Research Fellow/Professor  |  Lin, Chung-Yen  
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Chung-Yen Lin received B.S., M.S. and Ph.D. in zoology, fishery science and zoology from National Taiwan University (NTU) in 1991, 1993 and 1999, respectively. In 1995, he and his colleague published the first book to introduce internet in Chinese. At the same time, he became a member of Frontier Foundation, the predecessor of YAM Navigator Inc (,  in 1995. And he also joined the team in NTU to edit and publish the textbook for Bioinformatics in 1999. After 4 years postdoc training in Division of Biostatistics and Bioinformatics, National Health Research Institutes (NHRI), he became an assistant researcher in the same departments in the end of 2004. During 2002- 2004, he contributed to his knowledge on IT and life science to help Center of Disease Control (CDC, Taiwan) for constructing pathogens surveillance framework (for Enterovirus and SARS) and developing rapid detective kits for SARS and other pathogens in his own developing algorithm (PDA,, NAR, 2003). In Oct 2005, he joined the institute as an assistant research fellow. And he became an associate research fellow and full research fellow in 2011 and 2020, respectively. Meanwhile, two of his research projects (Electronic Lab notebook and Genome ‐ wide DNA methylation on Cloud) are awarded by Microsoft Inc. for cloud applications from 2011 to 2013.

Recently his research is motivated by a desire to utilize IT/AI innovations to decipher the secrets of nature and make life better. In recent years, my works have focused on the following areas:

1)  Network analyses in tumorigenesis and infectious diseases

To explore essential nodes/hubs and fragile motifs in a complex biological network, he and his team have implemented eleven topological algorithms as cytohubba (, BMC Systems Biology, 2014), collaborated with Prof. Ming-Tat Ko in the Institute of Information Science, Academia Sinica. The new version of cytohubba for Cytoscape 3. x was released in Jan 2017 and downloaded over 120,000 times, with citations nearly 4,000 times at the end of 2023. Cytohubba is a good starting point for new therapies and novel insights into understanding the underlying mechanisms controlling standard cellular processes and disease pathologies. It is widely used in research on infectious diseases, immunology, cancer biomarker identification, natural language analysis, and social network analysis.

2) Developing value-added databases/web applications for biomedical research communities

Recently, his team released new platforms called “Electronic Laboratory Notebook” (ELN,, iScience, 2022) and “Multi-Omics online Analysis System” (MOLAS,, Marine Biotechnology, 2021)  for digitizing daily experimental results on cloud and deciphering the regulatory mechanisms hidden within transcriptomic data generated through next-generation sequencing (NGS), respectively. Meanwhile, ELN was also awarded by NATIONAL INNOVATION AWARD (NIA) 2018(國家新創獎-學研新創獎) and continued to get the NIA excelsior awards from 2019~2021. Many of our databases/ Applications are listed on several Bioinformatics portals and DockerHub (  /GitHub( ) with accumulated users and processed sequences over 400,000 and 2,200,000, respectively. Besides, to provide an integrated genome de novo assembly solution for precision medicine and genome breeding, we implemented GABOLA ( ), a de novo genome assembly system, combining advantages in leading sequencing platforms (next generation Sequencing and 3rd generation long-read sequencing), constructing complete and accurate individual genomes. GABOLA also won the NIA 2021 and Future tech Awards 2021 by MOST.

3) Using Machine learning/ AI to decipher the biological problems

To reveal the tumor micro-environment, Professor Lin with his team estimated immune cell composition from complex tissues in a gene profiling deconvolution approach using 𝛎-Support Vector Regression. The approach performed better than current state-of-the-art deconvolution methods, and it was now implemented as a web application for public use (, BMC Bioinformatics, 2018). Recently, Dr. Lin''s team utilized deep learning to construct predictive models for the activity of Anti-Microbial Peptides (AMP) (, mSystems 2021), anti-cancer peptides (, Pharmaceuticals, 2022), and antiviral peptides (, Bioinformatics Advances, 2022) (Video Clip: ). Through generative adversarial network models, we can produce and screen antimicrobial peptides with high efficacy, accelerating the development of new antimicrobial drugs and reducing the misuse of antibiotics and the emergence of resistant strains, thereby minimizing the waste of limited medical resources (IJMS, 2023). This research was recognized with the 2023 National Innovation Award and was invited to participate in the 2023 Taiwan Medical Technology Exhibition. Additionally, in collaboration with teams from Chang Gung and the National Health Research Institutes, we combined relevant medical records and blood test values to build an artificial intelligence model for early prediction of children''s allergies ( ), which also won the 2023 National Innovation Award and was invited to the 2023 Taiwan Medical Technology Exhibition.


In summary, the objective of his researches is to using IT innovations to make the life better. His interests include interactome of host-pathogens, Omics Biology, medical applications in AI.