CEBioMeds@usm.my +604-562 2888

Bioinformatics

Synopsis

This module is split into two parts consisting of lectures and practical sessions covering genomic, proteomic and transcriptomic analysis for bioinformatics data. In this module, the students will be introduced to the common bioinformatic tools, databases and languages used to study biological data. The students will have the opportunity to learn how to generate 1) potential solutions, 2) in-depth interpretations, and 3) predictions using biological data of a particular disease model. The module will be delivered as blended learning, where the theoretical components will be taught online as a core module, while the practical sessions will be delivered face-to-face as a separate module (elective module). Students are encouraged to attend both modules to fulfil the course learning outcomes. For the elective module, additional costs may apply. The certificate will be issued according to the enrolment plan.

Objective

The objectives of the module are to:

  1. Learn how to use bioinformatics tools and their significance in biological data analysis.
  2. Learn about useful bioinformatics databases in medical research
  3. Learn how to extract useful information from bioinformatics data

Learning Outcome

At the end of the module, the participants will be able to:

  1. Utilize common bioinformatics tools and understand their significance in biological data analysis.
  2. Capable of using critical thinking to look for biological information from bioinformatics databases
  3. Apply bioinformatics tools to analyse computational and experimental data
  4. Choose appropriate methods and tools to extract information from bioinformatics data


The topics will be covered in this module

- Bioinformatics Database for Medical Research

- Comparative Genomics

- Drug Repurposing in Drug Discovery

- Bioinformatics for Precision Medicine

- Interpreting Bioinformatics Data in Medical Research

- Analyzing Medical Bioinformatics Data using Galaxy

- Pathway Analysis for Interpreting High Throughput Data

- Basic BioPython for Biologist

USM

MYR 350per module


Non USM (Local)

MYR 450per module


Non USM (International)

USD 200per module




Open Soon

HAZRINA BINTI YUSOF HAMDANI

PENSYARAH UNIVERSITI DS51 B.Tech (Hons) Information Technology; M.Sc (Computer Science); Ph.D (Bioinformatics)
Expertise : Computational Biology and Bioinformatics

Hazrina's primary research interest is in computational biology & bioinformatics, where she applied her knowledge in computational and the development of algorithms to solve biological problems. Previously, she utilized graph theory in mathematics and computer science to solve structural 3-dimensional (3D) motif identification in ribonucleic acids (RNA) 3D structure. She managed to publish two web services that applied the graph theory to identify 3D motifs and patterns in ribonucleic acids (RNA) 3D structure: NASSAM (Nucleic Acids Search for Substructures and Motifs) and COGNAC (COnnection tables Graphs for Nucleic ACids). Hazrina's research interest is expanding by incorporating Machine Learning and Deep Learning algorithms for structural 3D motif identification, DNA aptamers development and sequential mutation prediction, such as in genomics of RNA viruses.

MOHAMMAD SYAMSUL REZA BIN HARUN

PENSYARAH UNIVERSITI DS51 B.Sc Biomedical Science (IIUM); M.Sc Vaccine Technology (UPM); Ph.D Veterinary Medicine and Science (University of Nottingham)
Expertise : Bioinformatics, Molecular biology, Virology, Protozoology

Dr Mohammad Syamsul Reza bin Harun is a senior lecturer and a researcher at the Department of Biomedical Science, Advanced Medical and Dental Institute (AMDI), Universiti Sains Malaysia (USM), Bertam Campus, Pulau Pinang, Malaysia. His main expertise is on parasitology and virology focusing on pathogen-host interaction looking into global changes in host cells following infection. He got a background on Biomedical Sciences (BSc - International Islamic University Malaysia, Malaysia), Vaccine Technology (MSc - Universiti Putra Malaysia, Malaysia) and Veterinary Medicine and Science (PhD - University of Nottingham, UK) from three different universities. He has taught undergraduate and postgraduate students in these three courses: Industrial Waste Management, Environmental Microbiology and Bioinformatics. He has three publications as the main author and another four as co-author, all in SCOPUS/WOS journals. Currently, he holds one international grant and one university grant and is co-supervising an MSc student at AMDI.

AHMAD NAQIB BIN SHUID

PENSYARAH UNIVERSITI DS51 B Sc (HONS), UNIVERSITI MALAYA (UM); M. Sc, UNIVERSITI PUTRA MALAYSIA (UPM); Ph.D, UNIVERSITY OF READING, UNITED KINGDOM
Expertise : BIOINFORMATICS, BIOMOLECULAR MODELLING AND DESIGN, MICROBIOLOGY, MOLECULAR AND STRUCTURAL BIOLOGY, MOLECULAR BIOTECHNOLOGY

I joined Advanced Medical and Dental Institute, University Science Malaysia (AMDI, USM) as a lecturer in 2019. Obtained my PhD in Bioinformatics from university of Reading, UK. My main research interest is on protein prediction and refinement.

DR. NURULISA BINTI ZULKIFLE

PENSYARAH UNIVERSITI DS51 B.Sc Hons (Biology); M.Sc (Medical Research); Ph.D (Cellular & Molecular Physiology)
Expertise : Protein-Protein Interaction

Dr. Nurulisa earned her B.Sc. (Hons) Biology and M.Sc. (Medical Research) degrees from Universiti Sains Malaysia in Penang. She then pursued her Ph.D. at the University of Liverpool's Institute of Translational Medicine, where she was trained in yeast two hybrid methods to elucidate the non-canonical interaction between E2-ubiquitin conjugating enzymes and deubiquitin proteins (DUBs). For this work, she also used Cytoscape, which is an open source bioinformatics software platform for visualising molecular interaction networks. Later in her professional career, she used her skills in molecular interactions for transcriptome analysis to identify differentially expressed genes with potential molecular marker properties. Her primary research interests are in evaluation of the selected DUBs as molecular therapeutic target for cancer, with a focus on two areas: 

1. Elucidating novel DUBs-interacting proteins and pathways. 

2. Effect of DUBs knock-up and knockdown on the global gene expression and pathway in liver cancer.