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Course Description Course Name : Developing Bioinformatics Software In Pyhton Course Code : BT-508 Course Type : Optional Level of Course : Second Cycle Year of Study : 1 Course Semester : Spring (16 Weeks) ECTS : 6 Name of Lecturer(s) : Prof.Dr. ZEYNEL CEBECİ Learning Outcomes of the Course : Develops software for the statistical analysis of biological data Codes algorithms of local and global alignments on sequence database Creates statistical scatter graphs for biological data Develops database applications Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : This course aims to teach Pyhon programming language, and to develop applications for analyzing biological data. Course Contents : The Structure of Pyhton programs; Literals, variables and types; Expressions, operators; Typecasting; Functions; Conditionals, Loops and random numbers; Arrays; Memory management; Strings; Structures; Applications: searching and sorting; File input and output Language of Instruction : Turkish Work Place : Classrom, Computer laboratory   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Introduction to Python programming language and setting up the compilers to personal computer Downloading and installing Python compiler/interpreter Internet/Computer work 2 Data types and Operations Reading a textbook chapter on data types and operations Reading 3 Statements and Expressions Reading a textbook chapter on expressions and statements Reading 4 Functions Reading a textbook chapter on functions Reading 5 Modules Reading a textbook chapter on building modules Reading 6 Principles of Object Oriented Programming (OOP) and Classes Reading a textbook chapter on OOP Reading 7 Exceptions and Tools Reading a textbook chapter on bugs and debugging Reading 8 Midterm Exam Preparing for midterm exam Individual/Group Work 9 Intregrating modules in Python Reading a textbook chapter on integration of programs Reading 10 Introduction to graphics programming in Pyhton Reading a textbook chapter on graphics and programming Reading 11 Genetic Algorithms in Python 1 Reading a textbook chapter on algorithms on genetics analysis Reading 12 Genetic Algorithms in Python 2 Reading a textbook chapter on algorithms on genetics analysis Reading 13 Project work and presentation 1 Preparing for project presentations Internet/Computer work 14 Project work and presentation 2 Preparing for project presentations Internet/Computer work 15 Final exam preperation Preparing for final exam Individual/Group Work 16/17 Final Exam Preparing for final exam Individual/Group Work   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  M. Lutz & D. Ascher (2004). Learning Python. O´Reilly 2nd Edition. ISBN 0-596-00281-5. 591 s.  M. Lutz. (2001). Programming Python. O´Reilly, ISBN:0-596-00085-5. 1255 s. Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 60     Homeworks/Projects/Others 3 40 Total 100 Rate of Semester/Year Assessments to Success 40   Final Assessments 100 Rate of Final Assessments to Success 60 Total 100   Contribution of the Course to Key Learning Outcomes # Key Learning Outcome Contribution* 1 Evaluates and directs his level of learning in the field of knowledge and skills with his expert level critically. 0 2 Transfers current developments in the field of his work, supporting them with quantitative and qualitative data, systematically to the area outside of the field, written, orally and visually. 0 3 Follows national and international publications and attends social interactions and scientific studies in international level, communicates in at least in one foreign language in order to share studies on international base. 0 4 Uses advanced information and communication technologies along with the required level of their computer software. 5 5 Uses the knowledge in his field for problem solving and / or practical skills in interdisciplinary studies. 5 6 Improves common knowledge accumulation concerning the Biotechnology in the frame of basic theory and practices. 5 7 Is aware of scientific, ethical and social values and handles research process with this frame. 0 8 Handles theories, hypothesis, opinions in the field of Biotechnology with an objective sceptic, logical, analytical manner and evaluates them in critical point of view. 0 9 Gains comprehensive information about natural and applied sciences and its limits with modern techniques and methods applied. 0 10 Improves and increases the knowledge to an expert level in the field of biotechnology 2 11 Understands the interdisciplinary interaction associated with biotechnology. 3 12 Integrates and interprets the knowledge from different disciplines by his expertrise in biology and generate new information 3 13 Analizes the problems encountered in the field of research methods. 5 14 Carries out a study requiring expertise in the field independently. 5 15 Developes new strategic approaches and takes resposibility for analitical solutions for unpredictable complicated problems encountered in applications related to biotechnology. 5 16 Demonstrates leadership in the required environment to solve problems associated with biotechnology. 2 * Contribution levels are between 0 (not) and 5 (maximum).   Student Workload - ECTS Works Number Time (Hour) Total Workload (Hour) Course Related Works     Class Time (Exam weeks are excluded) 14 4 56     Out of Class Study (Preliminary Work, Practice) 14 2 28 Assesment Related Works     Homeworks, Projects, Others 3 10 30     Mid-term Exams (Written, Oral, etc.) 1 14 14     Final Exam 1 14 14 Total Workload: 142 Total Workload / 25 (h): 5.68 ECTS Credit: 6