Selected Publications
International Journal Papers
    2026
  1. Y.-H. Yu, H.-T Hong, and T.-H. Yang*, “Generalizable deep-learning-based mRNA-protein interaction prediction strongly depends on protein diversity,” Journal of Cheminformatics, 2026 June (SCI 2025 impact factor = 5.7, Ranking 13.6% (35/258) in Computer Science, Information Systems ).
  2. T.-H. Yang, W.-T. Chiu, Y.-H. Chu, H.-T. Hong, C.-W. Liu, L.-Y. Chang, H.-C. Hung, W.-C. Dai, Y.-L. Chen, S. Y. Lim, Y.-C. Chuang, W.-Y. Huang*, and T.-L. Liu*, “A Fluorescence Imaging- and Deep Learning-Based Approach for Detecting Hepatitis B Virus Integration into Host Genomes,” Journal of Imaging Informatics in Medicine, vol. 18, p. 74, 2026 May (SCI 2025 impact factor = 3.8, Ranking 16.9% (36/213) in Radiology, Nuclear Medicine & Medical Imaging).
  3. Y.-H. Yu, W.-C. Dai, Z.-H. Jiang, T.-H. Yang*, “CRMIPred: Identifying the spatial interactions among cis-regulatory modules via considering their cross-attended epigenetic profiles,” Computer Methods and Programs in Biomedicine, vol. 280, p. 109314, 2026 June (SCI 2025 impact factor = 4.8, Ranking 13.6% (20/147) in Computer Science, Theory & Methods).
    CRMIPred can be downloaded at https://github.com/cobisLab/CRMIPred/.
  4. Y.-H. Yu, K.-L He, and T.-H. Yang*, “CRM-TI: an enhanced pipeline for computationally assigning the target genes of cis-regulatory modules by considering comprehensive long-range regulation mechanisms,” BioData Mining, vol. 19, p. 45, 2026 May (SCI 2025 impact factor = 7.4, Ranking 13.6% (5/67) in Computer Science, Information Systems).
    CRM-TI can be downloaded at https://github.com/cobisLab/CRM-TI/.
    5. 2025
  5. T.-H. Yang, Y.-Y. Chen, C.-C. Liao, H.-C. Zheng, C.-L. Hsieh, J.-S. Chen, W.-C. Tsai, Y.-Y. Tseng, W.-S. Wu*, “ NoAC: an automatic builder for knowledge bases and query interfaces on genomes of non-model organisms ,” Journal of Molecular Biology, vol. 437, p. 169488, 2025 Dec. (SCI 2024 impact factor = 4.5, Ranking 26.6% (85/319) in Biochemistry & Molecular Biology).
  6. T.-H. Yang†, Y.-H. Huang†, Y.-H. Lee, J.-N. Lai, K.-D. Chen, M.-H. Guo, Y. Pang, C.-Y. Chen, W.-S. Wu*, and H.-C. Kuo*, “Identifying the risk of Kawasaki disease based solely on routine blood test features through novel construction of machine learning models,” Computational and Structural Biotechnology Journal, vol. 27, pp. 2832–2842, 2025 June (SCI 2024 impact factor = 4.1, Ranking 32.6% (104/319) in Biochemistry & Molecular Biology).
    †: Co-first author
  7. T.-H. Yang, X.-W. Li, Y.-H. Lee, S.-Y. Lu, W.-S. Wu*, and H.-C. Lee* “mirTarCLASH: a comprehensive miRNA target database based on chimeric read-based experiments,” Database, vol. 2025: article ID baaf023; doi:10.1093/database/baaf023, 2025 Apr. (SCI 2024 impact factor = 3.6, Ranking 17.9% (12/67) in Mathematical & Computational Biology).
    8. 2024
  8. T.-H. Yang*, Y.-H. Yu†, S.-H. Wu†, F.-Y. Zhang†, H.-C. Tsai†, and Y.-C. Yang†, “DMLS: an automated pipeline to extract the Drosophila modular transcription regulators and targets from massive literature articles,” Database, vol. 2024: article ID baae049; doi: 10.1093/database/baae049, 2024 Jun. (SCI 2022 impact factor = 5.8, Ranking 10.9% (6/55) in Mathematical & Computational Biology).
    †: These authors contributed equally
    DMLS can be accessed at https://cobis.bme.ncku.edu.tw/DMLS/.
  9. T.-H. Yang†, G.-D. Syu†, C.-S. Chen†, G.-R. Chen, S.-E. Jhong, P.-H. Lin, P.-C. lin, Y.-C. Wang, Pramod Shah, Y.-Y. Tseng, and W.-S. Wu*, “BAPCP: a comprehensive and user-friendly web tool for identifying biomarkers from protein microarray technologies,” Computer Methods and Programs in Biomedicine, vol. 254, p. 108260, 2024 Jun. (SCI 2022 impact factor = 6.1, Ranking 13.5% (15/111) in Computer Science, Theory & Methods).
    †: Co-first authors
  10. T.-H. Yang*, “DEBFold: computational identification of RNA secondary structures for sequences across structural families using deep learning,” Journal of Chemical Information and Modeling, vol. 64 (9), pp. 3756–3766, 2024 May (SCI 2022 impact factor = 5.6, Ranking 18.3% (11/60) in Chemistry, Medicinal).
    DEBFold can be accessed at https://cobis.bme.ncku.edu.tw/DEBFold/.
  11. T.-H. Yang, J.-C. Chen, S.-H. Wu†, F.-Y. Chang†, Y.-C. Huang, M.-H. Lee, Y.-Y. Tseng, and W.-S. Wu*, “Identifying human miRNA target sites via learning the interaction patterns between miRNA and mRNA segments,” Journal of Chemical Information and Modeling, vol. 64 (7), pp. 2445–2453, 2024 Apr. (SCI 2022 impact factor = 5.6, Ranking 18.3% (11/60) in Chemistry, Medicinal).
    †: These authors contributed equally
    12. 2023
  12. T.-H. Yang*, Z.-Y. Liao, Y.-H. Yu, and M. Hsia, “RDDL: a systematic ensemble pipeline tool that streamlines balancing training schemes to reduce the effects of data imbalance in rare-disease-related deep-learning applications,” Computational Biology and Chemistry, vol. 106, p. 107929, 2023 Oct. (SCI 2022 impact factor = 3.1, Ranking 38.7% (43/111) in Biology).
    RDDL can be downloaded at https://github.com/cobisLab/RDDL/.
  13. T.-H. Yang*, Y.-H. Yu†, S.-H. Wu†, and F.-Y. Zhang†, “CFA: an explainable deep learning model for annotating the transcriptional roles of cis-regulatory modules based on epigenetic codes,” Computers in Biology and Medicine, vol. 152, p. 106375, 2023 Jan.(SCI 2021 impact factor = 6.698, Ranking 10.5% (6/57) in Mathematical & Computational Biology).
    †: These authors contributed equally
    CFA can be downloaded at https://github.com/cobisLab/CFA/.
    14. 2022
  14. T.-H. Yang, C.-W. Hsu, Y.-X. Wang, C.-H. Yu, Jagat Rathodd, Y.-Y. Tseng, and W.-S. Wu*, “YMLA: a comparative platform to carry out functional enrichment analysis for multiple gene lists in yeast,” Computers in Biology and Medicine, vol. 151, p. 106314, 2022 Dec. (SCI 2021 impact factor = 6.698, Ranking 10.5% (6/57) in Mathematical & Computational Biology).
  15. T.-H. Yang*, C.-Y. Wang†, H.-C. Tsai†, Y.-C. Yang†, and C.-T. Liu, “YTLR: extracting yeast transcription factor-gene associations from the literature using automated literature readers,” Computational and Structural Biotechnology Journal, vol. 20, pp. 4636-4644, 2022 Aug. (SCI 2021 impact factor = 6.155, Ranking 23.6% (70/296) in Biochemistry & Molecular Biology).
    †: These authors contributed equally
    YTLR can be downloaded at https://github.com/cobisLab/YTLR/.
  16. T.-H. Yang*, Y.-C. Lin†, M. Hsia†, and Z.-Y. Liao†, “SSRTool: a web tool for evaluating RNA secondary structure predictions based on species-specific functional interpretability,” Computational and Structural Biotechnology Journal, vol. 20, pp. 2473-2483, 2022 May (SCI 2020 impact factor = 7.271, Ranking 15% (45/295) in Biochemistry & Molecular Biology).
    †: These authors contributed equally
    SSRTool is available at https://cobis.bme.ncku.edu.tw/SSRTool/.
  17. W.-S. Wu†, T.-H. Yang†, K.-D. Chen, P.-H. Lin, G.-R. Chen, and H.-C. Kuo*, “KDmarkers: A biomarker database for investigating epigenetic methylation and gene expression levels in Kawasaki disease,” Computational and Structural Biotechnology Journal, vol. 20, pp. 1295-1305, 2022 Mar. (SCI 2020 impact factor = 7.271, Ranking 15% (45/295) in Biochemistry & Molecular Biology).
    †: co-first authors
  18. T.-H. Yang*, “An aggregation method to identify the RNA meta-stable secondary structure and its functionally interpretable structure ensemble,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 19, no. 1, pp. 75–86, 2022 Feb. (SCI 2020 impact factor = 3.710, Ranking 12% (15/125) in Statistics & Probability).
    19. 2021
  19. T.-H. Yang*, Y.-C. Yang† and K.-C. Tu†, “regCNN: identifying Drosophila genome-wide cis-regulatory modules via integrating the local patterns in epigenetic marks and transcription factor binding motifs,” Computational and Structural Biotechnology Journal, vol. 20, pp. 296-308, 2021 Dec. (SCI 2020 impact factor = 7.271, Ranking 15% (45/295) in Biochemistry & Molecular Biology).
    †: These authors contributed equally
    The regCNN download website is now moved to https://cobis.bme.ncku.edu.tw/regCNN/.
  20. T.-H. Yang, S.-C. Shiue, K.-Y. Chen, Y.-Y. Tseng, and W.-S. Wu*, “Identifying piRNA targets on mRNAs in C. elegans using a deep multi-head attention network,” BMC Bioinformatics, vol. 22, no. 1, pp. 1-23, 2021 Oct. (SCI 2020 impact factor = 3.169, Ranking 27.6% (16/58) in Mathematical & Computational Biology).
  21. T.-H. Yang, Y.-H. Chiang, S.-C. Shiue, P.-H. Lin, Y.-C. Yang†, K.-C. Tu†, Y.-Y. Tseng, J.-T. Tseng*, and W.-S. Wu*, “Cancer DEIso: An integrative analysis platform for investigating differentially expressed gene-level and isoform-level human cancer markers,” Computational and Structural Biotechnology Journal, vol. 19, pp. 5149-5159, 2021 Sep. (SCI 2020 impact factor = 7.271, Ranking 15% (45/295) in Biochemistry & Molecular Biology).
    †: These authors contributed equally
  22. T.-H. Yang*, C.-Y. Wang†, H.-C. Tsai†, and C.-T. Liu†, “Human IRES Atlas: an integrative platform for studying IRES-driven translational regulation in humans,” Database, vol. 2021: article ID baab025; doi:10.1093/database/baab025, 2021 May (SCI 2020 impact factor = 3.451, Ranking 24% (14/58) in Mathematical & Computational Biology).
    †: These authors contributed equally
    The website of Human IRES Atlas is now moved to https://cobis.bme.ncku.edu.tw/Human_IRES_Atlas/.
    23. 2019
  23. T.-H. Yang*, “Transcription factor regulatory modules provide the molecular mechanisms for functional redundancy observed among transcription factors in yeast,” BMC Bioinformatics, vol. 20, no. 23, pp. 1-16, 2019. Dec. (SCI 2018 impact factor = 2.511, Ranking 15.3% (9/59) in Mathematical & Computational Biology).
    24. 2014
  24. T.-H. Yang, C.-C. Wang, P.-C. Hung, and W.-S. Wu*, “cisMEP: an integrated repository of genomic epigenetic profiles and cis-regulatory modules in Drosophila,” BMC Systems Biology, vol. 8, no. Suppl 4, p. S8, 2014. (SCI 2013 impact factor = 2.853, Ranking 13% (7/52) in Mathematical & Computational Biology).
  25. T.-H. Yang, H.-T. Chang, E. S. Hsiao, J.-L. Sun, C.-C. Wang, H.-Y. Wu, P.-C. Liao*, and W.-S. Wu*, “iPhos: toolkit to streamline the alkaline phosphatase assisted comprehensive LC-MS phosphoproteome investigation,” BMC Bioinformatics, vol. 15, no. Suppl 16, p. S10, 2014. (SCI 2013 impact factor = 2.672, Ranking 15% (8/52) in Mathematical & Computational Biology).
  26. P.-C. Hung, T.-H. Yang, H.-J. Liao*, and W.-S. Wu*, “The Yeast Nucleosome Atlas (YNA) database: An integrative gene mining platform for studying chromatin structure and its regulation in yeast,” BMC Genomics, vol. 15, no. Suppl 9, p. S5, 2014. (SCI 2013 impact factor = 4.041, Ranking 18% (29/165) in Biotechnology & Applied Microbiology).
  27. T.-H. Yang, C.-C. Wang, Y.-C. Wang, and W.-S. Wu*, “YTRP: a repository for yeast transcriptional regulatory pathways,” Database, vol. 2014: article ID bau014; doi:10.1093/database/bau014, 2014. (SCI 2013 impact factor = 4.457 , Ranking 9.6% (5/52) in Mathematical & Computational Biology).
    28. 2013
  28. F.-J. Lai, C.-C. Chiu, T.-H. Yang, Y.-M. Huang, and W.-S. Wu*, “Identifying functional transcription factor binding sites in yeast by considering their positional preference in the promoters,” PLOS ONE, vol. 8, no. 12, p. e83791, 2013. (SCI 2012 impact factor = 3.73, Ranking 13% (7/56) in Multidisciplinary Sciences).
  29. T.-H. Yang and W.-S. Wu*, “Inferring functional transcription factor-gene binding pairs by integrating transcription factor binding data with transcription factor knockout data,” BMC Systems Biology, vol. 7, no. Suppl 6, p. S13, 2013. (SCI 2012 impact factor = 2.982, Ranking 15% (7/47) in Mathematical & Computational Biology).
    30. 2012
  30. T.-H. Yang and W.-S. Wu*, “Identifying biologically interpretable transcription factor knockout targets by jointly analyzing the transcription factor knockout microarray and the ChIP-chip data,” BMC Systems Biology, vol. 6, no. 1, p. 102, 2012. (SCI 2011 impact factor = 3.15, Ranking 9% (4/47) in Mathematical & Computational Biology).