[1] M.-H. Chen, M.-J. Lin, Y.-C. Li, and Y.-C. Lu, “Banded Pair-HMM algorithm for DNA variant calling and its hardware accelerator design,” in 2019 IEEE International Conference on Bioinformatics and Bioengineering. IEEE, 2019, pp. 563–566.
[2] M.-J. Lin, Y.-C. Li, and Y.-C. Lu, “Hardware accelerator design for dynamic-programming-based protein sequence alignment with affine gap tracebacks,” in 2019 IEEE Biomedical Circuits and Systems Conference. IEEE, 2019, pp. 1–4.
[3] Y.-C. Li and Y.-C. Lu, “BLASTP-ACC: Parallel architecture and hardware accelerator design for BLAST-based protein sequence alignment,” IEEE Transactions on Biomedical Circuits and Systems, vol. 13, no. 6, pp. 1771–1782, 2019.
[4] Y.-C. Li, M.-J. Lin, X.-X. Huang, C.-Y. Chen, and Y.-C. Lu, “Comprehensive study of keywords for sequence-based automatic annotation of protein functions,” in 2020 IEEE International Conference on Bioinformatics and Bioengineering. IEEE, 2020, pp. 23–28.
[5] S. Yuan, G. Wu, Y.-C. Li, Y.-C. Lu, and K.-C. Li, “GPU accelerated liquid association GALA,” Statistics and Its Interface, vol. 13, no. 1, pp. 119–125, 2020.
[6] J.-P. Wu, Y.-C. Lin, Y.-W. Wu, S.-W. Hsieh, C.-H. Tai, and Y.-C. Lu, “A memory-efficient accelerator for DNA sequence alignment with two-piece affine gap tracebacks,” in 2021 IEEE International Symposium on Circuits and Systems. IEEE, 2021, pp. 1–4.
[7] H.-W. Liu, Z.-W. Shen, Y.-M. Yeh, and Y.-C. Lu, “A nucleotide-position-based data format for fast variant calling and its hardware analyzer design,” in 2022 IEEE Biomedical Circuits and Systems Conference. IEEE, 2022, pp. 529–533.
[8] C.-Y. Chen, S.-H. Huang, and Y.-C. Lu, “A hardware accelerator for long sequence alignment with the bit-vector scoring scheme and divide-and-conquer traceback,” in 2022 IEEE Biomedical Circuits and Systems Conference. IEEE, 2022, pp. 467–471.
[9] S.-S. Weng, Y.-M. Yeh, Y.-C. Li, and Y.-C. Lu, “An alignment-based hardware accelerator for rapid prediction of RNA secondary structures,” in 2022 IEEE International Symposium on Circuits and Systems. IEEE, 2022, pp. 2700–2704.
[10] Y.-M. Yeh and Y.-C. Lu, “MSRCall: a multi-scale deep neural network to basecall Oxford Nanopore sequences,” Bioinformatics, vol. 38, no. 16, pp. 3877–3884, 2022.
[11] Z.-W. Shen, J.-S. Huang, and Y.-C. Lu, “A memory-efficient accelerator for 128-parallel sequence-to-graph alignment in variant-enriched regions,” in 2024 IEEE Biomedical Circuits and Systems Conference. IEEE, 2024, pp. 1–5.
[12] C.-Y. Tsai, H.-Y. Tseng, P.-Y. Chang, Y.-C. Lu, “Energy-efficient basecalling for ONT long reads on a hybrid ASIC-GPU platform,” in 2025 IEEE Computer Society Annual Symposium on VLSI. IEEE, 2025, pp.1-6.
[13] J.-S. Huang, T.-W. Lin, Y.-C. Lu, “An FPGA accelerator for sequence-to-graph alignment with affine gap penalties,” in 2025 IEEE Biomedical Circuits and Systems Conference. IEEE, 2025, pp. 1-5. (to appear)
[14] C.-H. Lin, P.-Y. Chang, Y.-C. Lu, “BWFA-CAT: Bidirectional wavefront sequence alignment with content-aware tiling and its hardware accelerator,” in 2025 IEEE Asia Pacific Conferences on Circuits and Systems. IEEE, 2025, pp. 1-5. (to appear)
[15] K.-F. Lin, P.-J. Shih, Y.-C. Lu, “An FPGA protein-to-genome aligner with early linking and backtracking prediction schemes,” in 2025 IEEE Biomedical Circuits and Systems Conference. IEEE, 2025, pp. 1-5. (to appear)