Page 54 - Handbook Bachelor Degree of Science Academic Session 20202021

Faculty of Science Handbook, Academic Session 2020/2021

Main References:
SIV 3010 DATA MINING AND MACHINE LEARNING 1. Roger Pressman and Bruce Maxim (2014). Software
th
Engineering: A Practitioner's Approach. 8 ed.
th
This course introduces basic conceptual elements of 2. Ian Sommerville (2013). Software Engineering. 9 ed.
machine learning and data mining including data 3. Per Runeson, Martin Host, Austen Rainer, Bjorn
preprocessing methods, classification techniques, Regnell (2012). Case Study Research in Software
supervised and unsupervised learning, clustering Engineering, Wiley.
techniques, evaluation models and applications of machine
learning and data mining in bioinformatics. Software tools
such as MATLAB or WEKA will be introduced and used in SIV 3014 GRAPHICS AND DATA VISUALIZATION IN
solving bioinformatics problems. BIOINFORMATICS
This course aims to introduce the concepts in computer
Assessment Methods: graphics as well as apply effective techniques in designing
Continuous Assessment: 40% and developing computer graphic application. It covers the
Final Examination: 60% introduction of the components in computer graphics
systems and also the languages and tools use for graphics
Medium of Instruction: programming such as Python, SVG and OpenGL. Various
English problems related to Bioinformatics are considered to be
solved using graphics programming language.
Main References:
1. Jiawei Han and Micheline Kamber (2012). Data Assessment Methods:
Mining: Concepts and Techniques. Morgan Kaufmann Continuous Assessment: 60%
Publishers. Final Examination: 40%
2. Ian H. Witten, Eibe Frank, Mark A. Hall (2011). Data
Mining: Practical Machine Learning Tools and Medium of Instruction:
Techniques. The Morgan Kaufmann Publishers. English
3. Pang-Ning Tan, Michael Steinbach, Vipin Kumar
(2012). Introduction to Data Mining. Addison-Wesley. Main References:
1. Oswald Campesato (2014). Fundamentals of SVG
Programming. Charles River Media
SIV 3012 COMPUTATIONAL INTELLIGENCE IN 2. Conrad Bessant, Darren Oakley, Ian Shadforth
nd
BIOINFORMATICS (2014). Building Bioinformatics Solutions. 2 edition.
Oxford University Press
This course introduces computational intelligent (CI) 3. Andreas D. Baxevanis, B. F. Francis Ouellette (2011).
nd
techniques including artificial neural network, fuzzy logic, 2 edition. Bioinformatics: A Practical Guide to the
genetic algorithm, support vector machine and others. Analysis of Genes and Proteins. Wiley.
Example of case studies which applied CI in biological
problems will be discussed. Software tools such as SIV 3015 HEALTH INFORMATICS
MATLAB will be used to develop and implement the CI
models. Student will learn new methods to retrieve, group, process
and manage the knowledge and the data in the field of
Assessment Methods: health and bio health science. Students also will be learning
Continuous Assessment: 40% about the clinical data & hospital record system (HIS), HL7,
Final Examination: 60% telemedicine, telesurgery, teleradiology, decision support
system and other related aspect.
Medium of Instruction:
English Assessment Methods:
Continuous Assessment: 60%
Main References: Final Examination: 40%
1. Andres P. Engelbrecht (2014). Computational
Intelligence: An Introduction. Wiley. Medium of Instruction:
2. Russ Eberhart and Yuhui Shi (2014). Computational English
Intelligence: Concepts to Implementations. Morgan
Kaufmann. Main References:
3. S. Sumathi, Surekha Paneerselvam (2010). 1. Julus J. Berman (2010). Methods in Medical
Computational Intelligence Paradigms: Theory and Informatics: Fundamentals of Healthcare
Applications using MATLAB. CRC Press. Programming in Perl, Python, and Ruby. Chapman
and Hall/CRC.
2. Edward H. Shortliffe, James J. Cimino (2013).
SIV 3013 SOFTWARE ENGINEERING IN Biomedical Informatics: Computer Applications in
BIOINFORMATICS Health Care and Biomedicine (Health Informatics) 4
th
ed. Springer.
The syllabus of this course includes basic concepts of
software engineering, requirements gathering, requirement 3. Ramona Nelson, Nancy Staggers (2013). Health
specification and analysis, implementing systems, coding Informatics: An Interprofessional Approach. Mosby.
style and writing manuals. SIV 3016 GENETIC RESOURCE INFORMATICS

Assessment Methods: This course will discuss about diversities and issues
Continuous Assessment: 60% regarding organisms’ genetics resources. It will also focus
Final Examination: 40% on the development and usage of databases related to
genetic resources in bioinformatics research.
Medium of Instruction:
English Assessment Methods:
Continuous Assessment: 60%
Final Examination: 40%

53