: data analysis using MEGA computer software
13 Evaluation of software results: Evaluating the results of DNA and Protein data
14 Studying scientific papers and sample analysis: Application of analysis methods in scientific articles and evaluating the results

Recomended or Required Reading

- Claverie, J.M., Notredame, C. 2007. Bioinformatics for DUmmies.2nd Edition. Wiley Publishing Inc. 436 p.
- Baxevanis, A.D., Oullette, B.F.F. 2001. Bioinformatics: A practical guide to the analysis of genes and proteins. 2nd Edition. Wiley-International. 470 p.
- Mount, D.W., 2005. Bioinformatics: Sequence and Genome Analysis. Cold Spring Harbor Laboratory Press.
- Deonier, R.C., Tavare, S., Waterman, M.S. 2006. Computational Genome Analysis: An Introduction. Springer Verlag.
- Tamura, K., Dudley, J., Nei, M., Kumar, S., 2007. MEGA 4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0.
- Swofford, D.L. 1998. PAUP, Phylogenetic analysis using parsimony, version 4.0b10 Sinaeur Associates, Sunderland, MA.

Planned Learning Activities and Teaching Methods

The course will consist of lectures, class discussions, and presentations.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 FIN FINAL EXAM
3 FCG FINAL COURSE GRADE MTE * 0.40 + FIN * 0.60
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + RST * 0.60


Further Notes About Assessment Methods

None

Assessment Criteria

mid-term and final exams

Language of Instruction

Turkish

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at http://web.deu.edu.tr/fen

Contact Details for the Lecturer(s)

e-mail: ergin.sahin@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 2 28
Tutorials 14 2 28
Preparations before/after weekly lectures 13 4 52
Preparation for final exam 1 10 10
Preparation for midterm exam 1 6 6
Final 1 3 3
Midterm 1 2 2
TOTAL WORKLOAD (hours) 129

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12
LO.155445
LO.244454
LO.354445
LO.444555
LO.544555
LO.645454
LO.755545
LO.855545