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Code ENS 210
Term 201701
Title Computational Biology
Faculty Faculty of Engineering and Natural Sciences
Subject Engineering Sciences(ENS)
SU Credit 3
ECTS Credit 6.00 / 6.00 ECTS (for students admitted in the 2013-14 Academic Year or following years)
Instructor(s) Deniz Sezer dsezer@sabanciuniv.edu,
Detailed Syllabus
Language of Instruction English
Level of Course Undergraduate
Type of Course Click here to view.
Prerequisites
(only for SU students)
MATH101 CS201
Mode of Delivery Formal lecture,On-line task/distance,Recitation
Planned Learning Activities Interactive,Learner centered,Discussion based learning,Project based learning,Guided discovery
Content

1. Basic Concepts of Molecular Biology; Life, Proteins, Nucleic acids. 2. The Mechanisms of Molecular Genetics; Genes and the Genetic Code, Transcription, Translation and Protein Synthesis, junk DNA and Reading frames,Chromosomes 3. How the Genome is Studied; Maps and Sequences, Specific Techniques 4. The Human Genome Project 5. Molecular Biology Databases on the Web 6. Strings, Graphs and Algorithms 7. Sequence Alignment Algorithms; Global, Semiglobal, and Local Alignment 8. Multiple Sequence Alignment; Star alignment, Tree alignment 9. Database Search; PAM, BLOSSUM matrices, BLAST, FASTA 10. Quantitative and Probabilistic Pattern Matching 11. Protein Ligand Docking 12. Bio-ethics Also part of the "core course" pools for the BIO and CS degree program.

Objective

To supply the students with the foundations in Computational Biology.

Learning Outcome

To have basic knowledge of molecular biology genetics and biochemistry
To learn PERL and at to be able write PERL programs for basic computational biology problems.
To gain basic knowledge of the sequence alignment, database search , clustering, and profile algorithms in computational biology.
To learn ways to model biological problems and analyticla methodsfor solving problems in biology and medicine.
To learn to design an implement an algorithm and analyze the results of their algorithm that they developed as a team.

Programme Outcomes
 
Common Outcomes For All Programs
1 Understand the world, their country, their society, as well as themselves and have awareness of ethical problems, social rights, values and responsibility to the self and to others. 1
2 Understand different disciplines from natural and social sciences to mathematics and art, and develop interdisciplinary approaches in thinking and practice. 4
3 Think critically, follow innovations and developments in science and technology, demonstrate personal and organizational entrepreneurship and engage in life-long learning in various subjects. 5
4 Communicate effectively in Turkish and English by oral, written, graphical and technological means. 4
5 Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team; and have the skills to work effectively in multi-disciplinary teams. 4
1 Possess sufficient knowledge of mathematics, science and program-specific engineering topics; use theoretical and applied knowledge of these areas in complex engineering problems.
2 Identify, define, formulate and solve complex engineering problems; choose and apply suitable analysis and modeling methods for this purpose.
3 Develop, choose and use modern techniques and tools that are needed for analysis and solution of complex problems faced in engineering applications; possess knowledge of standards used in engineering applications; use information technologies effectively.
4 Ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling specified needs; apply modern design techniques for this purpose.
5 Design and conduct experiments, collect data, analyze and interpret the results to investigate complex engineering problems or program-specific research areas.
6 Knowledge of business practices such as project management, risk management and change management; awareness on innovation; knowledge of sustainable development.
7 Knowledge of impact of engineering solutions in a global, economic, environmental, health and societal context; knowledge of contemporary issues; awareness on legal outcomes of engineering solutions; understanding of professional and ethical responsibility.
1 Design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs and to solve a computational problem.
2 Demonstrate knowledge of discrete mathematics and data structures.
3 Demonstrate knowledge of probability and statistics, including applications appropriate to computer science and engineering.
1 Comprehend key concepts in biology and physiology, with emphasis on molecular genetics, biochemistry and molecular and cell biology as well as advanced mathematics and statistics.
2 Develop conceptual background for interfacing of biology with engineering for a professional awareness of contemporary biological research questions and the experimental and theoretical methods used to address them.
1 Applying fundamental and advanced knowledge of natural sciences as well as engineering principles to develop and design new materials and establish the relation between internal structure and physical properties using experimental, computational and theoretical tools.
2 Merging the existing knowledge on physical properties, design limits and fabrication methods in materials selection for a particular application or to resolve material performance related problems.
3 Predicting and understanding the behavior of a material under use in a specific environment knowing the internal structure or vice versa.
1 Formulate and analyze problems in complex manufacturing and service systems by comprehending and applying the basic tools of industrial engineering such as modeling and optimization, stochastics, statistics.
2 Design and develop appropriate analytical solution strategies for problems in integrated production and service systems involving human capital, materials, information, equipment, and energy.
3 Implement solution strategies on a computer platform for decision-support purposes by employing effective computational and experimental tools.
1 Use mathematics (including derivative and integral calculations, probability and statistics), basic sciences, computer and programming, and electronics engineering knowledge to design and analyze complex electronic circuits, instruments, software and electronics systems with hardware/software.
2 Analyze and design communication networks and systems, signal processing algorithms or software using advanced knowledge on differential equations, linear algebra, complex variables and discrete mathematics.
Assessment Methods and Criteria
  Percentage (%)
Final 40
Midterm 40
Group Project 20
Recommended or Required Reading
Readings

Setubal and Meidianis, Boston, Introduction to Computational Molecular Biology, PWS Publishing Company, Boston