Singapore, Singapore
A fourth year undergraduate student who is keenly interested in the use of computational tools for all kinds of biomedical applications. As a Life Science student with a Bioinformatics minor and a range of experience in mutiomics analysis, machine learning, sequence database curation, and data analysis, I work at the interface of computational and experimental research. Having participated in numerous dance and rhythmic gymnastic competitions since young has allowed me to develop a resilient character, one that is receptive to feedback and constantly striving to improve.
Curated over 100,000 Influenza A sequences from the GISAID database to characterise conserved 3′ and 5′ UTR variation across strains, hosts, and pathogenicity in collaboration with Vignuzzi Lab. Performed multiple sequence alignment using MAFFT and downstream data processing and visualisation in R and MEGA12 to quantify UTR nucleotide distributions. Identified reproducible SNP patterns, allowing us to conduct experiments to test hypotheses on UTR-mediated phenotypic variation.
Final Year Project at A*STAR ID Labs. Explored mechanisms of conserved pathology in Chikungunya and O'nyong’nyong virus infections through multiomics analysis on virus-infected cells. Performed integrated transcriptomic and proteomic analysis including PCA clustering, differential expression, functional enrichment, pathway analysis and visualisation with various R packages. Identified novel gene hits and pathways for follow up validation and functional studies.
Demonstrated a novel enzymatic regulation of p53 inhibitor Mdm2 by Western blot, harbouring potential for modulating apoptosis and necroptosis in the TNF pathway. Confirmed induction of ferroptosis in mouse dermal fibroblasts by 3 inducer compounds through Western blot and live cell imaging by Incucyte.
Studied the Tilapia Lake Virus (TiLV) and Nervous Necrosis Virus (NNV) at A*STAR ID Labs. Utilised molecular cloning and DNA assembly to aid in the discovery of a fluorescent reporter TiLV design with potential for studying its pathogenicity in vivo. Identified a potentially susceptible cell line for generating fluorescent TiLV in vitro through mammalian cell culture, transfection, and fluorescence imaging. Optimised the RT-qPCR protocol for detection of NNV RNA resulting in production of more reliable results for further investigation.
A group project generating a machine learning algorithm for detecting Parkinsonism tremors in 6 marmoset model animals during a part-time attachment at A*STAR BII. Implemented and evaluated 4 feature extraction methods by ability to distinguish Parkinson-like tremors from video footage of marmosets. Presented methodology and results in a 5000-word written report, congress poster, and presentation for roughly 50 audience members.
Trained and tested 4 machine learning models, including 2 convolutional neural networks (CNNs), for differentiating malignant and benign brain tumours from MRI scans. Received top score in the cohort for a 2000-word written report and group presentation.