Derrin Bright

MSc Precision Health and Medicine
National University of Singapore, Singapore

Bio: I've always been interested in how biology and technology can work together. My focus lies at that intersection, where I use computational tools and machine learning to explore biological data and understand how diseases function. Using my skills in bioinformatics, I want to help build that bridge between biology and artificial intelligence.

Currently, I am pursuing my Master of Science in Precision Health and Medicine at the National University of Singapore. I completed my Bachelor of Technology in Biotechnology at Vellore Institute of Technology, Vellore, before that. Recent work includes a first author paper on transcription factor binding sites across HPV types, analyzing transcriptomic data to uncover dysregulated pathways in autoimmune diseases, and using molecular docking to visualize how a potential drug compound binds to its target protein, identifying the key interactions that make the binding effective.

I have also worked with computational tools such as AlphaFold for protein structure prediction, GROMACS and AutoDock for molecular simulations, and data analytics platforms like KNIME, alongside machine learning frameworks such as TensorFlow and Keras. Outside of my academic work, I enjoy playing cricket and chess, as well as spending time outdoors.

Core Interests:

  •    Systems Biology
  •   Genomics and Transcriptomics
  •   Machine Learning in Bioinformatics

Education

National University of Singapore - Singapore

Master of Science (MSc)
Precision Health and Medicine, Department of Biochemistry, Yong Loo Lin School of Medicine
August 2026 - Present

Vellore Institute of Technology - Vellore, India

Bachelor of Technology (BTech)
Biotechnology, School of Bio Sciences and Technology (SBST)
Courses: Bioinformatics, Genomics and Proteomics, Molecular Biology, Cell Biology, Genetic Engineering, Biochemistry, Immunology, Biology, Probability and Statistics, Linear Algebra, Calculus
CGPA: 8.8/10
September 2022 - 2026

Publications

Comparative Analysis of Transcription Factor Binding Sites in the Long Control Region Across Human Papillomavirus Types | Viruses, 2026, 18(6):646 (MDPI)

D. Bright, J.I. Fuxman Bass*
*Corresponding author

Integrative transcriptomic analysis identifies predictive gene signatures across autoimmune diseases: implications for personalized therapeutic targeting | Under review at Journal of Autoimmunity (Elsevier)

M. Srinivasan, D. Bright, H. Dhandapani, S. Panda, P. Tayalia*
*Corresponding author

Comparative Analysis of HPV-Positive Cervical and Head and Neck Cancers Using WGCNA and Machine Learning Identifies Shared Biomarkers | Under review at Tumour Virus Research (Elsevier)

B. Kiruba, S.B. Niranjan †, D. Bright †, N. Patel, C.A. Biju, V. Sundararajan*, S.S. Lulu*
†Equal contribution
*Corresponding author

Research Experience

Nanyang Technological University (NTU) - Singapore

Project Intern
  • Developing a transcription factor activity inference pipeline on large-scale postmortem brain RNA-seq data to investigate gene regulatory dynamics across neurodegenerative disease progression.
  • Supervisor: Dr. Guillaume Thibault
    • Jan 2026 - June 2026

    Boston University - Massachusetts, USA

    Research Intern
  • Developed an automated bioinformatics pipeline for transcription factor motif analysis across 200+ HPV genomes, identifying differentially enriched TFs between high-risk and low-risk types
  • Integrated motif-based approaches with deep learning sequence models to assess regulatory activity and characterise binding site conservation across 1,000+ clinical isolates
  • Supervisor: Dr. Juan Fuxman Bass
    • Sep 2025 - April 2026

    University of Liverpool - Liverpool, UK

    Research Intern
  • Analyzed single-cell RNA-seq data from CLL and Richter’s Transformation patients, developing machine learning models (XGBoost, SVM, Random Forest) to differentiate disease states at the transcriptomic level.
  • Built genome-scale metabolic models (GEMs) for CLL and Richter’s Transformation cell types using the ftINIT algorithm, and identified differential metabolic reactions and enriched pathways between disease states and cell types.
  • Supervisor: Dr. Francesco Del Carratore
    • Sep 2025 - Aug 2026

    IIT Bombay - Mumbai, India

    Research Intern
  • Conducted differential expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA) to identify key gene modules associated with autoimmune disease progression, followed by Gene Set Enrichment Analysis (GSEA) and Protein-Protein Interaction (PPI) network construction using NetworkAnalyst to uncover dysregulated pathways and functional gene relationships.
  • Built and evaluated predictive models, including Logistic Regression, SVM, XGBoost, and Deep Neural Networks to classify disease vs. healthy states based on gene expression, enhancing biological interpretability through integrated network and machine learning approaches.
  • Supervisor: Dr. Prakriti Tayalia
    • May 2025 - Oct 2025

    Ashoka University - Delhi, India

    Research Intern
  • Analyzed 5 assembled E. coli genomes to investigate carbapenem and beta-lactam resistance by performing BLAST and RGI-CARD analysis to identify mutations, and correlating genotype-phenotype relationships through the AST report analysis.
  • Performed Multiple Sequence Alignment (MSA) of Penicillin-Binding Proteins (PBPs) from the five E. coli genomes against a reference wild-type sequence to detect conserved mutations, and conducted genomic analysis that led to the identification of a 12-base pair insertion in the PBP3 gene, contributing to antibiotic resistance mechanisms.
  • Automated genomic data processing by developing a custom script to systematically rename and organize FASTA files, creating a structured dataset necessary for phylogenetic analysis using the PhaME tool.
  • Supervisor: Dr. Shraddha Karve
    • Jan 2025 - Mar 2025

    NovaLinks - Vellore, India

    Biotech Team Lead - Intern
  • Led a project integrating miRNA analysis and histopathological imaging with machine learning to enhance lung cancer subtype classification and improve diagnostic precision.
  • Conducted research on miRNA biomarkers specific to lung cancer and provided biological insights to support the development of an accurate classification model for distinguishing adenocarcinoma from squamous cell carcinoma.
    • Biotech Intern
  • Analyzed urinary and serum biomarkers for the detection of Urinary Tract Infections (UTIs) and evaluated their diagnostic potential in asymptomatic conditions, including Chronic Kidney Disease (CKD), Non-Alcoholic Fatty Liver Disease (NAFLD), Non-Alcoholic Steatohepatitis (NASH), and Acute Kidney Injury (AKI).
  • Performed comparative analysis of optical sensor technologies (PMT vs CMOS) and finalized wavelength ranges and strip flushing techniques to enhance detection accuracy and device efficiency.
    • Dec 2024 - Mar 2025

    Teachnook - Bangalore, India

    Data Science Intern
  • Worked on multiple plant detection and defect detection tasks with the input image and plant specifications including the length and width of the sepals and petals.
  • Implemented multiple algorithms, including Random Forest, SVM, and Logical Regressor, to analyze the plant specifications and ResNet with multiple layers for analyzing the input images.
  • Gained proficiency in Python, NumPy, and Pandas, alongside essential data visualization techniques, and foundational concepts on machine learning and deep learning.
  • Supervisor: Dr. Meghana Gowda
    • Sep - Oct 2024

    Bversity - Bangalore, India

    Bioinformatics Intern
  • Explored drug design and discovery using bioinformatics, leveraging KNIME for molecular similarity searches to streamline chemical space exploration and compound prioritization.
  • Conducted protein structure predictions using AlphaFold, building a foundation in structure-based drug design.
  • Completed targeted projects, including antiviral and antibacterial drug screening and protein interaction prediction, enhancing my understanding of therapeutic targeting and molecular interactions in infectious diseases.
  • Supervisor: Dr. Anjana Yagnapriya
    • February 2024

    Alpha Bio Cell, VIT University - Vellore, India

    Vice Chairperson
  • Led several biotechnology and bioinformatics-related events, including hackathons, workshops, and quizzes, enhancing the club's engagement.
  • Mentored junior core members, ensuring effective collaboration and event planning across different stages.
  • Applied leadership, technical, and project management skills to drive various initiatives, significantly contributing to the club’s growth and impact.
  • Supervisor: Dr. Ramesh Pathy
    • Jan - Dec 2024

    Skillset


    ros airsim matlab sw fusion ansys
    pybullet c++ python c++ c++

    c++ c++ c++ c++

    Projects

    Identification of Conserved Functional Modules and Unique Hub Genes across Autoimmune Disorders

    Tools: GSEA, NetworkAnalyst, R Studio

    Conducting an integrative transcriptomic analysis across autoimmune diseases, combining results from Differential Expression, WGCNA, and GSEA to define a curated list of implicated genes. Constructing and analyzing Protein-Protein Interaction networks to identify the core genes and biological processes shared across these diseases, while also characterizing the molecular signatures unique to each condition.

    Comparative Transcriptomic Analysis of HPV-Associated Cancers Using Co-Expression Network Modeling

    Tools: DESEQ2, WGCNA, Cytoscape, ClusterProfiler, Seurat, Scikit-learn, Pandas, NumPy

    Conducted a comparative analysis of HPV-positive cervical and head and neck cancers using TCGA data. Performed DESeq2 and WGCNA to identify shared genes between both cancers. Applied machine learning models to filter features, identifying 16 HPV signature genes, and validated findings using single-cell RNA-seq analysis. Constructed PPI networks and performed functional enrichment analyses to identify shared molecular mechanisms underlying HPV-driven tumorigenesis.

    Multi-Modal Genomic Analysis of Beta-Lactam Resistance Mechanisms in Five Clinical E. coli Isolates

    Tools: Prokka, Biopython, ResFinder, CARD-RGI, BLAST

    Performed integrated whole-genome sequencing and bioinformatics analysis of clinical E. coli isolates to identify the genetic drivers of beta-lactam antibiotic resistance, including novel PBP3 mutations and β-lactamase genes. Conducted Multiple Sequence Alignment (MSA) of Penicillin-Binding Proteins (PBPs) from the five E. coli genomes against a reference wild-type sequence to detect conserved mutations, and conducted genomic analysis that led to the identification of a 12-base pair insertion in the PBP3 gene, contributing to antibiotic resistance mechanisms.

    Computational Identification of Antimalarial Leads through Fingerprint Similarity Analysis

    Tools: KNIME, RDKit, PubChem, Seaborn

    Screened a library of antimalarial molecules against a query (chloroquine drug) by generating molecular fingerprints and computing Tanimoto similarity coefficients using KNIME and RDKit nodes. Extracted molecular data from the Protein Data Bank (PDB) database and utilized RDKit to represent chemical structures as molecular fingerprints. Visualized pairwise similarity scores between molecular fingerprints as a heatmap representation, identifying high-similarity molecules as potential candidates for antimalarial drug development.

    In Silico Analysis of Binding Mode and Affinity for the 3DTC/CEP-6331 Complex using Molecular Docking

    Tools: AutoDock Vina, OpenBabel, LigPlot, MGLTools, Avagadro, COACH server

    Implemented a molecular docking simulation using AutoDock Vina to model the interaction between the 3DTC kinase and the CEP-6331 inhibitor, achieving a predicted binding affinity of -12.23 kcal/mol.Analyzed the top binding pose to identify the specific amino acids responsible for the stable interaction, including key hydrophobic (ILE180, LEU274) and polar (LYS228, ASP284) residues.

    Single-Cell Transcriptomic Profiling of the B16 Melanoma's Microenvironment

    Tools: Seurat, SingleR, DESeq2, dplyr

    Processed raw single-cell transcriptomic data from a B16 melanoma model using R (Seurat), applying quality control, normalization, and clustering to map the tumor’s cellular heterogeneity. Characterized the resulting cell clusters by annotating fourteen distinct cell types within the tumor microenvironment and performed differential expression analysis to identify their unique gene signatures.

    Data-Driven Machine Failure Detection

    Tools: Pandas, NumPy, Scikit-learn, Seaborn

    Developed an automated solution for machine failure prevention by analyzing key metrics such as operating temperature, proximity measurements, electrical current, and environmental factors like air quality and pressure. Employed a Random Forest model, achieving a 2.116% performance improvement over a baseline logistic regression model through feature engineering.

    Computational Analysis of Transcriptional Regulation by the MOV10 Protein

    Tools: SRA Toolkit, FastQC, Trimmomatic, HISAT2, Subread, DESEQ2, UpSetR, ggVennDiagram, EnhancedVolcano, pheatmap

    Investigated the transcriptomic impact of MOV10's knockdown and overexpression by analyzing a public RNA-seq dataset (PRJNA217781), identifying hundreds of differentially expressed genes under knockdown and overexpression conditions. Uncovered a dual regulatory mechanism for MOV10, where its knockdown and overexpression induce two distinct and often inverse transcriptional responses.

    Notable Achievements

    • First runner-up in the Biomimicry Innovation Challenge and Showcase, Vellore Institue of Technology, 2024
    • Top 10 Winner of Bio-Inspired Design Fest (BIDFEST) Ideathon, Vellore Institue of Technology, 2024

    Certificates

    Extra-curricular

    National Service Scheme, NGO - Vellore, India

    Volunteer
    Engaged with students at government schools and conducted sessions on career opportunities

    Becoming I Foundation, NGO - Vellore, India

    Volunteer
    Participated in outreach programs, visiting government schools to teach foundational science, math, and english

    Eco Club, Chettinad Vidyashram - Chennai, India

    Green Ambassador
    Led tree plantations, recycling drives, and plastic waste collection, promoting sustainability and environmental awareness.

    BioSummit, School of Biosciences and Technology - Vellore, India

    Event Coordinator
    Organized a flagship event connecting academia and food industries, managing food distribution and ensuring smooth execution.

    Contact me

    My inbox is always open; glad to connect, discuss and collaborate. Could relate to work, volunteering or a casual talk!
    Feel free to reach out via email ; will get back ASAP!

    Copyrights © Derrin Bright / Last update April 2026