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About Us
The Taiwan International Graduate Program has been established to attract highly qualified young researchers both from home and abroad in order to help jump-start the development of several frontier areas that are crucial to the future development in science and technology. Specific graduate programs have been developed to enhance the innovative potential and academic standards of research on these and related fields. Within this context, the graduate program on “Bioinformatics” is designed to offer specific training and research opportunities to Ph.D. students interested in working on this particular area.

The TIGP Program on Bioinformatics (BP) is a joint-degree program sponsored by Academia Sinica (Institute of Information Science, Institute of Statistical Science, and Institute of Biomedical Sciences), National Tsing Hua University, National Chiao Tung University and National Yang Ming University. Additional teaching support will be available from other major research universities in Taiwan. Unlike most Bioinformatics programs offered in other universities that adopt existing courses in various departments, our courses are specifically designed for BP students and taught by active and experienced researchers in bioinformatics. The program provides interdisciplinary training and research opportunities that seamlessly integrate the related areas so that students can be well-prepared for independent research in this new, fascinating areas of bioinformatics. We will focus on genetics and proteomics study and emphasize data transfer, data analysis, biological information and biological feature extraction, knowledge management using advanced computation methodologies and computer science technology.

Our research areas include but not limited to the following:
● Computational biology: This area focuses on the design of various algorithms for sequence analysis, gene prediction, disease gene mapping, motif finding, and gene networks.
● Biological knowledge management: This area focuses on the integration of various heterogeneous databases, biological knowledge representation, automation of pipeline experiments, and the construction of various annotation databases. In addition, biological literature search is also a crucial component.
● Bioinformatics applications: This area focuses on using existing tools to analyze biological sequences, microarray data, proteomic data, etc. Statistical analysis and data mining techniques will be used to reach the goal of "information-driven biomedical research."
● Computational structural biology: This area focuses on protein structure prediction and classification, automated biomolecule docking, and molecular dynamics.