Page 64 - buku panduan 20192020

Faculty of Science Handbook, Session 2019/2020

SIV 3007 INSTRUMENTATION IN BIOLOGICAL JavaScript, PHP, CGI, Perl, and SQL. Besides that, the
SCIENCES basic concepts of WWW client-server communications
and the skills to use the above tool to create Web
This course is going to introduce basic techniques and applications will be also introduced. Various problems
skills in biological experiments and instrumentation. It will related to Bioinformatics such as query, search and
cover the basic biochemistry, genetics, molecular, physical retrieve information are considered to be solved using
biochemistry experimental techniques to answer biological internet programming languages.
questions.
Assessment Methods:
Assessment Methods: Continuous Assessment: 60%
Continuous Assessment: 100% Final Examination: 40%

Medium of Instruction: Medium of Instruction:
English English

Soft Skills: Soft Skills:
CT3, TS2 CS3, CT3, TS2

Main References: Main References:
1. M. H. Fulekar and B. Pandey (2013). 1. Scott Guelich, Shishir Gundavaram, Gunther
nd
Bioinstrumentation. K International Publishing House. Birznieks (2012). CGI Programming with Perl. 2 Ed.
2. S. Bejugam and V. R. Meka (2012). O’Reilly Media.
BioInstrumentation: Tremor Quantification and 2. Mitchell L Model (2013). Bioinformatics Programming
Parameter Extraction. LAP LAMBERT Academic Using Python. O’Reilly Media.
Publishing. 3. Ethan Cerami (2013). XML for Bioinformatics.
3. G. Karp (2013). Cell and Molecular Biology: Springer.
Concepts and Experiments. Wiley.

SIV 3010 DATA MINING AND MACHINE LEARNING
SIV 3008 INTRODUCTION TO GEOGRAPHIC
INFORMATION SYSTEMS This course introduces basic conceptual elements of
machine learning and data mining including data
This course provides an introduction to the theory and preprocessing methods, classification techniques,
practice of geographic information systems (GIS). This supervised and unsupervised learning, clustering
course will introduce some of the basic concepts of GIS, techniques, evaluation models and applications of
input of data, storage and management of data and machine learning and data mining in bioinformatics.
modelling output from GIS. Concepts such as how to Software tools such as MATLAB or WEKA will be
model the complex real world in a computer and the introduced and used in solving bioinformatics problems.
difference between data and geographic data are covered.
Lectures cover the basics of GIS, vector and raster data Assessment Methods:
models, geographic data analysis, visualisation Continuous Assessment: 40%
techniques and geographic overlay. The practical Final Examination: 60%
sessions build basic skills in GIS such as adding,
visualising, analysing and modelling data and creating Medium of Instruction:
effective map layouts. English

Assessment Methods: Soft Skills:
Continuous Assessment: 60% CS3, CT3, TS2
Final Examination: 40%
Main References:
Medium of Instruction: 1. Jiawei Han and Micheline Kamber (2012). Data
English Mining: Concepts and Techniques. Morgan
Kaufmann Publishers.
Soft Skills: 2. Ian H. Witten, Eibe Frank, Mark A. Hall (2011). Data
CT3, LL2 Mining: Practical Machine Learning Tools and
Techniques. The Morgan Kaufmann Publishers.
Main References: 3. Pang-Ning Tan, Michael Steinbach, Vipin Kumar
1. Ian Heywood ,Sarah Cornelius (2011). An (2012). Introduction to Data Mining. Addison-Wesley.
Introduction to Geographical Information Systems. 4
th
ed. Prentice Hall.
2. John R Jensen, Ryan R. Jensen (2013). Introductory SIV 3012 COMPUTATIONAL INTELLIGENCE IN
Geographic Information Systems. Pearson. BIOINFORMATICS
3. Keith C. Clarke (2011). Getting Started with
th
Geographic Information Systems, 5 ed. Prentice This course introduces computational intelligent (CI)
Hall. techniques including artificial neural network, fuzzy logic,
genetic algorithm, support vector machine and others.
Example of case studies which applied CI in biological
SIV 3009 INTERNET PROGRAMMING problems will be discussed. Software tools such as
MATLAB will be used to develop and implement the CI
This course aims to introduce the World Wide Web models.
(WWW), web software, connections and hardware,
introduction to internet programming and scripting, Assessment Methods:
website maintenance and Web applications. It covers an Continuous Assessment: 40%
introduction to internet programming and the languages. Final Examination: 60%
Topics include HTML, XHTML, DHTML, XML, CSS,

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