Bioinformatics and Multi-omics Data Application Core Lab

Introduction

With the advancement of high-throughput technologies such as proteomics, metabolomics, and next-generation sequencing, biomedical informatics analysis plays a crucial role in both academic and clinical research. In response to this interdisciplinary progress, the Chang Gung Molecular Medicine Research Center has successfully implemented numerous biomedical informatics analysis technologies. The center's primary focus lies in integrating cancer biomarkers and conducting a comprehensive analysis of next-generation sequencing data. These cutting-edge technologies encompass a wide range of omics analysis tools, microbiota analysis, proteomics analysis, as well as customized bioinformatics and statistical analysis. Looking ahead, the core laboratory aims to develop novel analytical techniques that seamlessly incorporate artificial intelligence, enabling the systematic analysis of multi-omics data, clinical information, medication records, and more. Ultimately, these advancements will facilitate the effective application of personalized precision medicine. Furthermore, the bioinformatics core laboratory has already established a high-performance computing cluster server, along with a high-speed distributed file system and backup system, enabling rapid processing of diverse omics-based biomedical big data.

Goal

Our objective is to establish a dedicated core laboratory focused on the application of biomedical informatics and omics data. We aim to develop a comprehensive biomedical informatics website system, an automated workflow, and an interactive visualization presentation system that can be universally utilized.
We are committed to developing analysis techniques specifically tailored to omics big data and providing high-quality biomedical informatics research analysis services.
Our goal is to successfully execute the research plan of the Chang Gung Molecular Medicine Research Center and establish a comprehensive cross-omics biomedical database, with a specific emphasis on cancer-related data.
Through the integration of artificial intelligence, our aim is to leverage its potential in processing multi-omics high-throughput data, integrating clinical and medication information, and enhancing the application of translational research in a clinical setting.
We are dedicated to promoting the advancement of biomedical informatics analysis techniques and providing education and training opportunities for individuals interested in developing their talent in information analysis.