Research Areas

1Systems Biology(Jia-Le Wu | Distinguished Professor)

Systems biology is an interdisciplinary research field that has emerged in recent years within bioinformatics. Where past research could only address a single gene or protein, the rapid advancement of biotechnology — such as the emergence of microarray and proteomics technologies — has accumulated vast amounts of data, allowing biologists today to examine molecular biological systems from a macroscopic (systems) perspective. In other words, today's data both permits and requires the simultaneous analysis of multiple genes or proteins. Because these components are not independent but interact with one another, new biological phenomena can emerge at different levels of biological systems. Systems biology research integrates multiple fields — such as molecular biology, computer science, mathematics, physics, and chemistry — to investigate biological phenomena at the level of cells, tissues, organs, populations, or ecosystems.

Advances in high-throughput experiments have yielded vast amounts of biological data across species, such as genomics, translatomics, proteomics, and metabolomics. New algorithms and mathematical models are needed to describe the dynamic behavior of biological systems and to compare predictions (hypotheses) against experimental data.

Research on Protein-Protein Interactions
The study of protein-protein interactions (PPIs) is one approach to systems biology research. Since proteins are composed of functional units known as domains, large-scale study of domain-domain interactions (DDIs) can deepen our understanding of interactions between cancer proteins, contributing to biomedical research.

Research on Cancer-Related Genes
Microarray experiments can record the expression of tens of thousands of genes at once, and data analysis can identify differentially expressed genes (DEGs) among them. This research uses R and Bioconductor to identify differentially expressed genes in prostate cancer microarrays, and then draws on three databases — tumor-associated genes (TAG), miRNA-regulated PPI pathways (ncRNAppi), and disease-associated microRNAs (miR2Disease) — to investigate the miRNAs regulating these DEGs and their relationship to human cancer.

Research on Pathogen-Host Interactions
Plant systems (such as Arabidopsis) are frequently infected by various bacterial pathogens, including viruses, bacteria, fungi, nematodes, and other pests. This research uses microarray experimental data to investigate differentially expressed genes in Arabidopsis infected by Xanthomonas campestris pv. campestris (Xcc) and Agrobacterium. Biological networks are composed of modules with similar functions, known as network motifs, which play important roles in many molecular biological processes. Common network motifs include the feed-forward loop, the single-input module, and the bi-fan, each with important dynamical properties. This research integrates microRNAs, DEGs, and network motifs to construct miRNA-regulated network motifs, furthering our understanding of the molecular mechanisms behind pathogen-host interactions during infection.

Research on Network Motifs
In the post-genomic era, systems-level analysis methods can benefit the study of biological networks and gene regulatory networks. Using graph-theoretic methods, this research performs global analysis of protein-protein interaction networks to identify interacting proteins and network substructures. For proteins of unknown function, predictions can be made using proteins of known function within the same sub-network; the effects of these predicted proteins on gene regulatory networks are then considered in predicting those networks. This research has the following goals: 1) large-scale collection of biomolecular regulatory relationship data; 2) development of an algorithm to identify the major network motifs across various biological networks; and 3) investigation of motif-motif interactions. Large-scale regulatory relationship data can serve as a foundation for future research across multiple biological networks. Information on motif-motif interactions can be used to build a global architecture of biological networks in a bottom-up manner. Because motifs are functionally specific, they may be evolutionarily conserved, allowing investigation of network motif conservation across higher animals.

• Education: Ph.D. in Physics, Vanderbilt University, USA
• Research Expertise: Microarray data analysis, protein-protein interaction, microRNA function and cancer, pathogen-host interaction
• Office / Extension: 4F, I408, Information and Electrical Engineering Building｜ext. 1856
• Courses Taught (AY 2026, Academic Year 115): Machine Learning (Doctoral), Seminar (III) (Doctoral)
• Selected Publications / Research Focus: Recent representative journal papers include studies on a tumor metastasis gene database, microRNA prognosis analysis in clear cell renal carcinoma, and drug screening based on gene expression signatures in breast cancer cell lines.

2Omics(Pei-Chun Chang | Associate Professor)

Omics is an interdisciplinary field within the biological sciences focused on integrating biological data and inferring the relationships within it. Omics encompasses genomics, proteomics, transcriptomics, metabolomics, histomics, and interactomics, among others. The core goals of omics research are: 1) identifying and annotating each element within an organism's genome, proteome, transcriptome, metabolome, histome, and interactome; 2) determining the interaction relationships among elements within each -ome, whether through experimental observation or manual definition; 3) mapping genes, proteins, ligands, and related information onto different biological states; 4) representing the network structure of a given element under a specific biological state; and 5) integrating the various omics fields.

For example, in cancer genomics, tissue microarray experiments yield gene expression data across various cancer subtypes, enabling study of how the full set of genes and mutations in the human cancer genome affect cancer cell development, and how a localized cancer progresses to metastatic cancer. These gene interaction network relationships can be visualized, and the insights gained can be applied to anticancer drug design.

• Education: Ph.D. in Chemistry, National Taiwan University
• Research Expertise: Biomedical informatics, computational chemistry
• Office / Extension: 4F, I416, Information and Electrical Engineering Building｜ext. 1868
• Courses Taught (AY 2026, Academic Year 115): Systems Biology, General Chemistry, Science and Innovation in Everyday Life-3
• Selected Publications / Research Focus: Published over 30 journal papers and led over 20 research projects, covering cancer classification, gene network analysis, and drug discovery, while also mentoring numerous undergraduate research projects.

3Bioinformatics Software Applications(Wen-Ling Chan | Associate Professor, Head, Documentation Section, Secretariat)

Non-Coding RNA and Cancer Pathogenesis
Non-coding RNA (ncRNA) refers to RNA molecules that are not translated into protein. Based on size, biological characteristics, and physiological function, they are classified into small RNA (sRNA) and long non-coding RNA (lncRNA). lncRNAs are ncRNAs longer than 200 bp; research suggests they are likely quite abundant within cells, in numbers possibly comparable to protein-coding genes. The functions of a small number of lncRNAs have been confirmed, including regulating the transcription of neighboring genes, regulating alternative splicing, affecting chromatin remodeling, altering histone modifications, generating endogenous small RNAs (siRNAs or other small RNAs), and regulating protein activity. For some diseases, the pathogenic mechanism involves not only changes in protein-coding genes but also requires the regulation of related lncRNAs to be fully explained. Growing evidence shows that these non-protein-coding ncRNAs play important roles in normal physiology, biological development, and disease formation. This research team integrates various biological databases, combining microarray and NGS data to comprehensively construct and investigate the function and regulatory mechanisms of ncRNAs.

• Education: Ph.D. in Bioinformatics, National Yang Ming Chiao Tung University
• Research Expertise: Bioinformatics, systems biology
• Office / Extension: Information Building IB02｜ext. 20102
• Courses Taught (AY 2026, Academic Year 115): Introduction to Biomedical Informatics and Medical Engineering, Bioinformatics Software Applications, Data Structures and Algorithms, Smart Mobile Care App (Continuing Education Bachelor's Program), Exploring Taichung — City of Sustainability-2
• Selected Publications / Research Focus: Published over 20 journal papers; main research includes pan-cancer gene expression/mutation/methylation analysis and predicting hepatocellular carcinoma recurrence via hepatitis B virus gene mutations.

4Precision Medicine Research(Chao-Neng Wang | Professor, Director of Industry-Academia Collaboration)

Precision medicine has become a global healthcare development trend. As medical big data and artificial intelligence advance rapidly, countries worldwide are increasingly focused on developing precision medicine. Further uncovering the associations between genomics, clinical data, life-history data, and disease requires the integration of large-scale, multidimensional big data.

Disease gene detection technologies and analysis platforms based on Next-Generation Sequencing (NGS) span applications including disease prevention, prediction, treatment, and prognosis analysis, providing patients, physicians, academic research institutions, and pharmaceutical companies with new clinical disease gene testing services.

Medical Big Data in Disease Risk Assessment
Understanding the profile of medical data through exploratory data analysis helps in formulating disease risk assessment models. Combining AI techniques with medical big data to predict disease occurrence risk differs from traditional epidemiological risk prediction. The combination of medical big data and AI allows prediction models to be continuously updated and refined as disease events occur. For example, if a model predicts an increased future risk of kidney disease for a given individual, healthcare providers can intervene early to reduce disease occurrence. In the future, omics data may be integrated into prediction models to improve accuracy, moving toward personalized healthcare management.

Development of an Immunotherapy Candidate Gene Screening Platform
The goal of immunotherapy is to enable the body's immune system to re-recognize cancer cells and attack tumors more effectively. Immunotherapy works through two main principles: stimulating the body's own immune system to attack cancer cells, or supplying substances the immune system needs. Immune cells and stromal cells are the two main components of the tumor microenvironment, and research shows they are valuable for tumor diagnosis and prognosis assessment. The core of the immunotherapy candidate gene screening platform is to integrate bioinformatics and machine learning to identify key marker genes and related biological pathways. Screening results in the tumor microenvironment suggest that these stromal cells and their marker genes may in the future serve as biomarkers for cancer treatment and prediction.

Accelerating Precision Medicine Reports with Natural Language Processing
The development of precision medicine has become a global trend in medical research. Simply put, precision medicine means tailoring treatment to the individual by integrating gene sequencing with biomedical big data analysis, providing richer and more precise insights for clinical judgment, enabling more accurate diagnosis and medication, and ultimately supporting personalized medicine. How medical data resources and unstructured data are integrated will determine the future of precision medicine. Within biomedical literature, the PubMed database alone contains approximately 28 million biomedical papers. This team provides a set of natural language processing techniques — spanning unstructured annotation, machine learning and deep learning-based prediction, and final result validation — to precisely analyze diseases, drugs, genes, mutation sites, and gene-drug associations within biomedical literature, ultimately building a database that gives clinicians the best predictions and prevention, diagnosis, and treatment decisions, helping patients better understand themselves, choose the best drugs and treatment plans, and further manage their personal health.

• Education: Ph.D. in Bioinformatics and Biomedical Informatics, Asia University
• Research Expertise: Semantic computing, artificial intelligence, systems biology, biomedical informatics
• Office / Extension: 4F, I414, Information and Electrical Engineering Building｜ext. 1850
• Selected Publications / Research Focus: Published over 60 journal papers, with recent works covering machine learning in clinical applications and bioinformatics analysis; recipient of the 21st National Innovation Award in the Clinical Innovation category, and winner of first place in the Ministry of Education's “Asian Silicon Valley Smart Innovation” category in 2022.

1Biosensing(Wen-Pin Hu | Associate Professor, Deputy Dean of R&D)

Surface plasmon resonance (SPR) is a versatile and highly sensitive technique used in many applications. Surface plasmon waves are evanescent electromagnetic waves, with maximum intensity occurring at the interface where the plasmon wave is generated; wave intensity decays exponentially with distance from this interface. The Kretschmann configuration is most commonly used to excite surface plasmon waves. In this configuration, the sensor surface — formed by a metal film — has the biological sample under study immobilized on it. Light used to excite the surface plasmon wave passes through a prism and strikes the thin metal film; the light couples to the plasmon mode of the metal film, and part of the light reflects back through the prism, where it is detected by a photodetector. Changes in the detected light intensity represent changes in the biomolecular layer on the metal film.

Surface plasmon biosensors can provide real-time and kinetic information on biomolecular interactions, making them useful for detecting biological analytes and analyzing biomolecular interactions. Surface plasmon resonance measurement requires no labeling of biomolecules, and even allows real-time monitoring and quantitative analysis. This sensing technology has already been applied in areas such as biomedical diagnostics, food safety testing, and drug development.

Although the sensitivity of such label-free biosensors has improved substantially through engineering advances, it still cannot match that of biosensors requiring labeling. In addition, a label-free biosensor typically requires precision instrumentation. Our research focuses on optimizing the chemical modification of the sensing surface and improving the measurement instrumentation, to enhance the sensitivity of surface plasmon resonance technology for biomedical detection and lower its detection limit.

• Education: Ph.D. in Biomedical Engineering, National Cheng Kung University
• Research Expertise: Medical engineering, biosensing, bio-optics, biomechanics
• Office / Extension: 5F, H50C, Information Building｜ext. 1881
• Courses Taught (AY 2026, Academic Year 115): Introduction to Biomedical Sensing Technology (Doctoral), Windows Programming, Physiology, Information Seminar
• Selected Publications / Research Focus: Representative works include a 2026 paper on aptamers and silicon nanowire field-effect transistors; ongoing project: “Developing an Interleukin-17A Detection Technique Using Novel Aptamer-Modified Field-Effect Transistors” (2026.08–2027.07).

2Biophotonics and Ultrasound Research(Yu-Lin Sung | Associate Professor)

Biomedical sensing devices have been a key R&D focus in biotechnology worldwide in recent years. This research combines biophotonics and ultrasound development technology with nano/micro-electromechanical fabrication techniques, applying them to disease prevention, detection, tracking, and analysis, in order to identify causes and effective treatments. Research expertise: 1. Ultrasound imaging. 2. Design and development of cochlear implants. 3. Design of optoelectronic-driven hearing aids. 4. Drug encapsulation and delivery technology. 5. Surface acoustic wave (SAW) devices applied to biomedical sensing components.

Current research topics include: “Development of Novel SAW Devices for Drug Delivery,” “Development of Drug Delivery System Components for Treating Middle Ear Disease,” “Research on Novel Hearing Aids,” “Polymer Nano-Drying for Drug Encapsulation and Delivery Applications,” “ZnO Nanorods Applied to LEDs to Enhance Biophotonic Properties,” “Preliminary Development of Muscle Density Scanning,” “High-Frequency Ultrasound-Guided Anesthesia Puncture Probe System,” “Development of an Ultrasonic Atomizer for Chitosan Micro-Carrier Encapsulation Applications,” and “Development of an Automated Ultrasonic Muscle Mass Detector and Its Clinical Trial Application in Sarcopenia Screening.”

• Education: Ph.D. in Physics, National Taiwan University
• Research Expertise: Biomedical device research, acousto-optic device research, biomedical electronics research, nano-optoelectronics research
• Office / Extension: 6F, I626, Information and Electrical Engineering Building｜ext. 1811
• Courses Taught (AY 2026, Academic Year 115): Engineering Mathematics, Electronics
• Selected Publications / Research Focus: Published over 20 journal papers covering GaN HEMT devices, ultrasound equipment, electromagnetic interference shielding, and sarcopenia detection; also published 2 books and holds 3 technology transfer agreements (a middle-ear-infection drug delivery device, an ultrasonic metamaterial lens, and an air circulation filtration system).

33D Printing(Yu-Fang Shen | Associate Professor)

Three-dimensional printing originally referred to a patented process (3DPTM) developed at the Massachusetts Institute of Technology, and is now a general term for additive manufacturing. In its early stages, it was mainly used to produce prototypes of workpieces, but as computer technology has advanced, the precision and structural strength of 3D printing have continuously improved, leading to broader application across many fields; it is now regarded as a key technology driving the third industrial revolution.

In the medical field today, increases in printable size, material variety, and precision have expanded the possibility of rapidly producing customized, high-end medical devices, giving 3D printing enormous development potential in healthcare. Medical devices that can be produced by 3D printing include surgical models, surgical guides, and customized implants, applicable across specialties such as craniomaxillofacial surgery, artificial joints, dental implant orthodontics, apical treatment, spinal correction, and prosthetics/orthotics — offering a degree of fit and realism that better matches individual patient needs than currently available medical device options.

3D printing is already used in clinical surgical assistance, medical teaching models, and personalized implants; future research will focus on cell printing, biodegradable implants, and regenerative medicine. In addition, to meet diverse printing requirements, this research also focuses on developing new printing materials suited to the mechanical properties of the target object, and is committed to developing biodegradable, highly biocompatible, non-toxic, environmentally friendly materials for use in biomedical and tissue engineering applications.

• Education: Ph.D. in Chemistry, National Chung Hsing University
• Research Expertise: Biomedical materials, tissue engineering and regenerative medicine, 3D printing, medical engineering
• Office / Extension: Basement, HB50, Health Building｜ext. 20050
• Courses Taught (AY 2026, Academic Year 115): Introduction to Biomedical Materials (Master's), Polymer Materials Science, Medical Engineering Laboratory, Seminar (I) (Master's), Basic Biochemistry
• Selected Publications / Research Focus: Recent research covers 3D printing, cell building blocks, exosomes, tissue engineering scaffolds, wound dressings, and cancer drug screening applications.

4Medical, Hygiene, and Protective Textiles(Ching-Wen Lou | Distinguished Professor)

Beyond aesthetic textiles for general clothing and home furnishings, textiles widely used in industry, agriculture, animal husbandry, fisheries, infrastructure, transportation, medical and hygiene applications, protective equipment, sports, military, and aerospace are known as Technical Textiles. Medical applications fall into four categories: (1) non-implantable materials, such as bandages, plaster casts, and gauze; (2) extracorporeal devices, such as neck braces and triangular bandages; (3) implantable materials, such as bone scaffolds, dressings, vascular stents, artificial blood vessels, and sutures; and (4) medical and healthcare products, such as surgical gowns, caps, shoes, and mattresses. Hygiene applications include products such as diapers, sanitary pads, and wet wipes.

Protective applications fall into two categories: (1) short-term protection, such as ballistic, stab, and needle-puncture resistance; and (2) long-term protection, such as industrial and medical protective clothing components and firefighter protective gear. Our main research work focuses on functional process design for textiles and evaluating their suitability as technical textiles.

Our current research directions are: (1) composite yarns, fabrics, and reinforced thermoplastic composite panels with electrostatic protection, electromagnetic interference shielding, and far-infrared radiation functions; (2) designing wearable electronics that integrate circuits, detection, and alarm systems; (3) puncture-resistant protective composite fabrics; (4) composite fabrics for artificial bone scaffolds and vascular stents; and (5) polymer solution membrane and nanofiber membrane composite wound dressings.

• Education: Ph.D. in Textile Engineering, Feng Chia University
• Research Expertise: Medical textiles, functional textiles, artificial medical dressings, textile engineering, medical and healthcare composite materials, smart wearable textiles
• Office / Extension: 6F, I614, Information and Electrical Engineering Building｜ext. 1755
• Selected Publications / Research Focus: Published over 150 journal papers from 2021–2026, covering fiber materials, composite materials, energy conversion, and medical applications, published in international journals such as LANGMUIR, Chemical Engineering Journal, and ACS Applied Materials.

5Tissue Engineering(Chia-Che Ho | Deputy Chair, Associate Professor)

Tissue engineering uses pre-fabricated scaffolds with porous structure, biocompatibility, and biodegradability to provide mechanical support for damaged tissue, maintain tissue shape, and serve as a bridge guiding and accelerating tissue growth into the scaffold. The porous structure is designed to improve the efficiency of nutrient and metabolite transport during tissue regeneration; by adjusting the scaffold's degradation rate, the scaffold gradually degrades and is metabolized within the body, ultimately being replaced by newly formed tissue to achieve complete tissue regeneration.

Recent advances in bioprinting manufacturing have opened a new chapter in the applicability and feasibility of tissue engineering for regenerative medicine. It works by using an automated positioning system to arrange bio-ink — composed of cells and biomedical materials — with different cell types, materials, and biomolecules at different positions, so that the resulting product not only resembles human tissue in macroscopic structure but also allows control over the internal cell composition and microenvironment to facilitate tissue regeneration. However, the properties of the bio-ink greatly affect the efficiency of cell growth, differentiation, and tissue remodeling. Our research therefore focuses on developing biomedical materials suited to bioprinting systems, investigating how the physicochemical properties of materials affect cell growth, and improving the printability of medical materials through parameter control.

• Education: Ph.D. in Oral Sciences, Chung Shan Medical University
• Research Expertise: Additive manufacturing and bioprinting, tissue engineering, biomedical materials, nanomaterials, surface modification, drug delivery systems
• Office / Extension: Basement, HB02, Health Building｜ext. 20002
• Selected Publications / Research Focus: 20 journal papers and 10 conference papers from 2018–2026; 9 research projects (funded by NSTC/MOST/Asia University and others), and mentored 4 undergraduate research projects (2020–2025, Academic Years 109–114).

6Biomedical Materials(Wen-Yu Su | Assistant Professor)

Biomaterials are one of the rapidly developing fields in recent years. Biomaterials broadly refer to the materials used in medical devices intended for use inside or outside the body, including categories such as medical metal materials, medical ceramic materials, medical polymer materials, and medical composite materials, among others. Because these materials come into direct or indirect contact with living organisms — and may even remain within the body long-term, interacting with tissue — the main difference between biomedical materials and general industrial materials is that they must have good biocompatibility.

Biomedical materials are currently applied across a wide range of medical devices, from everyday items such as adhesive bandages, contact lenses, and syringes, to implantable devices such as artificial joints and bone cement, all of which employ various biomedical materials. Our current main research direction is implantable biodegradable medical devices, primarily using natural polymer materials that generally have good biocompatibility, such as hyaluronic acid, collagen, and chitosan. Main application areas include antibiotic-loaded bone substitutes, vitreous substitutes, wound dressings, and nerve guiding channels (NGC), with efforts made in collaboration with industry resources to move toward productization wherever possible.

• Education: Ph.D. in Biomedical Engineering, National Taiwan University
• Research Expertise: Biomedical ceramic materials, tissue engineering and regenerative medicine, environmentally responsive hydrogels
• Office / Extension: Basement, HB23, Health Building｜ext. 20023
• Courses Taught (AY 2026, Academic Year 115): Calculus (I), Introduction to Biomedical Informatics and Medical Engineering, Information Seminar, Biomedical Innovation and Commercialization, Capstone Project (II)
• Selected Publications / Research Focus: Journal papers cover nerve guiding channels and MRI biomarker research; conference papers cover injectable hydrogels and tissue engineering scaffold applications; in recent years, has mentored numerous undergraduate students in research projects on bone tissue engineering, cartilage repair, and nerve repair.