Mao-Jan Lin

Mao-Jan Lin

PhD student at Johns Hopkins University

Posts by Collection

portfolio

publications

Hardware Accelerator Design for Dynamic-Programming-Based Protein Sequence Alignment with Affine Gap Tracebacks

Published in 2019 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2019

We propose an ASIC design for dynamic programming sequence alignment with affine-gap traceback. The architecture reduce memory usage for traceback by 25%. The design speed up pairwise alignment by 570x

Recommended citation: Lin, Mao-Jan, Yu-Cheng Li, and Yi-Chang Lu. "Hardware accelerator design for dynamic-programming-based protein sequence alignment with affine gap tracebacks." 2019 IEEE Biomedical Circuits and Systems Conference (BioCAS). IEEE, 2019.
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Profiling genes encoding the adaptive immune receptor repertoire with gAIRR Suite

Published in Frontiers in Immunology, 2022

gAIRR-Suite is a new toolkit profiling genes encoding the Adaptive Immune Receptor Repertoire (AIRR). We combined experimental and computational methods to genotype both documented and novel V, D, J genes in the human germline genome.

Recommended citation: Lin, Mao-Jan, et al. "Profiling genes encoding the adaptive immune receptor repertoire with gAIRR Suite." Frontiers in Immunology 13 (2022): 922513.
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Traceback Memory Reduction for Three-Sequence Alignment Algorithm with Affine Gap Models

Published in 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2022

A traceback encoding design reduces memory requirements for three-sequence alignment with affine gap models.

Recommended citation: Chien, Ruei-Ting, Mao-Jan Lin, Yang-Ming Yeh, and Yi-Chang Lu. "Traceback Memory Reduction for Three-Sequence Alignment Algorithm with Affine Gap Models." 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) (2022).
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Measuring, visualizing, and diagnosing reference bias with biastools

Published in Genome Biology, 2024

Recent alignment methods aim to reduce reference bias, where reads with non-reference alleles fail to align correctly. However, there is a lack of methods for analyzing reference bias. We present biastools, which measures and categorizes reference bias.

Recommended citation: Lin, Mao-Jan, et al. "Measuring, visualizing, and diagnosing reference bias with biastools." Genome Biology 25.1 (2024): 101.
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IGLoo enables comprehensive analysis and assembly of immunoglobulin heavy-chain loci in lymphoblastoid cell lines using PacBio high-fidelity reads

Published in Cell Reports Methods, 2025

Lymphoblastoid cell lines (LCLs) contain a mixture of germline and somatically recombined haplotypes in the immunoglobulin (IG) gene regions, making them hard to profile and assemble. IGLoo is a toolkit to profile the IG heavy chain (IGH) locus in LCLs with HiFi reads. It can also improve the assembly quality in the IGH locus.

Recommended citation: Lin, Mao-Jan, Ben Langmead, and Yana Safonova. "IGLoo enables comprehensive analysis and assembly of immunoglobulin heavy-chain loci in lymphoblastoid cell lines using PacBio high-fidelity reads." Cell Reports Methods 5(5) (2025): 101033.
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Unmasking human T cell receptor germline diversity: 335 novel alleles identified in 47 Pangenome reference individuals using the gAIRR Suite

Published in Journal of Advanced Research, 2026

Analysis of 47 HPRC individuals with gAIRR Suite identifies 335 novel germline T cell receptor alleles and expands the available reference sequences.

Recommended citation: Yu-Hsuan Yang, Chi-Yuan Yao, Mao-Jan Lin, Kuan-Ta Huang, Yu-Hui Lin, Yi-Hui Huang, I-Hsuan Chiu, Sheng-Kai Lai, Chih-Yeh Chen, Ya-Chien Yang, Chia-Lang Hsu, Jacob Shujui Hsu, Chien-Yu Chen, Pei-Lung Chen. "Unmasking human T cell receptor germline diversity: 335 novel alleles identified in 47 Pangenome reference individuals using the gAIRR Suite." Journal of Advanced Research (2026).
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Minimizing reference bias with an imputed personalized reference

Published in Genome Research, 2026

The impute-first framework builds a personalized reference through imputation before aligning the full read set, reducing reference bias in downstream variant calling.

Recommended citation: Vaddadi, Kavya, Mao-Jan Lin, Sina Majidian, Taher Mun, and Ben Langmead. "Minimizing reference bias with an imputed personalized reference." Genome Research (2026).
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gAIRR-wgs: high-resolution T cell receptor allele typing in biobank-scale whole-genome sequencing data

Published in Briefings in Bioinformatics, 2026

gAIRR-wgs supports high-resolution T cell receptor allele typing from whole-genome sequencing data at biobank scale.

Recommended citation: Huang, Kuan-Ta, Yu-Hsuan Yang, Mao-Jan Lin, Yu-Hui Lin, Sheng-Kai Lai, Ting-Hsuan Chou, Chieh-Yu Lee, Tsung-Kai Hung, Chia-Lang Hsu, Ya-Chien Yang, Chien-Yu Chen, Pei-Lung Chen, and Jacob Shu-Jui Hsu. "gAIRR-wgs: high-resolution T cell receptor allele typing in biobank-scale whole-genome sequencing data." Briefings in Bioinformatics (2026).
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ImpuT2T: Pangenome-Based Patching for Human Genome Assemblies

Preprint on bioRxiv, 2026

ImpuT2T uses a panel of T2T or near-T2T assemblies to scaffold and patch gaps in assemblies generated from HiFi reads.

Recommended citation: Lin, Mao-Jan, Vikram S. Shivakumar, Ben Langmead, and Human Pangenome Reference Consortium. "ImpuT2T: Pangenome-Based Patching for Human Genome Assemblies." bioRxiv (2026).
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talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.