Hi, I am Jiecong Lin, a joint postdoctoral research fellow currently affiliated with Harvard Medical School/MGH/BCH and The University of Hong Kong. I am honored and humbled by the opportunity to learn from and work with Prof. Luca Pinello (MGH), Prof. Daniel Bauer (BCH), and Prof. Ruibang Luo (HKU), who kindly supervise my research activities. I'm incredibly fortunate to work alongside so many talented researchers in both computational and experimental labs.

My research in computational biology primarily centers on developing advanced deep learning models to unlock gene regulation from genomic sequences. Additionally, I specialize in creating computational models for evaluating off-target effects of CRISPR, a revolutionary genome editing technology..During my incredible four-year journey as a PhD student at the Bioinformatics Lab in City University of Hong Kong, I had the privilege of being supervised by Prof. Ka-Chun Wong. In 2021, I successfully completed my PhD, solidifying my expertise and passion for this field. For a detailed overview of my academic and professional achievements, please refer to my curriculum vitae and my google scholar page.

• Jiecong Lin, Ruibang Luo*, and Luca Pinello*. "EPInformer: a scalable deep learning framework for gene expression prediction by integrating promoter-enhancer sequences with multimodal epigenomic data." bioRxiv (2024): 2024-08. [paper][code]

• Jiecong Lin^, My Anh Nguyen^, Linda Y. Lin^, Jing Zeng, Archana Verma, Nola R. Neri, Lucas Ferreira da Silva, Adele Mucci, Scot Wolfe, Kit L Shaw, Kendell Clement, Christian Brendel, Luca Pinello*, Danilo Pellin*, and Daniel E. Bauer*. "Scalable assessment of genome editing off-targets associated with genetic variants." bioRxiv (2024): 2024-07. [paper][code]

• Fuzhou Wang, Jiecong Lin, Hamid Alinejad-Rokny, Wenjing Ma, Lingkuan Meng, Lei Huang, Jixiang Yu, Nanjun Chen, Yuchen Wang, Zhongyu Yao, Weidun Xie, Xiangtao Li, Ka-Chun Wong*. "Unveiling multi-scale architectural features in single-cell Hi-C data using scCAFE." Advanced Science (2025)

• Lingkuan Meng, Jiecong Lin, Ke Cheng, Kui Xu, Hongyan Sun, and Ka-Chun Wong*. "UniPTM: Multiple PTM site prediction on full-length protein sequence." bioRxiv (2024): 2024-08.

• Chen, Xingjian, Jiecong Lin, Yuchen Wang, Weitong Zhang, Weidun Xie, Zetian Zheng, and Ka-Chun Wong*. "HE2Gene: image-to-RNA translation via multi-task learning for spatial transcriptomics data." Bioinformatics 40, no. 6 (2024).

• Kathleen A Christie, Jimmy A Guo, Rachel A Silverstein, Roman M Doll, Megumu Mabuchi, Hannah E Stutzman, Jiecong Lin, Linyuan Ma, Russell T Walton, Luca Pinello, G Brett Robb, and Benjamin P Kleinstiver*. "Precise DNA cleavage using CRISPR-SpRYgests." Nature biotechnology 41, no. 3 (2023): 409-416.

• Samuele Cancellieri^, Jing Zeng^, Linda Yingqi Lin^, Manuel Tognon, My Anh Nguyen, Jiecong Lin, Nicola Bombieri, Stacy A Maitland, Marioara-Felicia Ciuculescu, Varun Katta, Shengdar Q Tsai, Myriam Armant, Scot A Wolfe, Rosalba Giugno*, Daniel E Bauer*, and Luca Pinello*. "Human genetic diversity alters off-target outcomes of therapeutic gene editing." Nature genetics 55, no. 1 (2023): 34-43.

• Fuzhou Wang, Hamid Alinejad‐Rokny, Jiecong Lin, Tingxiao Gao, Xingjian Chen, Zetian Zheng, Lingkuan Meng, Xiangtao Li, and Ka‐Chun Wong*. "A Lightweight Framework For Chromatin Loop Detection at the Single‐Cell Level." Advanced Science 10, no. 33 (2023): 2303502.

• Jiecong Lin, Xingjian Chen, and Ka-Chun Wong*. "An artificial intelligence approach for gene editing off-target quantification: Convolutional self-attention neural network designs and considerations." Statistics in Biosciences 15, no. 3 (2023): 657-668.

• Lei Huang, Jiecong Lin, Rui Liu, Zetian Zheng, Lingkuan Meng, Xingjian Chen, Xiangtao Li, and Ka-Chun Wong*. "CoaDTI: multi-modal co-attention based framework for drug–target interaction annotation." Briefings in bioinformatics 23, no. 6 (2022): bbac446.

• Fuzhou Wang, Tingxiao Gao, Jiecong Lin, Zetian Zheng, Lei Huang, Muhammad Toseef, Xiangtao Li, and Ka-Chun Wong*. "GILoop: robust chromatin loop calling across multiple sequencing depths on Hi-C data." Iscience 25, no. 12 (2022).

• Jiecong Lin, Lei Huang, Xingjian Chen, Shixiong Zhang, and Ka-Chun Wong*. "DeepMotifSyn: a deep learning approach to synthesize heterodimeric DNA motifs." Briefings in Bioinformatics 23, no. 1 (2022): bbab334.

• Shixiong Zhang, Xiangtao Li, Qiuzhen Lin, Jiecong Lin, and Ka-Chun Wong*. "Uncovering the key dimensions of high-throughput biomolecular data using deep learning." Nucleic acids research 48, no. 10 (2020): e56-e56.

• Jiecong Lin, Zhaolei Zhang, Shixiong Zhang, Junyi Chen, and Ka‐Chun Wong*. "CRISPR‐Net: a recurrent convolutional network quantifies CRISPR off‐target activities with mismatches and indels." Advanced science 7, no. 13 (2020): 1903562.

• Ka-Chun Wong*, Jiecong Lin, Xiangtao Li, Qiuzhen Lin, Cheng Liang, and You-Qiang Song. "Heterodimeric DNA motif synthesis and validations." Nucleic acids research 47, no. 4 (2019): 1628-1636.

• Jiecong Lin, and Ka-Chun Wong*. "Off-target predictions in CRISPR-Cas9 gene editing using deep learning." Bioinformatics (ECCB 2018 special issue) 34, no. 17 (2018): i656-i663.