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Research Fellow 蔡懷寬 研
究
Huai-Kuang Tsai 人
員
Ph.D., Computer Science and Information Engineering, Faculty
National Taiwan University, Taiwan
T +86-2-2788-3799 ext. 1718 E hktsai@iis.sinica.edu.tw
F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/hktsai
・ Research Fellow, Institute of Information Science, Academia Sinica (2015/11-present)
・ Professor (Joint appointment), Genome and Systems Biology degree program, National
Taiwan University (2016/8-present)
・ Professor (Joint appointment), Department of Computer Science and Engineering,
National Ocean University (2016/8-present)
・ Professor (Joint appointment), Department of Biological Science and Technology,
National Chiao-Tung University (2016/8-present)
・ Associate Professor (Adjunct), Institute of BioMedical Informatics, National Yang-Ming
University (2013/8-present)
・ Core faculty, Bioinformatics Program, Taiwan International Graduate Program (TIGP),
Academia Sinica (2006/7-present)
・ Editor, Scienti c Reports (2016/9-present)
Research Description
Bioinformatics is an interdisciplinary eld that combines computer science and biology to analyze biological data. My research interests
are functional genomics and pest bioinformatics. For functional genomics, I am interested in understanding the dynamic interactions
between cis- and trans-regulatory elements and the evolutionary signatures of genomes. Our recent progresses include (1) transcriptional
regulatory mechanism and evolution, (2) epigenetics and enhancer function, and (3) discovery of non-coding RNA (ncRNA) and mRNA
isoforms. We recently develop a statistical method to identify the novel factors involving in the transcriptional bu ering during S phase
in the budding yeast, which are validated by the biological experiments. By integrating multi-omics data, we are able to show that the
divergent transcription factor (TF)-binding motifs tend to be introduced in the edges of cis-regulatory regions across evolutionary time.
In addition, we have employed machine learning techniques to investigate the TF binding site prediction and the combinatorial e ect of
TFs on alternative splicing of gene transcripts. As emergence of long ncRNAs (lncRNAs) through evolution may hold the potential role in
transcriptional regulation, we have demonstrated that a notable portion of lncRNAs were derived from pseudogenized protein-coding
genes. Besides, we have constructed the database related to splicing isoforms in di erent organisms and a novel splicing annotation tool.
For pest bioinformatics, we apply bioinformatics approaches to help the pest control management. Our applications cover the discovery
of gene isoforms in mosquitoes, image classi cation of urban pest insects (e.g. termites and red imported re ants), and the metagenome
diversity in the invasive yellow crazy ant. In addition, our team could not only analyze the large amount of biological data but also conduct
the interdisciplinary and collaborative research with di erent biology experts, who experimentally validating novel hypotheses generated by
our analyses.
Publications
1. Chiang, S., Shinohara, H., Huang, J.H., Tsai, H.K.*, and Okada, 6. Tsai, Z.T.Y., Shiu, S.H.*, and Tsai, H.K.* (2015) Contribution of Brochure 2020
M.* (2020) Inferring the transcriptional regulatory mechanism sequence motif, chromatin state, and DNA structure features to
of signal-dependent gene expression via an integrative predictive models of transcription factor binding in yeast, PLoS
computational approach, FEBS Letters, DOI: 10.1002/1873- Computational Biology, 11(8), e1004418.
3468.13757.
7. Tsai, Z.T.Y., Chu, W.Y., Cheng, J.H., and Tsai, H.K.* (2014)
2. Huang, J.H., Kwan, SY. Tsai, T.Y., and Tsai, H.K.* (2018) Associations between intronic non-B DNA structures and exon
Expansion of transcription factor binding sites for introducing skipping, Nucleic Acids Research, 42(2), 739-747.
lineage-specific motifs in the promoter regions, Frontiers in
Genetics, 9, 571. 8. Chen, Y.C., Cheng, J.H., Tsai, Z.T.Y., Tsai, H.K.*, and Chuang
T.J.* (2013) The impact of trans-regulation on the evolutionary
3. Shiau, C.K., Huang, J.H. and Tsai, H.K.* (2018) CATANA: rates of metazoan proteins, Nucleic Acids Research, 41(13),
Comprehensive alternative transcript atlas based on annotation, 6371-80.
Bioinformatics, bty795.
9. Chen, M.J., Chou, L.C., Hsieh, T.T., Lee, D.D., Liu, K.W., Yu,
4. Liu, W.H., Tsai, Z.T.Y., and Tsai, H.K.* (2017) Comparative C.Y., Oyang, Y.J., Tsai, H.K.* and Chen, C.Y.* (2012) De novo
genomic analyses highlight the contribution of pseudogenized motif discovery facilitates identification of interactions between
protein-coding genes to human lincRNAs, BMC Genomics, 18, transcription factors in Saccharomyces cerevisiae, Bioinformatics,
786. 28, 701-708.
5. Cheng, J.H., Pan D., Tsai, Z.T.Y., and Tsai, H.K.* (2015) 10. Wang, T.Y., Su, C.H. and Tsai, H.K.* (2011) MetaRank: a
Genome-wide analysis of enhancer RNA in gene regulation rank conversion scheme for comparative analysis of microbial
across 12 mouse tissues, Scientific Reports, 5, 12648. community compositions, Bioinformatics, 27, 3341-3347.
181
究
Huai-Kuang Tsai 人
員
Ph.D., Computer Science and Information Engineering, Faculty
National Taiwan University, Taiwan
T +86-2-2788-3799 ext. 1718 E hktsai@iis.sinica.edu.tw
F +886-2-2782-4814 W www.iis.sinica.edu.tw/pages/hktsai
・ Research Fellow, Institute of Information Science, Academia Sinica (2015/11-present)
・ Professor (Joint appointment), Genome and Systems Biology degree program, National
Taiwan University (2016/8-present)
・ Professor (Joint appointment), Department of Computer Science and Engineering,
National Ocean University (2016/8-present)
・ Professor (Joint appointment), Department of Biological Science and Technology,
National Chiao-Tung University (2016/8-present)
・ Associate Professor (Adjunct), Institute of BioMedical Informatics, National Yang-Ming
University (2013/8-present)
・ Core faculty, Bioinformatics Program, Taiwan International Graduate Program (TIGP),
Academia Sinica (2006/7-present)
・ Editor, Scienti c Reports (2016/9-present)
Research Description
Bioinformatics is an interdisciplinary eld that combines computer science and biology to analyze biological data. My research interests
are functional genomics and pest bioinformatics. For functional genomics, I am interested in understanding the dynamic interactions
between cis- and trans-regulatory elements and the evolutionary signatures of genomes. Our recent progresses include (1) transcriptional
regulatory mechanism and evolution, (2) epigenetics and enhancer function, and (3) discovery of non-coding RNA (ncRNA) and mRNA
isoforms. We recently develop a statistical method to identify the novel factors involving in the transcriptional bu ering during S phase
in the budding yeast, which are validated by the biological experiments. By integrating multi-omics data, we are able to show that the
divergent transcription factor (TF)-binding motifs tend to be introduced in the edges of cis-regulatory regions across evolutionary time.
In addition, we have employed machine learning techniques to investigate the TF binding site prediction and the combinatorial e ect of
TFs on alternative splicing of gene transcripts. As emergence of long ncRNAs (lncRNAs) through evolution may hold the potential role in
transcriptional regulation, we have demonstrated that a notable portion of lncRNAs were derived from pseudogenized protein-coding
genes. Besides, we have constructed the database related to splicing isoforms in di erent organisms and a novel splicing annotation tool.
For pest bioinformatics, we apply bioinformatics approaches to help the pest control management. Our applications cover the discovery
of gene isoforms in mosquitoes, image classi cation of urban pest insects (e.g. termites and red imported re ants), and the metagenome
diversity in the invasive yellow crazy ant. In addition, our team could not only analyze the large amount of biological data but also conduct
the interdisciplinary and collaborative research with di erent biology experts, who experimentally validating novel hypotheses generated by
our analyses.
Publications
1. Chiang, S., Shinohara, H., Huang, J.H., Tsai, H.K.*, and Okada, 6. Tsai, Z.T.Y., Shiu, S.H.*, and Tsai, H.K.* (2015) Contribution of Brochure 2020
M.* (2020) Inferring the transcriptional regulatory mechanism sequence motif, chromatin state, and DNA structure features to
of signal-dependent gene expression via an integrative predictive models of transcription factor binding in yeast, PLoS
computational approach, FEBS Letters, DOI: 10.1002/1873- Computational Biology, 11(8), e1004418.
3468.13757.
7. Tsai, Z.T.Y., Chu, W.Y., Cheng, J.H., and Tsai, H.K.* (2014)
2. Huang, J.H., Kwan, SY. Tsai, T.Y., and Tsai, H.K.* (2018) Associations between intronic non-B DNA structures and exon
Expansion of transcription factor binding sites for introducing skipping, Nucleic Acids Research, 42(2), 739-747.
lineage-specific motifs in the promoter regions, Frontiers in
Genetics, 9, 571. 8. Chen, Y.C., Cheng, J.H., Tsai, Z.T.Y., Tsai, H.K.*, and Chuang
T.J.* (2013) The impact of trans-regulation on the evolutionary
3. Shiau, C.K., Huang, J.H. and Tsai, H.K.* (2018) CATANA: rates of metazoan proteins, Nucleic Acids Research, 41(13),
Comprehensive alternative transcript atlas based on annotation, 6371-80.
Bioinformatics, bty795.
9. Chen, M.J., Chou, L.C., Hsieh, T.T., Lee, D.D., Liu, K.W., Yu,
4. Liu, W.H., Tsai, Z.T.Y., and Tsai, H.K.* (2017) Comparative C.Y., Oyang, Y.J., Tsai, H.K.* and Chen, C.Y.* (2012) De novo
genomic analyses highlight the contribution of pseudogenized motif discovery facilitates identification of interactions between
protein-coding genes to human lincRNAs, BMC Genomics, 18, transcription factors in Saccharomyces cerevisiae, Bioinformatics,
786. 28, 701-708.
5. Cheng, J.H., Pan D., Tsai, Z.T.Y., and Tsai, H.K.* (2015) 10. Wang, T.Y., Su, C.H. and Tsai, H.K.* (2011) MetaRank: a
Genome-wide analysis of enhancer RNA in gene regulation rank conversion scheme for comparative analysis of microbial
across 12 mouse tissues, Scientific Reports, 5, 12648. community compositions, Bioinformatics, 27, 3341-3347.
181
