• HOME
• ABOUT US
  • Name Address
  • General Description
  • Governance
  • Academic Calendar
  • Degree Programmes
  • List of Programmes in English
  • General Admission and Registration Procedures
  • Credit Mobility and Recognition of Prior Learning
  • ECTS Credit Allocation
  • Academic Guidance
  • Contacts
• Degree Programmes
  • Third Cycle Programmes (Doctorate Degree)
  • Second Cycle Programmes (Master's Degree)
  • First Cycle Programmes (Bachelor's Degree)
  • Short Cycle Programmes (Associate's Degree)
• GENERAL INFORMATION FOR STUDENTS
  • Cost of Living
  • Accommodation
  • Meals
  • Medical Facilities
  • Facilities for Disabled Students
  • Insurance
  • Financial Supports
  • Student Affairs Office
  • Practical Information for International Students
  • Language Courses
  • Work Placement Possibilities
  • Sports, Social and Cultural Facilities
  • Student Associations and Clubs
  • About İzmir - Turkey
• INTERNATIONAL RELATIONS
  • International Relations Office
  • Registration Procedures
  • Agreements
  • Coordinators
  • Documents
  • List of Programmes in English
  • ECTS / DS Labels

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS MPT 6006 BIOINFORMATICS IN MOLECULAR PATHOLOGY ELECTIVE 2 0 0 6

Offered By

Molecular Pathology

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

Offered to

Molecular Pathology

Course Objective

The aim of this course is to elucidate on the methods and applications devoted to deciphering molecular and biological information embedded in the data generated through analyses of biological samples. With a broad perspective, course aims to introduce students to data analysis tools and their relevance to clinical applications.

Learning Outcomes of the Course Unit

1   Students will be able to understand the vetting, classification, grouping, analysis and reporting of data generated by various analysis techniques. 2   Students will be able to track the information in the data files generated in Next Generation Sequencing systems. 3   Students will be able to interpret results generated by molecular analysis software. 4   Student will be able to integrate information generated by bioinformatics analyses to clinical practice and improve patient care. 5   Students will be able to appreciate the ethical analysis and application of data mining software.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Basics of Bioinformatics 2 Bioinformatic Databases Genetic 3 Bioinformatic Databases Protein and Others 4 Pair-wise Sequence Databases 5 Genome Alignment 6 Phylogenic tree & Multiple sequence alignments 7 Protein Structure Alignments 8 Protein Secondary Structure Predictions 9 Molecular Simulations Structural Information 10 Molecular Simulations Functional Information 11 Protein Interactions 12 Analyzing the Big Data 13 Bioinformatics Applications in Clinic 14 Bioinformatics Application to Clinical Cases 15 Bioinformatics Application to Clinical Cases

Recomended or Required Reading

No single textbook is required for this course. Relevant publications on the topics will be provided to the students as the course proceeds.

Planned Learning Activities and Teaching Methods

: Theoretical lecture presentations and frequent project assignments enabling application of theoretical information.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 ASG ASSIGNMENT 2 PAR PARTICIPATION 3 FCG FINAL COURSE GRADE 4 FCG FINAL COURSE GRADE ODV * 0.30 + DKL * 0.20 + FN* 0.50 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) ODV * 0.30 + DKL * 0.20 + BUT* 0.50 *** 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

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Assist. Prof. Dr. Ayça Erşen Danyeli 009023324123416 ayca.ersen@gmail.com

Office Hours

Friday 13:00-14:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 15 2 30 Preparations before/after weekly lectures 15 3 45 Preparation for final exam 1 45 45 Preparing assignments 1 25 25 Final 1 5 5 TOTAL WORKLOAD (hours) 150

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 PO.9 PO.10 PO.11 LO.1 5 5 5 LO.2 5 5 5 LO.3 5 5 5 LO.4 5 5 5 LO.5 4 5 5 5 4