| PSYCHOLOGY | |||||
| 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 | Fall | 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 |
| Course Lecturer(s): |
Prof. Dr. SÜREYYA AKYÜZ Assist. Prof. SERKAN AYVAZ |
| 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) | Develop close interest in human mind and behavior, and attain critical thinking skills (in particular the ability to evaluate psychological theories using empirical evidence), as well as appreciating psychology as an evidence based science. | |
| 2) | Gain a biopsychosocial understanding of human behavior, namely, the biological, psychological, social determinants of behavior. | |
| 3) | Acquire theoretical and applied knowledge and learn about basic psychological concepts and perspectives | |
| 4) | Familiarize with methodology and data evaluation techniques by being aware of scientific research methods (i.e. correlational, experimental, longitudinal, case study). | |
| 5) | Employ ethical sensitivity while doing assessment, research or working with groups. | |
| 6) | Familiarize with the essential perspectives of psychology (cognitive, developmental, clinical, social, behavioral, and biological). | |
| 7) | Get the opportunity and skills to evaluate qualitative and quantitative data, write reports, and present them. | |
| 8) | Attain preliminary knowledge for psychological measurement and evaluation. | |
| 9) | To have a basic knowledge of other disciplines (e.g. sociology, history, political science, communication studies, philosophy, anthropology, literature, law, art, etc) that can contribute to psychology and to be able to make use of this knowledge in understanding and interpreting of psychological process. | 3 |