DR. CHANG SIOW WEE
Institute of Biological Sciences
Faculty of Science
siowweeum.edu.myView CV | |
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Biography | |
Siow-Wee Chang is a senior lecturer in the Bioinformatics Programme at the Institute of Biological Sciences, Faculty of Science, Universiti Malaya, Malaysia. She received her Ph.D. in Computer Science with a focus on Artificial Intelligence (AI) from Universiti Malaya, Malaysia. To date, she has published more than 30 papers in respectable journals and conference proceedings both locally and internationally. Her current research areas encompass artificial intelligence (AI), bioinformatics, medical informatics, data science and human-computer interaction. Siow-Wee Chang’s research interests covered multi-disciplinary topics bridging life sciences and computer sciences, focusing on disease diagnosis and prognosis prediction using AI approaches. Her work particularly addresses cardiovascular diseases, osteoarthritis, Alzheimer’s disease and cancer studies. Additionally, she also involved in flora and fauna studies, for example plant species and plant disease identification and marine species identification. These studies integrate the knowledge of biology, image analysis, machine learning and deep learning. The aims of these studies are to discover interesting patterns from the biological/medical data and elucidate the relationships between these data. Moreover, Siow-Wee Chang is also actively engaged in research related to omics profiling analysis, biomarker discovery and drug discovery & repurposing. Her studies utilized multi-omics approach, gene expression analysis, spatial transcriptomics, and AI methods. The goals of these studies are to identify potential disease biomarkers and discover drugs that can enhance the therapeutic process. She is also a member of the Malaysian Society of Bioinformatics and Computational Biology (MaSBiC). |
Publication
Finance
Project Title | Progress | Status |
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1. A Machine Learning Framework for Drug Repurposing in Alzheimer's Disease 2. Biomaker Discovery in Coronary Artery Disease through Transcriptomic Analysis and Machine Learning Approach |
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A Machine Learning Integrated Framework For Investigating Potential Biomarkers In Alzheimer?s Disease |
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Big Data Analytics In Diagnosis And Prognosis Of Acute Myocardial Infarction (ami): A Machine Learning Based Approach |
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This information is generated from Research Grant Management System |
A multi-ethnic proteomic profiling analysis in Alzheimer's disease identifies the disparities in dysregulation of proteins and pathogenesis
Differential Expression Analysis of Blood MicroRNA in Identifying Potential Genes Relevant to Alzheimer's Disease Pathogenesis, Using an Integrated Bioinformatics and Machine Learning Approach
A biomarker discovery of acute myocardial infarction using feature selection and machine learning
An integrative bioinformatics approach in microRNA data analytics of Alzheimer’s disease
Virtual Assembly System Using an Ergonomics Co- Location Workstation
Interactive 3D Visualization for Tropical Plant Species
Development of an Augmented Reality-Based G-Code Generator in a Virtual CNC Milling Simulation
Design and Development of 6 DOF System for Virtual Bicycle Simulator
Augmented Reality Assisted Factory Layout Planning and Analysis for a Flexible Manufacturing Cell