BioAI.Com Lab

我們實驗室主要聚焦於「細菌抗藥性」的相關研究上，透過不同的面向切入，涵蓋「抗藥性傳播研究」、「環境抗藥性研究」、「病原菌族群及群落演化研究」、「新型抗藥性機制研究」等，希望能更了解細菌產生抗藥性的動態過程。另外，本實驗室利用NGS及Nanopore定序方式取得細菌全基因體與細菌群落總體基因組資料，並利用MALDI-TOF方法取得單一菌株質譜資料，進行機器學習預測模型的建置，並開發視覺化生物資訊整合平台提供臨床及公衛抗藥性分析使用。除此之外，為了能更有效對抗細菌抗藥性，我們也利用電腦輔助(AI)藥物設計進行新型抗生素的開發。細菌抗藥性是全球重要的公衛議題，攸關所有人的健康，希望對微生物演化、流行病學、傳染病、資料科學、基因體學及藥物設計有興趣的學生加入我們的團隊！

Our laboratory primarily focuses on research related to "bacterial antibiotic resistance," employing various perspectives, including "resistance transmission studies," "environmental resistance studies," "pathogenic bacterial population and community evolution studies," and "novel resistance mechanism research." Our aim is to gain a deeper understanding of the dynamic processes involved in bacterial development of antibiotic resistance. Additionally, our laboratory utilizes Next-Generation Sequencing (NGS) and Nanopore sequencing methods to obtain bacterial whole-genome and community metagenomic data. We employ Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF) to acquire single-strain mass spectrometry data. This information is used to construct machine learning prediction models, and we have developed a visualization bioinformatics integration platform for clinical and public health antibiotic resistance analysis. Furthermore, in our efforts to combat bacterial antibiotic resistance more effectively, we harness computer-assisted (AI) drug design for the development of novel antibiotics. Bacterial antibiotic resistance is a globally significant public health issue, directly impacting the health of all individuals. We welcome students interested in microbiological evolution, epidemiology, infectious diseases, data science, genomics, and drug design to join our team!

徵人中：徵求大學部專題生、碩士生，若對我們的研究有興趣，歡迎跟老師聯絡！

Recruitment: Seeking for undergraduate and master students. If you are interested in our research, please feel free to contact us.

Mail: current788@cc.ncue.edu.tw

Phone: +886-4-723-2105 ext:3462

Asst. Prof. Yen-Yi Liu (劉儼毅老師)