| INDUSTRIAL ENGINEERING | |||||
| Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 | ||
| Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
| MBG1002 | Introduction to Bioinformatics | Spring | 3 | 0 | 3 | 5 |
| This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
| Language of instruction: | English |
| Type of course: | Non-Departmental Elective |
| Course Level: | Bachelor’s Degree (First Cycle) |
| Mode of Delivery: | Face to face |
| Course Coordinator : | Assist. Prof. CEMALETTİN BEKPEN |
| Recommended Optional Program Components: | There is none. |
| Course Objectives: | Bioinformatics (computational molecular biology)involves applying computational methods for managing and analyzing information about the sequence, structure and function of biological molecules and systems. This introductory course will cover statistical and algorithmic concepts to address common,yetdifficultquestionsthatarisewhileanalyzingbiologicaldata.Biologicaldatacan be categorized based on the levels of information that exist in living cells: DNA, RNA, proteins, metabolites, and other small molecules. This course is organized into modules, each section focuses on a particular type of biological data, biological questions that are associated with these data, and the computational approaches to address these questions. The goals of this course are to provide an understanding of: 1_The types of biological data 2_The computational problems that arise while analyzing biological data 3_A set of algorithms that have important applications in computational biology, but which have key applications outside of biology as well. 4_Core set of widely used algorithms in computational biology |
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The students who have succeeded in this course; 1. Recognize the working in interdisciplinary teams of biologists, biochemists, medical researchers, geneticists, and computer engineers. 2. Perform sophisticated searches over enormous databases, and to interpret results. 3. Perform genomic comparisons, display genes and large genomic regions in Genome Browsers. 4. Recognize the basic bioinformatics problems and their solutions, including: fragment assembly, gene finding, protein folding and microarray studies. 5. Anayze the results in probabilistic terms using statistical significance. 6. Recognize the sequencing techniques, inherent computational problems, possible solutions. 7. Define Markov Model building and its usage for gene prediction. 8. Define computational methods for analysis of microarray data, and discuss the interpretations of gene expression from this data. 9. Discuss ethical, legal, and social issues associated with the Human Genome Project and its outcomes. |
| Bioinformatics is a rapidly growing field that integrates molecular biology, statistics, and computer science. This course is devoted to the mathematical models and computer algorithms of DNA and protein sequence analysis. In this course, the students will learn many of the popular tools for performing bioinformatics analysis and you will be introduced to the thinking that drives these algorithms. Various existing bioinformatics methods will be critically described and the strengths and limitations of each will be discussed. |
| Week | Subject | Related Preparation |
| 1) | Introduction to Bioinformatics | |
| 2) | Genomics data mining (Biological Databases) | |
| 3) | Sequencing (Methods and Sequencing technologies) | |
| 4) | Sequence Search | |
| 5) | Genomic Variation | |
| 6) | Sequence Alignment | |
| 7) | Molecular Phylogenetic | |
| 8) | Whole Genome Sequencing and Mapping | |
| 9) | Review for the midterm exam | |
| 10) | Downstream Analysis of Variant Detection (SNPs, SVs, CNVs) | |
| 11) | Omics Data Analysis (Transcriptomics, Proteomics) | |
| 12) | Omics Data Analysis (Epigenomics, Paleogenomics) | |
| 13) | Omics Data Analysis (Functional Genomics, Metagenomics) | |
| 14) | General Review |
| Course Notes / Textbooks: | Biyoinformatik ders notları haftalık olarak verilecektir. Course material will be supplied weekly. 1) Pevsner J. 2015. Bioinformatics and Functional Genomics, 3rd Ed. Wiley Blackwell. |
| References: | 1) Pevsner J., Bioinformatics and Functional Genomics, Wiley-Liss, 2009 2) Mount D.W., Bioinformatics: Sequence and Genome Analysis (2nd edition), Cold Spring Harbor Laboratory Press, 2004 3) Krane D.E., Raymer M.L., Fundamental Concepts of Bioinformatics, Benjamin Cummings, 2003 4) Setubal C., Meidanis J., Introduction to Computational Molecular Biology, PWS Publishing, 1997" |
| Semester Requirements | Number of Activities | Level of Contribution |
| Homework Assignments | 1 | % 20 |
| Midterms | 1 | % 30 |
| Final | 1 | % 50 |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 50 | |
| PERCENTAGE OF FINAL WORK | % 50 | |
| Total | % 100 | |
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | Build up a body of knowledge in mathematics, science and industrial engineering subjects; use theoretical and applied information in these areas to model and solve complex engineering problems. | |
| 2) | Identify, formulate, and solve complex engineering problems; select and apply proper analysis and modeling methods for this purpose. | |
| 3) | Design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; apply modern design methods for this purpose. The ability to apply modern design methods to meet this objective. | |
| 4) | Devise, select, and use modern techniques and tools needed for solving complex problems in industrial engineering practice; employ information technologies effectively. | |
| 5) | Design and conduct experiments, collect data, analyze and interpret results for investigating the complex problems specific to industrial engineering. | |
| 6) | Cooperate efficiently in intra-disciplinary and multi-disciplinary teams; and show self-reliance when working independently. | |
| 7) | Demonstrate effective communication skills in both oral and written English and Turkish. Writing and understanding reports, preparing design and production reports, making effective presentations, giving and receiving clear and understandable instructions. | |
| 8) | Recognize the need for lifelong learning; show ability to access information, to follow developments in science and technology, and to continuously educate him/herself. | 3 |
| 9) | Develop an awareness of professional and ethical responsibility, and behaving accordingly. Information about the standards used in engineering applications. | |
| 10) | Know business life practices such as project management, risk management, and change management; develop an awareness of entrepreneurship, innovation, and sustainable development. | 4 |
| 11) | Know contemporary issues and the global and societal effects of modern age engineering practices on health, environment, and safety; recognize the legal consequences of engineering solutions. | |
| 12) | Develop effective and efficient managerial skills. |