Scientific popular articles on Bioinformatics and Artificial Intelligence:

[1].  熊召平, 刘琦, 郑明月, 蒋华良等, 联邦学习能否打破新药研发的反摩尔定律, 中国计算机学会通讯(CCCF), 2022.

[2].  刘琦#, 人工智能应用于新药研发的范式转变, 知识分子公众号科普, 2018.

[3].  刘琦#, 化学界诞生了一个“AlphaGO", 知识分子公众号科普, 2018.

[4].  刘琦#, 生物信息学研究的思考, 中国计算机学会通讯(CCCF), 2016.

Representative papers in the area of Bioinformatics:

— 2025年度 —

[1]. Yuli Gao et al, Qi Liu#, Weakly-supervised peptide-TCR binding prediction facilitates neoantigen identification, Cell System, Advance Access. 2025.

    [2]. Shaliu Fu et al, Qi Liu#, Benchmarking single-cell multi-modal data integrations, Nature Methods, Advance Access,  2025.

[3]. Yichen Gao et al, Qi Liu#, Causal disentanglement for single-cell representations and controllable counterfactual generation, Nature Communications, Advance Access, 2025.

[4]. Xichen Liao, Qi Liu#, Guohui Chuai#, PrimeNet: rational design of Prime editing pegRNAs by deep learning, Briefings in Bioinformatics, Advance Access, 2025.

[5]. Dongdong Mao et al, Qi Liu#, Gonghui Li#, Heterogeneous driving effect guides personalized tumor treatment targeting N6-methylatedadenine, Cancer Research. Advance Access, 2025.

[6]. Xiaojie Chen et al, Qi Liu#, SpaLinker identifies phenotype-associated spatial tumor microenvironment features by integrating bulk and spatial sequencing data, Cell Genomics. Advances Access, 2025.

[7]. Hao Xu et al, Qi Liu#, Jing-Dong Jackie Han#, Biomedical data and AI, Science China-Life Science. Advance Access, 2025.

[8]. Pengxiang Wang et al, Qi Liu#, Jia Fan#, Xinrong Yang#, Exploring Morphological Heterogeneity of Circulating Tumor Cells: Machine Learning-Based Approach for Cell Identification and Prognostic Implications, Science Bulletin.  Advance Access, 2025.

— 2024年度 —

[1]. Wenhui Li et al, Qi Liu#, Discovering CRISPR-Cas system with self-processing pre-crRNA capability by foundation models, Nature Communications, 2024.

[2]. Zhiting Wei et al, Qi Liu#, PerturBase: a comprehensive database for single-cell perturbation data analysis and visualization, Nucleic Acids Research, 2024.

[3]. Yicheng Gao, Qi Liu#, Delineating the cell types with transcriptional kinetics, Nature Computational Science, 2024.

[4]. Yicheng Gao et al, Qi Liu#, Toward subtask decomposition-based learning and benchmarking for genetic perturbation outcome prediction and beyond, Nature Computational Science, 2024.

[5]. Qi Liu*, Translating “AI for omics” into precision therapy, Medicine Plus, 2024.

[6]. Liangzi Mengfang et al, Qi Liu#, Genomics-guided Representation Learning for Pathologic Pan-cancer Tumor Microenvironment Subtype Prediction, MICCAI, 2024.

[7]. Yicheng Gao et al., Qi Liu#, Unified cross-modality integration and analysis of T-cell receptors and T-cell transcriptomes by low-resource-aware representation learning, Cell Genomics, Advance Access, 2024.

[8]. Yunda Si et al, Qi Liu#, Luonan Chen#, Foundation models in Molecular Biology, Biophysics Reports, Advance Access, 2024.

[9]. Zhang Wei et al, Qi Liu#, Zhouxi Shi#, Qi Dai#, scHybridBERT: integrating gene regulation and cell graph for spatial-temporal dynamics in single-cell clustering. Briefings in Bioinformatics, Advance Access, 2024.

[10]. Fengying Sun et al., Qi Liu#… ShiTie Liu#, Single- Cell Omics: experimental workflow, data analyses and applications, Science China - Life Sciences. Advance Access, 2024.

[11]. Tianyi Ding et al, Qi Liu#, He Zhang #, Inter3D: Capture of TAD reorganization endows variant patterns of gene transcription, Genomics Proteomics & Bioinformatics, Advance Access, 2024.

[12]. Bin Duan et al., Qi Liu#, Multi-slice Spatial Transcriptome Domain Analysis with SpaDo, Genome Biology. Advance Access, 2024.

— 2023年度 —

[1].  Chen Tang et al., Qi Liu#, Personalized tumor combination therapy optimization using the single-cell transcriptome, Genome Medicine. Advance Access, 2023.

[2]. Qinchang Chen et al., Qi Liu#, Genome-wide CRISPR off-target prediction and optimization using RNA-DNA interaction fingerprints, Nature Communications. Advance Access, 2023.

[3]. Yicheng Gao et al., Qi Liu#, Reply to: The pitfalls of negative data bias for the T-cell epitope specificity challenge, Nature Machine Intelligence. Advance Access, 2023.

[4]. Xiaowen Wang et al, Qi Liu#, Qin Liu#, A complete graph-based approach with multi-task learning for predicting synergistic drug combinations, Bioinformatics, Advance Access, 2023.

[5]. Yicheng Gao et al., Qi Liu#, Pan-Peptide Meta Learning for T-Cell Receptor-Antigen Binding Recognition, Nature Machine Intelligence. Advance Access, 2023.

[6]. Qinhu Zhang et al., Qi Liu#, Deshuang Huang#, Computational prediction and characterization of cell-type-specific and shared binding sites, Bioinformatics. Advance Access, 2023.

— 2022年度 —

[1].Gongchen Zhang et al., Qi Liu#, Systematic exploration of optimized base-editing gRNA design and pleiotropic effects with BExplorer, Genomics Proteomics & Bioinformatics. Advance Access, 2022.

[2]. Shaoqi Chen et al, Qi Liu#, Privacy-preserving integration of multiple institutional data for single-cell type identification with scPrivacy, Science China-Life Sciences, Advance Access, 2022.

[3]. Zhiting Wei et al.,Qi Liu#, DrSim: Similarity learning for transcriptional phenotypic drug discovery, Genomics Proteomics & Bioinformatics. Advance Access, 2022.

[4]. Qinchang Chen et al, Qi Liu#, Toward a molecular mechanism-based prediction of CRISPR-Cas9 targeting effects, Science Bulletin, Advance Access, 2022.

[5]. Qinhu Zhang et al, Qi Liu#, Deshuang Huang#, Base-resulotion prediction of transcription  factor binding signals by a deep learning framework, Plos Computational Biology, Advance Access, 2022.

[6]. Dongyu Xue et al, Qi Liu#, X-MOL: large-scale pre-training for molecular understanding and diverse molecular analysis, Science Bulletin, Advance Access, 2022.

[7].Gaoyang Li et al, Qi Liu#, A deep generative model for multi-view profiling of single cell RNA-seq and ATAC-seq data, Genome Biology, Advance Access, 2022.

— 2021年度 —

[1]. Yukang Gong et al, Qi Liu#, DeepReac+: Deep active learning for quantitative modeling of organic chemical reactions, Chemical Science, Advance Access, 2021.

[2]. Xiaowen Wang, Qi Liu#, Qin Liu#, PRODeepSyn: integrating protein-protein interaction network with omics data to predict anticancer synergistic drug combinations, Briefings in Bioinformatics, Advance Access, 2021.

[3. Tengbo Zhang et al, Qi Liu#, Ping Wang#, iCRISEE: an integrative  analysis of CRISPR screen by reducing false positive hits, Briefings in Bioinformatics, Advance Access, 2021.

[4]. Biyu Zhang et al, Qi Liu#, The tumor therapy landscape of synthetic lethality, Nature Communications, Advance Access, 2021.

[5]. Bin Duan et al, Qi Liu#, Integrating multiple references for single cell assignment, Nucleic Acids Research, Advance Access, 2021.

[6]. Qinhu Zhang et al, Qi Liu#, Deshuang Huang#, Locating transcription factor binding sites by Fully Convolutional Neural Network, Briefings in Bioinformatics, Advance Access, 2021.

[7] . Xiangyong Li et al, Qi Liu#, Hao Ye#, Benchmark HLA genetyping and clarifying HLA impact on survival in tumor immunotherapy,  Molecular Oncology, Advance Access, 2021.

— 2020年度 —

[1]. Bin Duan et al, Qi Liu#, Learning for single cell assignment, Science Advances, Advance Access, 2020. (入选2020年中国生物信息学应用十大进展 )

[2]. Jifang Yan et al, Qi Liu#, Benchmarking and integrating CRISPR off-target detection and prediction, Nucleic Acids Research, Advance Access, 2020.

[3]. Shaoqi Chen et al, Qi Liu#, FL-QSAR: a federated learning based QSAR prototype for collaborative drug discovery, Bioinformatics, Advance Access, 2020.

[4]. Zhiting Wei et al, Qi Liu#, iDMer: an integrative and Mechanism-driven response system for identifying compound interventions for sudden virus break, Briefings in Bioinformatics, Advance Access, 2020.

— 2019年度 —

[1]. Zhiting Wei et al, Qi Liu#, The landscape of tumor fusion neoantigens: a pan-cancer analysis, iScience, Advance Access, 2019. 

[2]. Chi Zhou et al, Qi Liu#, pTuneos: prioritizing Tumor neoantigens from next-generation sequencing data, Genome Medicine, Advance Access, 2019. 

[3]. Han Zhao et al, Qi Liu#, MetaMed: Linking microbiota functions with medicine therapeutics, mSystems, Advance Access, 2019. 

[4]. Chi Zhou et al, Qi Liu#, Towards in silico identification of tumor neoantigens in immunotherapy, Trends in Molecular Medicine, Advance Access, 2019. (Selected as one of the Best Review Article in Cell Trends 2019! Report Link )

[5]. Yuli Gao et al, Qi Liu#, Data Imbalance in CRISPR off-target prediction, Briefings in Bioinformatics, Advance Access, 2019. 

[6]. Bin Duan et al, Qi Liu#, Model based Understanding of Single-cell CRISPR Screening, Nature Communications, Advance Access, 2019. (入选2019年中国生物信息学应用十大进展 )

[7]. Chenyu Zhu et al, Qi Liu#, C3: Consensus Cancer Driver Gene Caller, Genomics, Proteomics & Bioinformatics, Advance Access, 2019. 

— 2018年度 —

[1]. Dongyu Xue et al, Qi Liu#, Advances and challenges in deep generative models for de novo molecule generation, WIREs Computational Molecule Science, Advance Access, 2018. 

[2]. Guohui Chuai et al, Qi Liu#, DeepCRISPR: optimized CRISPR guide RNA design by deep learning, Genome Biology, Advance Access, 2018.
        (F1000 Recommendation)

— 2017年度 —

[1]. Ke Chen et al, Qi Liu#, Towards in-silico prediction of the immune-checkpoint blockade response, Trends in Pharmacological Sciences, Advance Access, 2017. (Most read article in the latest 30 days after publication!)
 

[2]. Jifang Yan et al, Qi Liu#, Benchmarking CRISPR on-target sgRNA design, Briefings in Bioinformatics, Advance Access, 2017. 

[3]. Jifang Yan et al, Qi Liu#, Metatopics: an integration tool to analyze microbial community profile by topic model,  BMC Genomics, Advance Access, 2017. 

— 2016年度 —

[1]. Guohui Chuai, Jifang Yan et al, Qi Liu#, Deciphering relationship between microhomology and in-frame mutation occurence in human CRISPR-based gene knockout, Molecular Therapy-Nucleic Acids, Advance Access, 2016. (Featured Article ! )

[2].  Jian Ma et al, Qi Liu#, Han Xu# and X. Shirley Liu#, CRISPR-DO: A genome-wide CRISPR designer and optimizer for multiple species, Bioinformatics, Advance Access, 2016.
 

[3]. Guo-hui Chuai, Qi-Long Wang, Qi Liu#, In-silico meets in-vivo: towards computational CRISPR-based sgRNA design, Trends in Biotechnology, Advance Access, 2016. (Most read article in the latest 30 days after publication!)

— 2015年度及以前—

[1]. Haiping Wang, Quanquan Gu,Jia Wei, Zhiwei Cao, Qi Liu#, Mining drug-disease relationships as a complement to medical genetics-based drug repositioning: Where a recommendation system meets GWAS, Clinical Pharmacology & Therapeutics, Advance Access, 2015.
 

[2]. Yi Sun, Zhen Sheng, Chao Ma, Kailin Tang, Ruixin Zhu, Zhuanbin Wu, Ruling Shen, Jun Feng, Dingfeng Wu, Danyi Huang, Dandan Huang, Jian Fei#, Qi Liu#, Zhiwei Cao#, Combining genomic and network characteristics for extended capability in predicting synergistic drugs for cancer, Nature Communications, Advance Access, 2015.

[3]. WZ, LJ, KT, HP W, RX Z, WJ, ZW, Qi Liu#, When drug discovery meets web searching: learning to rank for ligand-based virtual screening, Journal of Cheminformatics, Advance Access, 2015. 

[4]. Haoqi Sun, Haiping Wang, Ruixin Zhu, Kailin Tang, Qin Gong, Juan Cui, Zhiwei Cao, Qi Liu#, iPEAP: integrating multiple omics and genetic data for pathway enrichment analysis, Bioinformatics, Advance Access online, 2013.

[5]. Yi Sun, Ruixin Zhu, Hao Ye, Jing Zhao, Yujia Chen, Qi Liu# and Zhiwei Cao#, Towards a bioinformatics analysis of anti-Alzheimer’s herbal medicines from a target network perspective, Briefings in Bioinformatics, May;14(3):327-43, 2012.

[6]. Qi Liu, Han Zhou, Ruixin Zhu, Ying Xu and Zhiwei Cao, Reconsideration of in-silico siRNA design from a perspective of heterogeneous data integration: problems and solutions, Briefings in Bioinformatics, Advance Access, 2012.

[7]. Hong Kang, Zhen Sheng, Ruixin Zhu, Qi Huang, Qi Liu# and Zhiwei Cao#, A virtual drug screen schema based on multi-view similarity integration and ranking aggregation, 26;52(3):834-43, J. Chem. Inf. Model. 2012.

[8]. Qi Liu, V. Olman, Huiqing Liu, Xiuzi Ye, Shilun Qiu, Ying Xu, RNACluster : an integrated tool for RNA secondary structure comparison and clustering, Journal of Computational Chemistry, 26(9), 1517-1526, 2008.


Representative papers in the area of Machine Learning:

[1]. Xiaoxiao Shi, Qi Liu, Wei Fan, and Philip S. Yu, Transfer across Completely Different Feature Spaces via Spectral Embedding, IEEE Transactions on Knowledge and Data Engineering (TKDE),  vol. 25, no. 4, pp. 906-918, 2011.

[2]. Xiaoxiao Shi, Qi Liu, Wei Fan, Philip Yu, and Ruixin Zhu, Transfer Learning on Heterogenous Feature Spaces via Spectral Transformation, IEEE International Conference on Data Mining (ICDM 2010),1049-1054, 2010.

[3]. Xiao Xiao shi, Qi Liu, Wei Fan,Qiang Yang, Philip S.Yu. Predictive Modeling with heterogeneous Sources, the 2010 SIAM International Conference on Data Mining (SDM’2010), 814-825, 2010.
 

 

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