|Instructor(s)||Prathap Siddavaatam [Coordinator]|
Office Hours: Friday 5-7 PM
|Calendar Description||Discusses the theory and practice of molecular database searching and sequence alignment in genetic engineering. Covers databases and Internet access, sequence homology searching, and multiple alignment and sequence motif analysis, and protein structure and function.|
|Prerequisites||BME 501 and BME 532 and MTH 410|
|Learning Objectives (Indicators)|
At the end of this course, the successful student will be able to:
NOTE:Numbers in parentheses refer to the graduate attributes required by the Canadian Engineering Accreditation Board (CEAB).
3.0 hours of lecture per week for 13 weeks
Note: In order for a student to pass a course with "Theory and Laboratory" components, in addition to earning a minimum overall course mark of 50%, the student must pass the Laboratory and Theory portions separately by achieving a minimum of 50% in the combined Laboratory components and 50% in the combined Theory components. Please refer to the "Course Evaluation" section for details on the Theory and Laboratory components.
|Examinations||Midterm exam in Week 8, 2.0 hours, closed book (covers Weeks 1-6 of lecture, |
assignment and laboratory material).
Final exam, during exam period, 3.0 hours, closed book (covers all the course
Exams will be done in a computer lab, partly on computer and partly on paper.
|Other Evaluation Information||Labs: Weekly, excluding the first week.|
Participation: Based on in-class exercises and in-class presentations of recent advances in biotechnology.
Research Project: Review and presentation of a scientific paper.
The research project combines two separate components: a written component
and an oral presentation component. The objective of this project is to study a
specific topic in bioinformatics literature and to become familiar with the research community and history of bioinformatics. You must select a publication
that presents either a specialized bioinformatics algorithm or its application.
A 12 minute presentation and a two page technical report will be used to
evaluate your project, as well as the technical merit and the skill with which the
student communicates his or her message.
Papers in (peer-reviewed) journals and conference proceedings are the main
resources for this project. The last Lab/Tutorial sessions will be dedicated
to the presentation of student projects.
Exploring Bioinformatics Chapters 1 2 D. Mount: Chapter 12
Introduction to Bioinformatics and Computational Genomics:
Exploring Bioinformatics: Chapter 8
Exploring Bioinformatics: Chapters 3 5 D Mount: Chapter 3 4
Exploring Bioinformatics: Chapters 4 5 D. Mount: Chapter 5
Multiple sequence alignment:
Exploring Bioinformatics: Chapters 9 D. Mount: Chapter 7
Exploring Bioinformatics: Chapters 10 D. Mount: Chapter 7
Exploring Bioinformatics: Chapter 11 D. Mount: Chapter 10 (pp 417-434)
Exploring Bioinformatics: Chapter 11 D. Mount: Chapter 10 (pp 435-467)
Protein Homology modeling:
Exploring Bioinformatics: Chapter 12 D. Mount: Chapter 8
Nucleic Acid Structure Prediction
D. Mount: Chapter 13
Data Mining and Machine Learning:
LAB 1: Exploring bioinformatics database on the internet
Students will be familiarized with key features of the bioinformatics databases.
LAB 2: Python tutorial
Students will familiarize themselves with this scripting language and use it to write simple bioinformatics applications.
LAB 3: Sequencing DNA
Gaining experience with DNA sequencing data and software that analyzes it. Example: the human gut metagenome in NCBI trace archives.
LAB 4: Dynamic programming algorithm Pairwise Sequence Alignment
Students will implement the dynamic programming algorithm and gain a better understanding of pairwise sequence alignment.
LAB 5: Assembly of DNA sequence data
Writing a simulator to generate synthetic DNA sequencing data (fragments)
LAB 6: Data Mining
Students practice with Weka Data Mining software
LAB 7: Multiple sequence alignment
Practice with online software (CLUSTAL) and with Hidden Markov Models on paper.
LAB 8: Gene annotation
Implementation of CpG approach to finding the promoter region.
LAB 9: RNA Secondary Structure
Using online software to predict RNA structure.
LAB 10: Classification of proteins
Students will experiment with support vector machines and attribute selection to classify protein according to structure (all alpha all beta or mixed).
LAB 11: Predicting protein secondary structure
Implementation and testing of Chou-Fasman alg.
Research project: Review and presentation of a scientific paper
Students will learn to present and research on papers from (peer-reviewed) journals and conference proceedings for communicating scientific information.
When possible, students are required to inform their instructors of any situation which arises during the semester which may have an adverse effect upon their academic performance, and must request any consideration and accommodation according to the relevant policies as far in advance as possible. Failure to do so may jeopardize any academic appeals.
Ryerson's Policy 60 (the Academic Integrity policy) applies to all students at the University. Forms of academic misconduct include plagiarism, cheating, supplying false information to the University, and other acts. The most common form of academic misconduct is plagiarism - a serious academic offence, with potentially severe penalties and other consequences. It is expected, therefore, that all examinations and work submitted for evaluation and course credit will be the product of each student's individual effort (or an authorized group of students). Submitting the same work for credit to more than one course, without instructor approval, can also be considered a form of plagiarism.
Suspicions of academic misconduct may be referred to the Academic Integrity Office (AIO). Students who are found to have committed academic misconduct will have a Disciplinary Notation (DN) placed on their academic record (not on their transcript) and will normally be assigned one or more of the following penalties:
The unauthorized use of intellectual property of others, including your professor, for distribution, sale, or profit is expressly prohibited, in accordance with Policy 60 (Sections 2.8 and 2.10). Intellectual property includes, but is not limited to:
For more detailed information on these issues, please refer to the Academic Integrity policy(https://www.ryerson.ca/senate/policies/pol60.pdf) and to the Academic Integrity Office website (https://www.ryerson.ca/academicintegrity/).