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Master of Bioinformatics

Bioinformatics is a new, exciting and challenging multidisciplinary field that combines mathematical, statistical, computer science and information technology methods to solve life science-based problems. Advances in experimental technologies have produced huge amounts of data. Therefore, managing and extracting useful information from these sources are important if we are to discover new knowledge to advance our understanding of the living world. In MBioinformatics degree programme, students will receive broad training in fundamental areas of bioinformatics, thus allowing them to perform independent research or contribute as a bioinformatics specialist in a research team. Master of Bioinformatics by coursework programme is designed to address the growing need for professionals with an educational background that blends biology with computer sciences and information technology. The combination of skills is needed in the Bioinformatics   industry as well as advanced life science-based industries such as biotechnology and biomedical research. The programme also prepares students for career advancement and further study at the PhD level.


Course Structure

Master of Bioinformatics

Session 2017/2018

(42 CREDITS)

1. Program Core Courses (23 CREDITS)

Course Code

Course Name

Credits

SQF7001

Research Methodology in Bioinformatics

3

SQF7003

Functional Bioinformatics

3

SQF7004

Application of Algorithms in Bioinformatics

3

SQF7005

Programming in Bioinformatics

3

SQF7006

Statistics in Bioinformatics

3

SQF7007

Application of Programming in Bioinformatics

3

SQF7008

Structural Bioinformatics

3

SQF7009

Entrepreneurship, Innovation and Emerging Technology

2

2. Program Elective Courses (9 CREDITS)

Course Code

Course Name

Credits

SQF7010

Systems Biology

3

SQF7011

Biomedical Informatics

3

SQF7012

Ecology Informatics

3

SQF7013

Database Systems

3

SQF7014

Computing

3

SQF7015

Human Computer Interaction

3

3. Research Project (10 CREDITS)

Course Code

Course Name

Credits

SOF7002

Bioinformatics Research Project

10


SQF7001 Research Methodology in Bioinformatics
Introduction to research methodology, research proposal, literature review, research design and methodology, research ethics, oral presentation techniques, project paper and writing research papers, collecting data and determining the validity of the data, data measurement techniques, data analysis and error, instrumentation.

Assessment Methods:
Continuous Assessment: 100%

Medium of Instruction:
English

Transferable Skills:
Skill for conducting research, writing research reports and oral presentations

SQF7002 Bioinformatics Research Project
Students must conduct research in the field of Bioinformatics under the supervision of a least one lecturer. This research in conducted at the University of Malaya or in an appropriate organizations outside the University of Malaya such as hospitals, company, government agencies, public or private research institutions that are related to the field of Bioinformatics. Students must write a Project Report (maximum 20,000 words, excluding tables, figures, notes and references) on the research project conducted.  Student are also required to resent their work and findings in a seminar.

Assessment Methods:
Continuous Assessment: 100%

Medium of Instruction:
English

Transferable Skills:
Research skills

SQF7003 Functional Bioinformatics
Topics include methods of large scale data analysis in order to find information on all genes and transcripts of an organism using bioinformatics tools. Specific topics include:

  1. Reference and de novo based assembly;
  2. Gene discovery (search and identify the molecular functions, biological processes, biological pathways, associated disorders, chromosomal location, publications, conserved domain given gene symbol or a DNA/amino acid sequence);
  3. Polymorphism discovery (to understand the different type of variation, to get all variants given a chromosomal position or a gene identifier, to verity if a variant is a novel or known, to identify the position of the variant in gene, codon and to identify relevant sequence variation and structural variation databases, to predict the damaging effect of the variant, to identify the allele frequency of the variant and to identify disorders related to the variant CNVs);
  4. Gene expression analysis (to explain what is a fold change and what is a log ratio, to calculate and identify up-regulated/down-regulated genes and to annotate gene information;
  5. NGS – Exome sequencing analysis (to understand the variant call file (VCF) format, to generate a VCF format file, to manipulate and filter the VCF file in terms of read depth, quality score, zygosity and to annotate the VCF file).

 Assessment Methods:
Continuous Assessment: 100%

Medium of Instruction:
English

Transferable Skills:Functional analysis of large datasets derived in most cases from emerging high-throughput genomic, transcriptomics and proteomic technologies.

SQF7004 Application of Algorithms in Bioinformatics
This course will focus on the application of algorithms to solve bioinformatics problems such as in pairwise and multiple sequence alignment, molecular sequence database search, scoring matrices, phylogenetic analysis and genome assembly. A specific discussion on hidden Markov Model application in gene prediction will also be conducted.

Assessment Methods:
Continuous Assessment: 100%

Medium of Instruction:
English

Transferable Skills:||
Computer programming language

SQF7005 Programming in Bioinformatics
This course aims to introduce programming techniques that can be applied in solving Bioinformatics problem.

 It covers the essential concepts in programming techniques such as procedural and object-oriented. Common Bioinformatics tasks such as sequence analysis, accessing and retrieving data from public databases, and interfacing with external tools such as Blast are considered to be solved using scripting languages.  Hands on introduction to programming for Bioinformatics using the scripting languages such as Perl and Python also will be introduced.

Assessment Methods:
Continuous Assessment: 100%

Medium of Instruction:
English

Transferable Skills:
Students able to write programme using programming language and build up problem solving skills

SQF7006 Statistics in Bioinformatics
This course focuses on the application of statistics to study large biological data sets, such as those in genetics and molecular bioinformatics studies. Provides an introduction to stochastic process theory probability theory and HMMS for bioinformatics data analysis.


Assessment Methods:
Continuous Assessment: 100%

Medium of Instruction:
English

Transferable Skills:
Statistical analysis using bioinformatics data

SQF7007 Application of Programming in Bioinformatics
This course aims to apply any appropriate programming techniques in the development of bioinformatics software.

It covers the essential concepts in software development specifically for Bioinformatics software.  It is include the approaches and issues related to laboratory information data / data management, database system design, implementation and integration. Several programming libraries / packages / APIs that are specially designed for Bioinformatics will be introduced.

Assessment Methods:
Continuous Assessment: 100%

Medium of Instruction:
English

Transferable Skills:-

SQF7008 Structural Bioinformatics
This course will focus on the 3D structure of protein. It will discuss the methods to determine protein 3D structure, motifs and domains in protein structure, classification based on protein structure, issues in protein folding and the structural influence in protein function. It will also discuss the molecular dynamics application in protein structure and QSAR based drug design.

Assessment Methods:
Continuous Assessment: 100%

Medium of Instruction:
English

Transferable Skills:
Structural visualization software

SQF7009 Entrepreneurship, Innovation and Emerging Technology
Concepts and basic knowledge of entrepreneurship. Successful entrepreneurs. Entrepreneurship lifecycle. Entrepreneurship strategy. Start-ups. Development of business plan. Innovation: Introduction, definition and dimensions. Intellectual property – Concepts, types and issues. Emerging technology in the field of Bioinformatics and related areas. Case studies.   

Assessment Methods:
Continuous Assessment: 100%

Medium of Instruction:
English

Transferable Skills:
Communication skills, creativity, innovation and critical thinking

SQF7010 Systems Biology
Biological systems, processes and regulatory networks in living cells. Computational models and modelling. Data integration. Standards in systems biology. Network structures, dynamics and function. Modelling of Biochemical systems. Model representations. Modelling tools. Model fitting. Stochastic systems and variability. Gene Expression Models. Metabolic Flux Models. Analysis of High-throughput Data. 

Assessment Methods:
Continuous Assessment: 100%

Medium of Instruction:
English

Transferable Skills:
Modelling of biological systems. High-throughput data analysis

SQF7011 Biomedical Informatics
Organization of information in biomedicine and healthcare, the effective management of this information using computational approaches, and the impact of such approaches on biomedical research, education, and patient care. Hands-on experience with existing resources and systems, including those used in biological, clinical, and public health contexts.  

Assessment Methods:
Continuous Assessment: 100%

Medium of Instruction:
English

Transferable Skills:-

SQF7012 Ecology Informatics
This course focuses on usage of bioinformatics method dealing with ecological dataset. The course will emphasis on development of ecological application using artificial neural networks (ANNs) techniques. The course will also emphasize on algorithms, methods, design, learning theories, network architecture and application of Matlab Neural Network toolbox.   

Assessment Methods:
Continuous Assessment: 100%

Medium of Instruction:
English

Transferable Skills:
Students are able to use matlab toolbox and software for design and development of ecological models

SQF7013 Database Systems
The syllabus of this course includes background of database systems, the relational model and languages, Relational algebra and relational calculus, database analysis and design, methodology and some selected database issues. An introduction to noSQL database is given toward the end of the course. Hands on practical sessions are held according to the topics given.   

Assessment Methods:
Continuous Assessment: 100%

Medium of Instruction:
English

Transferable Skills:
Effective communication, critical thinking and problem solving, teamwork, lifelong learning, professionalisms 

SQF7014 Computing
This course includes important and current topics in computer science that can be applied in Bioinformatics such as information systems, database systems, operating systems, worldwide web, programming, visual analytics, data science, big data analytics and cloud computing. The lectures are followed by hands-on practical on the topics presented.

Assessment Methods:
Continuous Assessment: 100%

Medium of Instruction:
English

Transferable Skills:
Effective communication, critical thinking and problem solving, teamwork, lifelong learning

SQF7015 Human Computer Interaction
This course enables students to learn practical principles and guidelines needed to develop high quality interface designs that users can understand, predict, and control. It covers theoretical foundations, design processes and usability testing. 

Assessment Methods:
Continuous Assessment: 100%

Medium of Instruction:
English

Transferable Skills:
Students are able to design user interface using suitable software

Language Requirement

For international students, candidates are required to have TOEFL results at least 550 or IELTS at least Band 5.5.

Entry Requirement

Applicants must have a Bachelor's Degree with Honors CGPA 3.0 and above or equivalent in the relevant field.

Applicants with a Bachelor's Degree of CGPA 2.7 to 2.99 may be considered if they meet at least one of the following criteria:

A. Having relevant work experience; or

B. Produce publications in related fields; or

C. is a recipient of a scholarship; or

D. is a graduate of the University of Malaya; or

E. is a government servant

Applicants with a Bachelor's Degree of CGPA 2.5 to 2.69 may be considered if they meet at least two of the criteria in (1) (A) to (E) above

Fees
Kindly refer at Fees Structure
Last Update: November 20, 2017

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