PhD - Bioinformatician
📧 archerkuo9006@gmail.com
🔬 ORCID: 0000-0002-6773-8179.
💼 LinkedIn Profile
Bioinformatician with demonstrated strengths in cross-species single-cell omics and reproducible computational pipelines (Genome Biology 2023, 2024; Briefings in Bioinformatics 2026), now transitioning to systems neuroscience and brain–computer interface (BCI) research. Future interests include cross-subject generalization of neural decoders, joint analysis of unsupervised behavioral classifiers with high-channel electrophysiology, and computational tools for translational BCI workflows.
Aug 2024 - Jan 2026
Department of Biotechnology and Bioindustry Sciences, National Cheng Kung University
University Center for Bioscience and Biotechnology, National Cheng Kung University
(Ongoing) Web-Based Single-Cell Metabolomic Data Analysis Platform
Project objective:
- To develop a user-friendly, code-free web-based analysis platform that enables users to perform single-cell metabolomic analyses, including classical single-cell analysis workflows and integrated cell type annotation.
Key contributions:
- Designed and engineered the overall user workflow, prioritising correctness of analytical results and reproducibility through comprehensive record-keeping.
- Led project planning, requirement clarification, and user-flow design.
- Architected and deployed the peripheral infrastructure (firewalls, routers, switches, computation servers, local storage servers), and built the backend with automated bioinformatics analysis pipelines.
- Co-authored the manuscript for publication.
Advanced Technologies of Single-Cell Metabolomics Unveiling Cellular Metabolomic Heterogeneity for Biological and Biomedical Research Journal of Food and Drug Analysis, 2026 | Accepted on Jan 16, 2026
Project objective:
- To provide a comprehensive overview of the current landscape of single-cell metabolomics research.
Key contributions:
- Synthesised the single-cell metabolomics literature, systematically comparing methodologies and findings across studies and organising them into structured summary tables.
- Co-authored the manuscript and led journal submission logistics.
Microbial Volatile 3-Methyl-1-Butanol Enhances Stomatal Closure and Salt Stress Tolerance via Ethylene and Jasmonate Pathways in Arabidopsis
Physiologia Plantarum, 2025 | DOI: 10.1111/ppl.70383
Project objective:
- To investigate the molecular mechanisms by which microbial volatile compounds regulate plant stress responses.
Key contributions:
- Advised the team on transcriptomic and metabolomic analytical strategies.
- Modeled metabolomic profiles to identify differentially accumulated metabolites and enrichment patterns linking microbial signaling to host stress responses.
Aug 2019 - Jun 2024
Department of Life Science and Institute of Plant Biology, National Taiwan University
Single-cell Transcriptomics Unveils Xylem Cell Development and Evolution
Co-first author | Genome Biology, 2023 | DOI: 10.1186/s13059-022-02845-1
PI: Ying-Chung Jimmy Lin
Project objective:
- To explore the developmental trajectories of xylem cells from an evolutionary perspective across angiosperms.
Key contributions:
- Hypothesised cross-species conservation of xylem differentiation programs and resolved it by integrating scRNA-seq with laser-capture microdissection RNA-seq (lcmRNA-seq), creating a comparative single-cell pipeline transferable beyond the original system.
- Conceived a method to integrate and visualise cell-type information within single-cell datasets.
- Designed and executed cross-species comparative analyses spanning multiple angiosperm species.
Sep 2018 - Jul 2019
Department of Plant Pathology and Microbiology, National Taiwan University
Unveiling of Extracellular Exosomal miRNA Profiles of Breast Cancer
Project objective:
- To establish a computational screening approach for breast cancer subtypes.
Key contributions:
- Modeled exosomal miRNA expression with GLM, LDA, and SVM classifiers to discriminate breast-cancer subtypes, demonstrating biomarker-grade predictive performance.
- 🧪 metabolopan — Cross-platform desktop GUI application (Rust) that takes raw MS-DIAL metabolomics output to KEGG over-representation analysis end-to-end: differential abundance testing (Student's / Welch's t-test, Brunner–Munzel) with FDR correction and volcano plots, followed by hypergeometric pathway/module enrichment with dot-plot export. Ships as a self-contained binary for macOS/Linux/Windows with cached PubChem/KEGG REST clients. Demonstrates systems-level programming (Rust) and end-to-end statistical-pipeline engineering transferable to high-channel neural data analysis.
- 🌡️ RemoteTemperatureSensor — ESP8266 + DS18B20 / DS3231 IoT temperature sensor with WiFi cloud logging (C++, Arduino, ThingSpeak). Demonstrates embedded-systems and hardware–software integration skills relevant to neural-recording instrumentation.
- 🧬 ylclab-peptide-blast — Reproducible Nextflow pipeline for peptide BLAST search.
- 🌱 ylclab-carbonhydrate-analysis — Carbohydrate composition analysis pipeline (Python).
AI Agents: Claude Code, GitHub Copilot
Programming Languages: R (10+ years), Python (5+ years), Bash (5+ years), Rust
Containerization: Docker
Version Control: Git, GitHub
Workflow Management: Snakemake, Nextflow
Databases: MariaDB, PostgreSQL
Bioinformatics Tools: NCBI tools, alignment and quantification pipelines, differential expression analysis tools, Cell Ranger, Seurat, and more
Backend: Express
IoT: Arduino (LCD, WiFi modules, sensor modules, and automated remote alerts via the internet)
Doctor of Philosophy | 2018 - 2024
Genome and Systems Biology Degree Program, National Taiwan University
Master's Student | 2017 - 2018
Department of Biochemical Science & Technology, National Taiwan University
Bachelor's Degree | 2013 - 2017
Department of Biochemical Science & Technology, National Taiwan University
Teaching Assistant | 2018 - 2020
General Education Statistics Course: "Statistics and Life"
Teaching Assistant | 2017 - 2019
Fundamental Laboratory Course: "Biotechnology Core Techniques"
Mentorship
Provided guidance and support to MS students in bioinformatics analysis and scientific reasoning