2025

1.Wentao Gao, Sui Wang, Tao Jiang , et al., Chromosome-scale and haplotype-resolved genome assembly of Populus trichocarpa, Horticulture Research, 2025.

2.Zhang T, Sun H, Wu Z, Zhao Z, Zhao X, Zhang H, Gao B, Wang G. GAADE: identification spatially variable genes based on adaptive graph attention network [J]. Briefings in Bioinformatics, 2025, 26(1): bbae669.

3.Gao W, Wang S, Jiang T, Hu H, Gao R, Zhou M, Wang G. Chromosome-scale and haplotype-resolved genome assembly of Populus trichocarpa [J]. Horticulture Research, 2025: uhaf012.

4.Hao G, Fan Y, Yu Z, Su Y, Zhu H, Wang F, Chen X, Yang Y, Wang G, Wong K-c. Topological identification and interpretation for single-cell epigenetic regulation elucidation in multi-tasks using scAGDE [J]. Nature Communications, 2025, 16(1): 1691.

5.Zhang T, Wu Z, Li L, Ren J, Zhang Z, Zhang J, Wang G. CellGAT: A GAT-Based Method for Constructing a Cell Communication Network Integrating Multiomics Information [J]. Biomolecules, 2025, 15(3): 342.

6.Zhang T, Zhao Z, Ren J, Zhang Z, Zhang H, Wang G. cfDiffusion: diffusion-based efficient generation of high quality scRNA-seq data with classifier-free guidance [J]. Briefings in Bioinformatics, 2025, 26(1): bbaf071.

7.Qiu S, Liu J, Guo J, Zhang Z, Guo Y, Hu Y. COVID-19 infection and longevity: an observational and mendelian randomization study. J Transl Med. 2025 Mar 6;23(1):283. doi: 10.1186/s12967-024-05932-y. PMID: 40050903; PMCID: PMC11887240.

2024

1.Rui Han, Xu Wang, Xuan Wang, Yadong Wang, Junyi Li, AFSC: A self-supervised augmentation-free spatial clustering method based on contrastive learning for identifying spatial domains, Computational and Structural Biotechnology Journal, Volume 23, 2024, Pages 3358-3367, ISSN 2001-0370, https://doi.org/10.1016/j.csbj.2024.09.005.

2.K. Cen, Z. Xing, X. Wang, Y. Wang and J. Li, "circ2DGNN: circRNA-Disease Association Prediction via Transformer-Based Graph Neural Network," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 21, no. 6, pp. 2556-2567, Nov.-Dec. 2024, doi: 10.1109/TCBB.2024.3488281.

3.Lexiang Wang, Jingli Zhou, Xuan Wang, Yadong Wang, Junyi Li, MCDHGN: heterogeneous network-based cancer driver gene prediction and interpretability analysis, Bioinformatics, Volume 40, Issue 6, June 2024, btae362, https://doi.org/10.1093/bioinformatics/btae362

4.Yue Liu, Yuhuan Zhou, Xiumei Hu, Wuri Le-Ge, Haoyan Wang, Tao Jiang, Junyi Li, Yang Hu, Yadong Wang, DIRMC: a database of immunotherapy-related molecular characteristics, Database, Volume 2024, 2024, baae032, https://doi.org/10.1093/database/baae032

5.Zhang L, Wang S, Wang Y, Zhao T. HBFormer: a single-stream framework based on hybrid attention mechanism for identification of human-virus protein-protein interactions. Bioinformatics. 2024 Nov 28;40(12):btae724. doi: 10.1093/bioinformatics/btae724. PMID: 39673490; PMCID: PMC11648999.

6.Guo H, Zhang L, Cui X, Cheng L, Zhao T, Wang Y. SCancerRNA: Expression at the Single-cell Level and Interaction Resource of Non-coding RNA Biomarkers for Cancers. Genomics Proteomics Bioinformatics. 2024 Sep 13;22(3):qzae023. doi: 10.1093/gpbjnl/qzae023. PMID: 39341795.

7.Liu J , Zhao X , Jia Y ,et al.HGGN: Prediction of microRNA-Mediated drug sensitivity based on interpretable heterogeneous graph global-attention network[J].Future Generation Computer Systems, 2024, 160:274-282.DOI:10.1016/j.future.2024.06.010.

8.Yuran J , Hongchao D , Linhao L ,et al.xQTLatlas: a comprehensive resource for human cellular-resolution multi-omics genetic regulatory landscape[J].Nucleic Acids Research, 2024(D1):D1.DOI:10.1093/nar/gkae837.

9.Jiang T, Guo H, Liu Y, Li G, Cui Z, Cui X, Liu Y, Li Y, Zhang A, Cao S, Zhao T, Juan L, Kong W, Chen M, Liu D, Liu H, Zhang Y, Xu K, Wang Y, He M, Guo J, Lu M, Chen J, Zhao X, Zhao G, Dang S, Chen C, Wu X, Qin Q, Li Y, Shen H, Jin L, Liu B, Chen X, Zhao Y, Wang Y. A comprehensive genetic variant reference for the Chinese population. Sci Bull (Beijing). 2024 Dec 30;69(24):3820-3825. doi: 10.1016/j.scib.2024.06.017. Epub 2024 Jun 18. PMID: 38945749.

10.Qiuhao Chen, Liyuan Zhang, Yaojia Liu, Zhonghao Qin, Tianyi Zhao, PUTransGCN: identification of piRNA–disease associations based on attention encoding graph convolutional network and positive unlabelled learning, Briefings in Bioinformatics, Volume 25, Issue 3, May 2024, bbae144, https://doi.org/10.1093/bib/bbae144

11.Cui X , Lin Q , Chen M ,et al.Long-read sequencing unveils novel somatic variants and methylation patterns in the genetic information system of early lung cancer[J].Computers in Biology and Medicine, 2024, 171.DOI:10.1016/j.compbiomed.2024.108174.

12.Zhang C, Zang T, Zhao T. KGE-UNIT: toward the unification of molecular interactions prediction based on knowledge graph and multi-task learning on drug discovery. Brief Bioinform. 2024 Jan 22;25(2):bbae043. doi: 10.1093/bib/bbae043. PMID: 38348746; PMCID: PMC10939374.

13.Xin Li, Yadong Liu, Zhongbo Yang, Yadong Wang and Tao Jiang, Comprehensive Benchmarking of Genotype Imputation Tools Using a Large-Scale Chinese Reference Panel, BIBM2024, pp.5218-5223.

14.Zhongbo Yang, Zhenhao Lu, Xin Li, Tao Jiang, et al., Comprehensive evaluation of haplotype phasing tools with different strategies across diverse sequence technologies, BIBM2024, pp.653-658.

15.Tao Jiang, Zuji Zhou, Zhendong Zhang, Shuqi Cao, Yadong Wang, Yadong Liu, MEHunter: transformer-based mobile element variant detection from long reads, Bioinformatics, Volume 40, Issue 9, September 2024, btae557.

16.Miao Cui, Yadong Liu, Xian Yu, Hongzhe Guo, Tao Jiang, Yadong Wang, Bo Liu, miniSNV: accurate and fast single nucleotide variant calling from nanopore sequencing data, Briefings in Bioinformatics, Volume 25, Issue 6, November 2024, bbae473.

17.姜涛, 刘博, 王亚东. 构建高精度中国人基因组变异图谱, 为"健康中国"建设奠定关键科学基础[J]. 中国科技成果, 2024, 25(12):52-54. DOI:10.3772/j.issn.1009-5659.2024.12.020.

18.吕俊增，曹舒淇，姜涛，基于大规模人群变异的中国人参考基因组构建方法[J/OL]. 生物信息学, 1-9 [2024-09-02].

19.Tao Jiang, Hongzhe Guo, Yadong Liu, Gaoyang Li, Zhe Cui, Xinran Cui, Yue Liu, Yang Li, Anqi Zhang, Shuqi Cao, Tianyi Zhao, Liran Juan, Weize Kong, Ming Chen, Dianming Liu, Hongri Liu, Yixiao Zhang, Kelin Xu, Yongjun Wang, Meian He, Jiancheng Guo, Ming Lu, Jun Chen, Xing Zhao, Genming Zhao, Shaonong Dang, Chao Chen, Xiaojian Wu, Qiyuan Qin, Yixue Li, Hongbing Shen, Li Jin, Bo Liu, Xingdong Chen, Yuhong Zhao, Yadong Wang, A comprehensive genetic variant reference for the Chinese population, Science Bulletin, 2024.

20.Heng Hu, Runtian Gao, Wentao Gao, Bo Gao, Zhongjun Jiang, Murong Zhou, Guohua Wang, Tao Jiang, SVDF: enhancing structural variation detect from long-read sequencing via automatic filtering strategies, Briefings in Bioinformatics, Volume 25, Issue 4, July 2024, bbae336, 2024.

21.Zhendong Zhang, Yue Liu, Xin Li, Yadong Liu, Yadong Wang, Tao Jiang, HapKled: a haplotype-aware structural variant calling approach for Oxford Nanopore sequencing data. Frontiers in Genetics, Volume 15, 2024.

22.Yue Liu, Yuhuan Zhou, Xiumei Hu, Wuri Le-Ge, Haoyan Wang, Tao Jiang, Junyi Li, Yang Hu, Yadong Wang, DIRMC: a database of immunotherapy-related molecular characteristics. Database, Volume 2024, 2024, baae032.

23.Z Zhang, T Jiang, G Li, S Cao, Y Liu, B Liu, Y Wang. (2024). Kled: an ultra-fast and sensitive structural variant detection tool for long-read sequencing data. Briefings in Bioinformatics 25 (2), bbae049.

24.Xinran Cui, Qingyan Lin, Ming Chen, Yidan Wang, Yiwen Wang, Yadong Wang, Jiang Tao, Honglei Yin, Tianyi Zhao. Long-read sequencing unveils novel somatic variants and methylation patterns in the genetic information system of early lung cancer. (2024). Computers in Biology and Medicine 171(10299):108174.

25.Zhang T, Zhang Z, Li L, Dong B, Wang G, Zhang D. GTAD: a graph-based approach for cell spatial composition inference from integrated scRNA-seq and ST-seq data [J]. Briefings in Bioinformatics, 2024, 25(1): bbad469.

26.Wang F, Liu C, Li J, Yang F, Song J, Zang T, Yao J, Wang G. SPDB: a comprehensive resource and knowledgebase for proteomic data at the single-cell resolution [J]. Nucleic Acids Research, 2024, 52(D1): D562-D71.

27.Zixuan E, Qiao G, Wang G, Li Y. GSL-DTI: Graph Structure Learning Network for Drug-Target Interaction Prediction [J]. Methods, 2024.

28.Dong B, Liu Z, Xu D, Hou C, Dong G, Zhang T, Wang G. SERT-StructNet: Protein secondary structure prediction method based on multi-factor hybrid deep model [J]. Computational and Structural Biotechnology Journal, 2024, 23: 1364-75.

29.Zhu Z, Ma X, Wang W, Dong S, Wang K, Wu L, Luo G, Wang G, Li S. Boosting knowledge diversity, accuracy, and stability via tri-enhanced distillation for domain continual medical image segmentation [J]. Medical Image Analysis, 2024: 103112.

30.Miao Y, Sun Z, Ma C, Lin C, Wang G, Yang C. VirGrapher: a graph-based viral identifier for long sequences from metagenomes [J]. Briefings in Bioinformatics, 2024, 25(2): bbae036.

31.Ke J, Zhao J, Li H, Yuan L, Dong G, Wang G. Prediction of protein N-terminal acetylation modification sites based on CNN-BiLSTM-attention model [J]. Computers in Biology and Medicine, 2024, 174: 108330.

32.Zhang T, Zhang Z, Li L, Ren J, Wu Z, Gao B, Wang G. GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues [J]. Biomolecules, 2024, 14(4): 436.

33.Zhang T, Wu Z, Li L, Ren J, Zhang Z, Wang G. CPPLS-MLP: a method for constructing cell–cell communication networks and identifying related highly variable genes based on single-cell sequencing and spatial transcriptomics data [J]. Briefings in Bioinformatics, 2024, 25(3): bbae198.

34.Zhang T, Ren J, Li L, Wu Z, Zhang Z, Dong G, Wang G. scZAG: Integrating ZINB-Based Autoencoder with Adaptive Data Augmentation Graph Contrastive Learning for scRNA-seq Clustering [J]. International Journal of Molecular Sciences, 2024, 25(11): 5976.

35.Bian J, Lu H, Dong G, Wang G. Hierarchical multimodal self-attention-based graph neural network for DTI prediction [J]. Briefings in Bioinformatics, 2024, 25(4).

36.Yang Q, Xu L, Dong W, Li X, Wang K, Dong S, Zhang X, Yang T, Jiang F, Zhang B. HLAIImaster: a deep learning method with adaptive domain knowledge predicts HLA II neoepitope immunogenic responses [J]. Briefings in Bioinformatics, 2024, 25(4).

37.Hu H, Gao R, Gao W, Gao B, Jiang Z, Zhou M, Wang G, Jiang T. SVDF: enhancing structural variation detect from long-read sequencing via automatic filtering strategies [J]. Briefings in Bioinformatics, 2024, 25(4).

38.Wang J, Sun Z, Wang G, Miao Y. TransGINmer: Identifying viral sequences from metagenomes with self-attention and Graph Isomorphism Network [J]. Future Generation Computer Systems, 2024.

39.Liu Z, Liang Y, Wang G, Zhang T. scLEGA: an attention-based deep clustering method with a tendency for low expression of genes on single-cell RNA-seq data [J]. Briefings in Bioinformatics, 2024, 25(5).

40.Miao Y, Sun Z, Lin C, Gu H, Ma C, Liang Y, Wang G. DeePhafier: a phage lifestyle classifier using a multilayer self-attention neural network combining protein information [J]. Briefings in Bioinformatics, 2024, 25(5).

41.Liu Q, Zhang D, Wang D, Wang G, Wang Y. Automatically detecting anchor cells and clustering for scRNA-seq data using scTSNN [J]. IEEE Journal of Biomedical and Health Informatics, 2024.

42.Dong B, Liu Z, Xu D, Hou C, Niu N, Wang G. Impact of Multi-Factor Features on Protein Secondary Structure Prediction [J]. Biomolecules, 2024, 14(9): 1155.

43.Teng Z, Li Y, Tian Z, Liang Y, Wang G. Drug repositioning by collaborative learning based on graph convolutional inductive network [J]. Future Generation Computer Systems, 2025, 162: 107491.

44.Qiao G, Wang G, Li Y. Causal Enhanced Drug-Target Interaction Prediction based on Graph Generation and Multi-Source Information Fusion [J]. Bioinformatics, 2024: btae570.

45.Xie X, Gui L, Qiao B, Wang G, Huang S, Zhao Y, Sun S. Deep learning in template-free de novo biosynthetic pathway design of natural products [J]. Briefings in Bioinformatics, 2024, 25(6): bbae495.

46.Liu C, Zhang Y, Liang Y, Zhang T, Wang G. DrugReSC: targeting disease-critical cell subpopulations with single-cell transcriptomic data for drug repurposing in cancer [J]. Briefings in Bioinformatics, 2024, 25(6): bbae490.

47.Xu R, Li D, Yang W, Wang G, Li Y. Improving ncRNA family prediction using Multi-Modal contrastive learning of sequence and structure [J]. Bioinformatics, 2024: btae640.

48.Zhang T, Zhang H, Ren J, Wu Z, Zhao Z, Wang G. scDRMAE: integrating masked autoencoder with residual attention networks to leverage omics feature dependencies for accurate cell clustering [J]. Bioinformatics, 2024, 40(10): btae599.

49.Dong B, Su H, Xu D, Hou C, Liu Z, Niu N, Wang G. ILMCNet: A Deep Neural Network Model That Uses PLM to Process Features and Employs CRF to Predict Protein Secondary Structure [J]. Genes, 2024, 15(10): 1350.

50.Zhang H-M, Wang G-H, Sun S-W, Yuan L. Advancing prognostic precision in gastric cancer with an immunoinflammatory index [J]. World Journal of Gastroenterology, 2024, 30(44): 4754.

51.Zhang T, Zhang X, Wu Z, Ren J, Zhao Z, Zhang H, Wang G, Wang T. VGAE-CCI: variational graph autoencoder-based construction of 3D spatial cell–cell communication network [J]. Briefings in Bioinformatics, 2025, 26(1): bbae619.

52.Xu L, Yang Q, Dong W, Li X, Wang K, Dong S, Zhang X, Yang T, Luo G, Liao X. Meta learning for mutant HLA class I epitope immunogenicity prediction to accelerate cancer clinical immunotherapy [J]. Briefings in Bioinformatics, 2025, 26(1): bbae625

53.Guo Y, Ma G, Wang Y, Lin T, Hu Y, Zang T. Causal associations and shared genetic etiology of neurodegenerative diseases with epigenetic aging and human longevity. Aging Cell. 2024 Nov;23(11):e14271. doi: 10.1111/acel.14271. Epub 2024 Sep 19. PMID: 39300745; PMCID: PMC11561668.

54.Sun Y, Guo J, Liu Y, Wang N, Xu Y, Wu F, Xiao J, Li Y, Wang X, Hu Y, Zhou Y. METnet: A novel deep learning model predicting MET dysregulation in non-small-cell lung cancer on computed tomography images. Comput Biol Med. 2024 Mar;171:108136. doi: 10.1016/j.compbiomed.2024.108136. Epub 2024 Feb 13. PMID: 38367451.

55.Sun M, Yang H, Hu Y, Fan J, Duan M, Ruan J, Li S, Xu Y, Han Y. Differential white blood cell count and epigenetic clocks: a bidirectional Mendelian randomization study. Clin Epigenetics. 2024 Aug 27;16(1):118. doi: 10.1186/s13148-024-01717-8. PMID: 39192327; PMCID: PMC11351201.

56.Gao S, Wang T, Han Z, Hu Y, Zhu P, Xue Y, Huang C, Chen Y, Liu G. Interpretation of 10 years of Alzheimer's disease genetic findings in the perspective of statistical heterogeneity. Brief Bioinform. 2024 Mar 27;25(3):bbae140. doi: 10.1093/bib/bbae140. PMID: 38711368; PMCID: PMC11074593.

57.Qiu S, Sun M, Xu Y, Hu Y. Integrating multi-omics data to reveal the effect of genetic variant rs6430538 on Alzheimer's disease risk. Front Neurosci. 2024 Mar 18;18:1277187. doi: 10.3389/fnins.2024.1277187. PMID: 38562299; PMCID: PMC10982421.

58.Qiu S, Sun Y, Guo J, Zhang Y, Hu Y. Genome-wide analysis reveals extensive genetic overlap between childhood phenotypes and later-life type 2 diabetes. Comput Biol Med. 2024 Mar;171:108065. doi: 10.1016/j.compbiomed.2024.108065. Epub 2024 Jan 29. PMID: 38387379.

2023

1.Peishun Jiao, Beibei Wang, Xuan Wang, Bo Liu, Yadong Wang, Junyi Li, Struct2GO: protein function prediction based on graph pooling algorithm and AlphaFold2 structure information, Bioinformatics, Volume 39, Issue 10, October 2023, btad637, https://doi.org/10.1093/bioinformatics/btad637

2.Xiaoshuai Zhang, Huannan Guo, Fan Zhang, Xuan Wang, Kaitao Wu, Shizheng Qiu, Bo Liu, Yadong Wang, Yang Hu, Junyi Li, HNetGO: protein function prediction via heterogeneous network transformer, Briefings in Bioinformatics, Volume 24, Issue 6, November 2023, bbab556, https://doi.org/10.1093/bib/bbab556

3.L. Du, R. Han, B. Liu, Y. Wang and J. Li, "ScCCL: Single-Cell Data Clustering Based on Self-Supervised Contrastive Learning," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 20, no. 3, pp. 2233-2241, 1 May-June 2023, doi: 10.1109/TCBB.2023.3241129

4.Yan, P.; Liu, Y.; Jia, Y.; Zhao, T. Deep Learning and Machine Learning Applications in Biomedicine. Appl. Sci. 2024, 14, 307. https://doi.org/10.3390/app14010307

5.Li S , Ma J , Zhao T ,et al.CellContrast: Reconstructing Spatial Relationships in Single-Cell RNA Sequencing Data via Deep Contrastive Learning[J]. 2023.DOI:10.1101/2023.10.12.562026.

6.Jia Y, Liu J, Chen L, Zhao T, Wang Y. THItoGene: a deep learning method for predicting spatial transcriptomics from histological images. Brief Bioinform. 2023 Nov 22;25(1):bbad464. doi: 10.1093/bib/bbad464. PMID: 38145948; PMCID: PMC10749789.

7.Li W, Li G, Sun Y, Zhang L, Cui X, Jia Y, Zhao T. Prediction of SARS-CoV-2 Infection Phosphorylation Sites and Associations of these Modifications with Lung Cancer Development. Curr Gene Ther. 2024;24(3):239-248. doi: 10.2174/0115665232268074231026111634. PMID: 37957848.

8.Guo H, Zhao T. Multiple mutations of IFITM3 are associated with COVID-19 susceptibilityregulation function of IFITM3 in COVID-19. J Infect. 2023 Jun;86(6):614-616. doi: 10.1016/j.jinf.2023.02.032. Epub 2023 Feb 24. PMID: 36841343; PMCID: PMC9951032.

9.Li S, Hsu C, Zhao T, He L. Editorial: Leveraging machine learning for omics-driven biomarker discovery. Front Mol Biosci. 2023 Jan 9;9:1119644. doi: 10.3389/fmolb.2022.1119644. PMID: 36699701; PMCID: PMC9868145.

10.P Meng, G Wang, H Guo, T Jiang, Identifying cancer driver genes using a two-stage random walk with restart on a gene interaction network. (2023). Computers in Biology and Medicine 158, 106810.

11.Yadong Liu, Zhenhao Lu, Zhongyu Liu, Hongzhe Guo, Yadong Wang, and Tao Jiang, Comprehensive evaluation of RNA-seq alignment methods based on long-read sequencing data. BIBM2023.

12.Tao Jiang, Shiqi Liu, Hongzhe Guo. Reply: Correspondence on NanoVar’s performance outlined by Jiang T. et al. in ‘Long-read sequencing settings for efficient structural variation detection based on comprehensive evaluation’. (2023). BMC Bioinformatics 24 (1), 352.

13.Anqi Zhang, Tangchao Kong, Baiquan Sun, Shizheng Qiu, Jiahe Guo, Shuyong Ruan, Yu Guo, Jirui Guo, Zhishuai Zhang, Yue Liu, Zheng Hu, Tao Jiang, Yadong Liu, Shuqi Cao, Shi Sun, Tingting Wu, Huilong Hong, Bingjun Jiang, Maoxiang Yang, Xiangyu Yao, Yadong Wang, A telomere-to-telomere genome assembly of Zhonghuang 13, a widely-grown soybean variety from the original center of Glycine max. (2023).The Crop Journal.

14.Pir Noman Ahmad, Yuanchao Liu, Khalid Khan, Tao Jiang, Umama Burhan. BIR: Biomedical Information Retrieval System for Cancer Treatment in Electronic Health Record Using Transformers. Sensors 2023, 23(23), 9355.

15.Liu Q, Wang D, Zhou L, Li J, Wang G. MTGDC: a multi-scale tensor graph diffusion clustering for single-cell RNA sequencing data [J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023: 1 - 12.

16.Ren T, Huang S, Liu Q, Wang G. scWECTA: A weighted ensemble classification framework for cell type assignment based on single cell transcriptome [J]. Computers in Biology and Medicine, 2023, 152: 106409.

17.Wang X, Gao X, Wang G, Li D. miProBERT: identification of microRNA promoters based on the pre-trained model BERT [J]. Briefings in bioinformatics, 2023, 24(3): bbad093.

18.Wang X, Li J, Wang G. MicroRNA Promoter Identification in Human with a Three-level Prediction Method [J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023: 1 - 10.

19.Bian J, Zhang X, Zhang X, Xu D, Wang G. MCANet: shared-weight-based MultiheadCrossAttention network for drug–target interaction prediction [J]. Briefings in Bioinformatics, 2023, 24(2): bbad082.

20.Chen S, Yu Y, Wang X, Wang S, Zhang T, Zhou Y, He R, Meng N, Wang Y, Liu W, Liu Z, Liu J, Guo Q, Huang H, Sederoff R R, Wang G, Qu G, Chen S. Chromosome‐level genome assembly of a triploid poplar Populus alba ‘Berolinensis’ [J]. Molecular Ecology Resources, 2023: 1092-107.

21.Cui L, Li H, Bian J, Wang G, Liang Y. Unsupervised construction of gene regulatory network based on single-cell multi-omics data of colorectal cancer [J]. Briefings in Bioinformatics, 2023, 24(2): bbad011.

22.Li Y, Guo Z, Wang K, Gao X, Wang G. End-to-end interpretable disease–gene association prediction [J]. Briefings in Bioinformatics, 2023, 24(3): bbad118.

23.Liu C, Zhang Y, Gao X, Wang G. Identification of cell subpopulations associated with disease phenotypes from scRNA-seq data using PACSI [J]. BMC biology, 2023, 21(1): 1-19.

24.Zhang T, Li L, Sun H, Wang G. DeepITEH: a deep learning framework for identifying tissue-specific eRNAs from the human genome [J]. Bioinformatics, 2023, 39(6): btad375.

25.Zhang T, Li L, Sun H, Xu D, Wang G. DeepICSH: a complex deep learning framework for identifying cell-specific silencers and their strength from the human genome [J]. Briefings in Bioinformatics, 2023: bbad316.

26.Zhao J, Qian F, Li X, Yu Z, Zhu J, Yu R, Zhao Y, Ding K, Li Y, Yang Y, Pan Q, Chen J, Song C, Wang Q, Zhang J, Wang G, Li C. CanMethdb: a database for genome-wide DNA methylation annotation in cancers [J]. Bioinformatics, 2023, 39(1): btac783.

27.Gao W, Xu D, Li H, Du J, Wang G, Li D. Identification of adaptor proteins by incorporating deep learning and PSSM profiles [J]. Methods, 2023, 209: 10-7.

28.Liu Y, Zhao X, Bian J, Wang G. Feature selection combined with top-down and bottom-up strategies for survival analysis: A case of prognostic prediction in glioblastoma [J]. Computers in Biology and Medicine, 2023, 153: 106486.

29.Li Y, Guo Z, Gao X, Wang G. MMCL-CDR: enhancing cancer drug response prediction with multi-omics and morphology images contrastive representation learning [J]. Bioinformatics, 2023, 39(12): btad734.

30.Dong B, Sun W, Xu D, Wang G, Zhang T. DAEMDA: A Method with Dual-Channel Attention Encoding for miRNA–Disease Association Prediction [J]. Biomolecules, 2023, 13(10): 1514.

31.Dong B, Sun W, Xu D, Wang G, Zhang T. MDformer: A transformer-based method for predicting miRNA-Disease associations using multi-source feature fusion and maximal meta-path instances encoding [J]. Computers in Biology and Medicine, 2023, 167: 107585.

32.Dong L, Wang J, Wang G. ASAS-EGB: A statistical framework for estimating allele-specific alternative splicing events using transcriptome data [J]. Computers in Biology and Medicine, 2023, 160: 106981.

33.Meng P, Wang G, Guo H, Jiang T. Identifying cancer driver genes using a two-stage random walk with restart on a gene interaction network [J]. Computers in Biology and Medicine, 2023, 158: 106810.

34.Wang F, Yang F, Huang L, Li W, Song J, Gasser R B, Aebersold R, Wang G, Yao J. Deep domain adversarial neural network for the deconvolution of cell type mixtures in tissue proteome profiling [J]. Nature Machine Intelligence, 2023, 5(11): 1236-49.

35.Guo Y, Li D, Hu Y. Appraising the Associations Between Systemic Iron Status and Epigenetic Clocks: A Genetic Correlation and Bidirectional Mendelian Randomization Study. Am J Clin Nutr. 2023 Jul;118(1):41-49. doi: 10.1016/j.ajcnut.2023.05.004. Epub 2023 May 3. PMID: 37146762.

36.Zhang X, Guo H, Zhang F, Wang X, Wu K, Qiu S, Liu B, Wang Y, Hu Y, Li J. HNetGO: protein function prediction via heterogeneous network transformer. Brief Bioinform. 2023 Sep 22;24(6):bbab556. doi: 10.1093/bib/bbab556. PMID: 37861172; PMCID: PMC10588005.

37.Du L, Liu H, Zhang L, Lu Y, Li M, Hu Y, Zhang Y. Deep ensemble learning for accurate retinal vessel segmentation. Comput Biol Med. 2023 May;158:106829. doi: 10.1016/j.compbiomed.2023.106829. Epub 2023 Apr 8. PMID: 37054633.

38.Zhang Z, Qiu S, Wang Z, Hu Y. Vitamin D levels and five cardiovascular diseases: A Mendelian randomization study. Heliyon. 2023 Dec 12;10(1):e23674. doi: 10.1016/j.heliyon.2023.e23674. PMID: 38187309; PMCID: PMC10767153.

39.Qiu S, Hu Y, Liu G. Mendelian randomization study supports the causal effects of air pollution on longevity via multiple age-related diseases. NPJ Aging. 2023 Dec 19;9(1):29. doi: 10.1038/s41514-023-00126-0. PMID: 38114504; PMCID: PMC10730819.

40.Wang F, Wang H, Yuan Y, Han B, Qiu S, Hu Y, Zang T. Integration of multiple-omics data to reveal the shared genetic architecture of educational attainment, intelligence, cognitive performance, and Alzheimer's disease. Front Genet. 2023 Oct 12;14:1243879. doi: 10.3389/fgene.2023.1359014. PMID: 37900179; PMCID: PMC10601659.

41.Qiu S, Zheng K, Hu Y, Liu G. Genetic correlation, causal relationship, and shared loci between vitamin D and COVID-19: A genome-wide cross-trait analysis. J Med Virol. 2023 May;95(5):e28780. doi: 10.1002/jmv.28780. PMID: 37212302.

42.Guo Y, Zhang Y, Hu Y. COVID-19 subgroups may slow down biological age acceleration. J Infect. 2023 Jan;86(1):66-117. doi: 10.1016/j.jinf.2022.10.018. Epub 2022 Oct 21. PMID: 36273644; PMCID: PMC9584757.

2022

1.Wang T, Liu Y, Yin Q, et al. Enhancing discoveries of molecular QTL studies with small sample size using summary statistic imputation[J]. Briefings in bioinformatics, 2022, 23(1): bbab370.

2.Wang T, Liu Y, Yin Q, et al. Correction to: Enhancing discoveries of molecular QTL studies with small sample size using summary statistic imputation[J]. Briefings in Bioinformatics, 2022, 23(3): bbac139.

3.Guan D, McCarthy S, Wood J, et al. Genome sequence assembly evaluation using long-range sequencing data[J]. bioRxiv, 2022.

4.Huang C, Cen K, Zhang Y, et al. MEAHNE: MiRNA-disease association prediction based on semantic information in heterogeneous networks[J]. bioRxiv, 2022.

5.Jiang T, Liu S, Cao S, et al. Structural Variant Detection from Long-Read Sequencing Data with cuteSV[J]. Methods in Molecular Biology (Clifton, NJ), 2022, 2493: 137-151.

6.Wang Y, Juan L, Peng J, et al. Explore potential disease related metabolites based on latent factor model[J]. BMC genomics, 2022, 23(1): 1-14.

7.Li J, Li X, Hutchinson J, et al. An ensemble prediction model for COVID-19 mortality risk[J]. medRxiv, 2022.

8.Wang S, Li J, Wang Y. M2PP: a novel computational model for predicting drug-targeted pathogenic proteins[J]. BMC bioinformatics, 2022, 23(1): 1-18.

9.Li J, Xiao L, Li L, et al. A Low-Cost Error-Tolerant Flip-Flop Against SET and SEU for Dependable Designs[J]. IEEE Transactions on Circuits and Systems I: Regular Papers, 2022.

10.Li S, Xu J, Li R, et al. Stretchable Electronic Facial Masks for Sonophoresis[J]. ACS nano, 2022, 16(4): 5961-5974.

11.Liu Q, Luo X, Li J, et al. scESI: evolutionary sparse imputation for single-cell transcriptomes from nearest neighbor cells[J]. Briefings in Bioinformatics, 2022.

12.Zhang Z, Jiao Q, Zhang Y, et al. OTUCD: Unsupervised GCN based metagenomics non-overlapping community detection[J]. Computational Biology and Chemistry, 2022, 98: 107670.

13.Wang L, Wu M, Wu Y, et al. Prediction of the disease causal genes based on heterogeneous network and multi-feature combination method[J]. Computational Biology and Chemistry, 2022, 97: 107639.

14.Wu Y, Wang X, Susilo W, et al. Mixed-protocol multi-party computation framework towards complex computation tasks with malicious security[J]. Computer Standards & Interfaces, 2022, 80: 103570.

15.Han X, Xie R, Li X, et al. SmileGNN: Drug–Drug Interaction Prediction Based on the SMILES and Graph Neural Network[J]. Life, 2022, 12(2): 319.

16.Zhang C, Jiang H, Jiang H, et al. Deep learning for microscopic examination of protozoan parasites[J]. Computational and Structural Biotechnology Journal, 2022.

17.Pi J, Jiao P, Zhang Y, et al. MDGNN: Microbial Drug Prediction Based on Heterogeneous Multi-Attention Graph Neural Network[J]. Frontiers in Microbiology, 2022, 13.

18.Zhang C, Jiang H, Liu W, et al. Correction of out-of-focus microscopic images by deep learning[J]. Computational and Structural Biotechnology Journal, 2022, 20: 1957-1966.

19.Liu H, Hu Y, Zhang Y, et al. Mendelian randomization highlights significant difference and genetic heterogeneity in clinically diagnosed Alzheimer’s disease GWAS and self-report proxy phenotype GWAX[J]. Alzheimer's Research & Therapy, 2022, 14(1): 1-10.

20.Wang F, Wang H, Wang L, et al. MHCRoBERTa: pan-specific peptide–MHC class I binding prediction through transfer learning with label-agnostic protein sequences[J]. Briefings in Bioinformatics, 2022, 23(3): bbab595.

21.Qiu S, Hu Y, Cheng L. A genome-wide cross-trait analysis highlights the shared genetic structure between COVID-19 and Alzheimer's disease[J]. Journal of Infection, 2022, 84(1): e1-e2.

22.Hu Y, Zhang Y, Zhang H, et al. Mendelian randomization highlights causal association between genetically increased C-reactive protein levels and reduced Alzheimer's disease risk[J]. Alzheimer's & dementia: the journal of the Alzheimer's Association, 2022.

23.Qiu S, Hu Y, Cheng L. BIN1 rs744373 located in enhancers of brain tissues upregulates BIN1 mRNA expression, thereby leading to Alzheimer's disease[J]. Alzheimer's & Dementia: the Journal of the Alzheimer's Association, 2022.

24.Zhang C, Lu Y, Zang T. CNN-DDI: a learning-based method for predicting drug–drug interactions using convolution neural networks[J]. BMC bioinformatics, 2022, 23(1): 1-12.

25.Zhang N, Zang T. A multi-network integration approach for measuring disease similarity based on ncRNA regulation and heterogeneous information[J]. BMC bioinformatics, 2022, 23(1): 1-14.

2021

1. Liu Y, Huang Y, Wang G, et al. A deep learning approach for filtering structural variants in short read sequencing data[J]. Briefings in bioinformatics, 2021, 22(4): bbaa370.

2. Liu Y, Jiang T, Su J, et al. SKSV: ultrafast structural variation detection from circular consensus sequencing reads[J]. Bioinformatics, 2021, 37(20): 3647-3649.

3. Xu D, Li J, Wang D, et al. Prediction performance of twelve tumor mutation burden panels in melanoma and non-small cell lung cancer[J]. Critical Reviews in Oncology/Hematology, 2021: 103573.

4. Mao G, Wu Y, Zhang Y, et al. DRBin: Metagenomic binning based on deep representation learning[J]. Journal of genetics and genomics= Yi chuanxue bao, 2021: S1673-8527 (21) 00375-1.

5. Liu Y, Qiu S, Hu Y, et al. Differentially expressed mutant genes reveal potential prognostic markers for lung adenocarcinoma[C]//2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2021: 1856-1864.

6. Wang T, Liu Y, Ruan J, et al. A pipeline for RNA-seq based eQTL analysis with automated quality control procedures[J]. BMC bioinformatics, 2021, 22(9): 1-18.

7. Liu Y, Wu X, Wang Y. An integrated approach for copy number variation discovery in parent–offspring trios[J]. Briefings in Bioinformatics, 2021, 22(6): bbab230.

8. Xin R, Gao Y, Gao Y, et al. isoCirc catalogs full-length circular RNA isoforms in human transcriptomes[J]. Nature communications, 2021, 12(1): 1-11.

9. Guan D, McCarthy S A, Ning Z, et al. Efficient iterative Hi-C scaffolder based on N-best neighbors[J]. BMC bioinformatics, 2021, 22(1): 1-16.

10. Jiang T, Liu S, Cao S, et al. Long-read sequencing settings for efficient structural variation detection based on comprehensive evaluation[J]. BMC bioinformatics, 2021, 22(1): 1-17.

11. Cui Z, Cui Y, Zang T, et al. interacCircos: an R package based on JavaScript libraries for the generation of interactive circos plots[J]. Bioinformatics, 2021, 37(20): 3642-3644.

12. Ye X, Wu Y, Pi J, et al. Deepgmd: a graph-neural-network-based method to detect gene regulator module[J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021.

13. Li J, Li H, Ye X, et al. IIMLP: integrated information-entropy-based method for LncRNA prediction[J]. BMC bioinformatics, 2021, 22(3): 1-12.

14. Xu Y, Cui X, Wang Y. Pan-Cancer Metastasis Prediction Based on Graph Deep Learning Method[J]. Frontiers in Cell and Developmental Biology, 2021, 9: 1133.

15. He M, Huang C, Liu B, et al. Factor graph-aggregated heterogeneous network embedding for disease-gene association prediction[J]. BMC bioinformatics, 2021, 22(1): 1-15.

16. Zhang X, Wang L, Liu H, et al. Prot2GO: predicting GO annotations from protein sequences and interactions[J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021.

17. Xu Y, Zhang L, Cui X, et al. Novel Multikernel Trick for Predicting Pan-CancerDistant Metastatic Sites Using a Feature Extraction Strategy[C]//2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2021: 1899-1905.

18. Li G, Liu Y, Li D, et al. Fast and Accurate Classification of Meta-Genomics Long Reads With deSAMBA[J]. Frontiers in cell and developmental biology, 2021, 9: 643645.

19. Zhang Z, Liu Y, Li G, et al. PocaCNV: A Tool to Detect Copy Number Variants from Population-Scale Genome Sequencing Data[C]//2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2021: 1912-1918.

20. Shi N, Wu Y, Du L, et al. ScSSC: Semi-supervised Single Cell Clustering Based on 2D Embedding[C]//International Conference on Intelligent Computing. Springer, Cham, 2021: 478-489.

21. Wang S, Li J, Wang Y, et al. A neighborhood-based global network model to predict drug-target interactions[J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021.

22. Li J, Chen Z, Ma D, et al. A Novel Approach to Predicting Interactions Between Microbes and Hosts[J]. 2021.

23. Cui Z, Cui Y, Gao Y, et al. Enhancement and Imputation of Peak Signal Enables Accurate Cell-Type Classification in scATAC-seq[J]. Frontiers in genetics, 2021, 12: 658352.

24. Quan W, Liu B, Wang Y. Fast and SNP-aware short read alignment with SALT[J]. BMC bioinformatics, 2021, 22(9): 1-13.

25. Gao Y, Liu Y, Ma Y, et al. Erratum to: abPOA: an SIMD-based C library for fast partial order alignment using adaptive band[J]. Bioinformatics, 2021.

26. Li G, Jiang T, Li J, et al. PanSVR: Pan-Genome Augmented Short Read Realignment for Sensitive Detection of Structural Variations[J]. Frontiers in Genetics, 2021: 1486.

27. Liu Y, Jiang T, Gao Y, et al. Psi-caller: a lightweight short read-based variant caller with high speed and accuracy[J]. Frontiers in Cell and Developmental Biology, 2021: 2139.

28. Wu Y, Ju D, Wang F, et al. Synthesis of aramid nanoscale fiber‐based nanocomposite with transparency, flexibility, and selective adsorption capability[J]. Polymers for Advanced Technologies, 2021, 32(6): 2476-2486.

29. Li H, Xiao L, Qi C, et al. Design of high-reliability memory cell to mitigate single event multiple node upsets[J]. IEEE Transactions on Circuits and Systems I: Regular Papers, 2021, 68(10): 4170-4181.

30. Li J, Jiang W, Han H, et al. Scgslc: An unsupervised graph similarity learning framework for single-cell rna-seq data clustering[J]. Computational Biology and Chemistry, 2021, 90: 107415.

31. Zhang Y, Ye T, Xi H, et al. Deep learning driven drug discovery: tackling severe acute respiratory syndrome coronavirus 2[J]. Frontiers in Microbiology, 2021, 12.

32. Zhao T, Hu Y, Valsdottir L R, et al. Identifying drug–target interactions based on graph convolutional network and deep neural network[J]. Briefings in bioinformatics, 2021, 22(2): 2141-2150.

33. Zhao T, Hu Y, Cheng L. Deep-DRM: a computational method for identifying disease-related metabolites based on graph deep learning approaches[J]. Briefings in Bioinformatics, 2021, 22(4): bbaa212.

34. Hu Y, Qiu S, Cheng L. Integration of multiple-omics data to analyze the population-specific differences for coronary artery disease[J]. Computational and mathematical methods in medicine, 2021, 2021.

35. Hu Y, Sun J, Zhang Y, et al. rs1990622 variant associates with Alzheimer’s disease and regulates TMEM106B expression in human brain tissues[J]. BMC medicine, 2021, 19(1): 1-10.

36. Qiu S, Cao P, Guo Y, et al. Exploring the causality between hypothyroidism and non-alcoholic fatty liver: a Mendelian randomization study[J]. Frontiers in cell and developmental biology, 2021, 9: 643582.

37. Liu H, Zhang Y, Hu Y, et al. Mendelian randomization to evaluate the effect of plasma vitamin C levels on the risk of Alzheimer’s disease[J]. Genes & Nutrition, 2021, 16(1): 1-17.

38. Qiu S, Zhang Y, Wang D, et al. The high expression of SARS-CoV-2 cell receptors might lead to higher COVID-19 infection rates in cancer patients[J]. Journal of Infection, 2021, 83(6): 709-737.

39. Zhang J, Sun M, Zhao Y, et al. Identification of Gingivitis-Related Genes Across Human Tissues Based on the Summary Mendelian Randomization[J]. Frontiers in Cell and Developmental Biology, 2021, 8: 624766.

40. Li F, Luo M, Zhou W, et al. Single cell RNA and immune repertoire profiling of COVID-19 patients reveal novel neutralizing antibody[J]. Protein & cell, 2021, 12(10): 751-755.

41. Zhao T, Lyu S, Lu G, et al. SC2disease: a manually curated database of single-cell transcriptome for human diseases[J]. Nucleic Acids Research, 2021, 49(D1): D1413-D1419.

42. Chen Y, Juan L, Lv X, et al. Bioinformatics Research on Drug Sensitivity Prediction[J]. Frontiers in Pharmacology, 2021, 12: 799712.

43. Zhou W, Xu C, Wang P, et al. N439K variant in spike protein alter the infection efficiency and antigenicity of SARS-CoV-2 based on molecular dynamics simulation[J]. Frontiers in cell and developmental biology, 2021: 2071.

44. Zhao T, Liu J, Zeng X, et al. Prediction and collection of protein–metabolite interactions[J]. Briefings in Bioinformatics, 2021, 22(5): bbab014.

45. Zhang N, Zang T. prePathCluster: An novel deep-learning based method for endocrine disease pathway analysis[C]//2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2021: 1919-1926.

46. Zhang N, Xu C, Zhang L, et al. DeepGP: An integrated deep-learning method for endocrine disease gene prediction using omics data[J]. Frontiers in Cell and Developmental Biology, 2021, 9: 1650.

2020

1. Li, Junyi, Qingzhe Xu, Mingxiao Wu, Tao Huang, and Yadong Wang. 2020. “Pan-Cancer Classification Based on Self-Normalizing Neural Networks and Feature Selection.” Frontiers in Bioengineering and Biotechnology.

2. Jiang, T., Liu, Y., Jiang, Y. et al. Long-read-based human genomic structural variation detection with cuteSV. Genome Biol 21, 189 (2020). https://doi.org/10.1186/s13059-020-02107-y

3. Li, Junyi, Yuan Ping, Hong Li, Huinian Li, Ying Liu, Bo Liu, and Yadong Wang. 2020. “Prognostic Prediction of Carcinoma by a Differential-Regulatory-Network-Embedded Deep Neural Network.” Computational Biology and Chemistry 88: 107317.

4. Juan, Liran, Yongtian Wang, Jingyi Jiang, Qi Yang, Guohua Wang, and Yadong Wang. 2020. “Evaluating Individual Genome Similarity with a Topic Model.” Bioinformatics.

5. Zhao, Tianyi, Yang Hu, Tianyi Zang, and Yadong Wang. 2020. “Identifying Protein Biomarkers in Blood for Alzheimer’s Disease.” Frontiers in Cell and Developmental Biology 8: 472.

6. Wang, Tao, Qidi Peng, Bo Liu, Yongzhuang Liu, and Yadong Wang. 2020. “Disease Module Identification Based on Representation Learning of Complex Networks Integrated From GWAS, EQTL Summaries, and Human Interactome.” Frontiers in Bioengineering and Biotechnology 8: 418.

7. Peng, Jiajie, Linjiao Zhu, Yadong Wang, and Jin Chen. 2020. “Mining Relationships among Multiple Entities in Biological Networks.” IEEE/ACM Transactions on Computational Biology and Bioinformatics 17 (3): 769–76.

8. Tan, Renjie, Jixuan Wang, Xiaoliang Wu, Liran Juan, Tianjiao Zhang, Rui Ma, Qing Zhan, Tao Wang, Shuilin Jin, and Qinghua Jiang. 2020. “ERDS-Exome: A Hybrid Approach for Copy Number Variant Detection from Whole-Exome Sequencing Data.” IEEE/ACM Transactions on Computational Biology and Bioinformatics 17 (3): 796–803.

9. Zhan, Qing, Yilei Fu, Qinghua Jiang, Bo Liu, Jiajie Peng, and Yadong Wang. 2020. “SpliVert: A Protein Multiple Sequence Alignment Refinement Method Based on Splitting-Splicing Vertically.” Protein and Peptide Letters 27 (4): 295–302.

10. Wang, Shiming, Jie Li, and Yadong Wang. 2020. “WMMDCA: Prediction of Drug Responses by Weight-Based Modular Mapping in Cancer Cell Lines.” IEEE/ACM Transactions on Computational Biology and Bioinformatics, 1–1.

11. Chu, Yanshuo, Chenxi Nie, and Yadong Wang. 2020. “A Pipeline for Reconstructing Somatic Copy Number Alternation’s Subclonal Population-Based Next-Generation Sequencing Data.” Frontiers in Genetics 10: 1374.

12. Wang, Tao, Jiajie Peng, Qidi Peng, Yadong Wang, and Jin Chen. 2020. “FSM: Fast and Scalable Network Motif Discovery for Exploring Higher-Order Network Organizations.” Methods 173: 83–93.

13. Juan, Liran, Yongtian Wang, Jingyi Jiang, Qi Yang, Qinghua Jiang, and Yadong Wang. 2020. “PGsim: A Comprehensive and Highly Customizable Personal Genome Simulator.” Frontiers in Bioengineering and Biotechnology 8: 28.

14. Dengfeng Guan, Shane A McCarthy, Jonathan Wood, Kerstin Howe, Yadong Wang, Richard Durbin, Identifying and removing haplotypic duplication in primary genome assemblies, Bioinformatics, Volume 36, Issue 9, 1 May 2020, Pages 2896–2898, https://doi.org/10.1093/bioinformatics/btaa025

15. Li, Jie, Shiming Wang, Zhuo Chen, and Yadong Wang. 2020. “A Bipartite Network Module-Based Project to Predict Pathogen-Host Association.” Frontiers in Genetics 10: 1357.

16. Li, Jie, Zhuo Chen, and Yadong Wang. 2020. “Contents, Construction Methods, Data Resources, and Functions Comparative Analysis of Bacteria Databases.” International Journal of Biological Sciences 16 (5): 838–48.

17. Wang, Tao, Qidi Peng, Bo Liu, Xiaoli Liu, Yongzhuang Liu, Jiajie Peng, and Yadong Wang. 2020. “EQTLMAPT: Fast and Accurate EQTL Mediation Analysis With Efficient Permutation Testing Approaches.” Frontiers in Genetics 10: 1309.

2019

1. Guo, Hongzhe, Bo Liu, Dengfeng Guan, Yilei Fu, and Yadong Wang. 2019. “Fast Read Alignment with Incorporation of Known Genomic Variants.” BMC Medical Informatics and Decision Making 19 (6): 265.

2. Liu, Bo, Yadong Liu, Junyi Li, Hongzhe Guo, Tianyi Zang, and Yadong Wang. 2019. “DeSALT: Fast and Accurate Long Transcriptomic Read Alignment with de Bruijn Graph-Based Index.” Genome Biology 20 (1): 1–14.

3. Tao Jiang, Bo Liu, Junyi Li, Yadong Wang, rMETL: sensitive mobile element insertion detection with long read realignment, Bioinformatics, Volume 35, Issue 18, 15 September 2019, Pages 3484–3486, https://doi.org/10.1093/bioinformatics/btz106

4. Wang, Yongtian, Liran Juan, Jiajie Peng, Tianyi Zang, and Yadong Wang. 2019. “LncDisAP: A Computation Model for LncRNA-Disease Association Prediction Based on Multiple Biological Datasets.” BMC Bioinformatics 20 (16): 582.

5. Liu, Yongzhuang, Jian Liu, and Yadong Wang. 2019. “Joint Detection of Germline and Somatic Copy Number Events in Matched Tumor-Normal Sample Pairs.” Bioinformatics 35 (23): 4955–61.

6. H. Guo, Y. Fu, Y. Gao, J. Li, Y. Wang and B. Liu, "deGSM: memory scalable construction of large scale de Bruijn Graph," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, doi: 10.1109/TCBB.2019.2913932.

7. T. Jiang, Y. Fu, B. Liu and Y. Wang, "Long-Read Based Novel Sequence Insertion Detection With rCANID," in IEEE Transactions on NanoBioscience, vol. 18, no. 3, pp. 343-352, July 2019, doi: 10.1109/TNB.2019.2908438.

8. Yan Gao, Bo Liu, Yadong Wang, Yi Xing, TideHunter: efficient and sensitive tandem repeat detection from noisy long-reads using seed-and-chain, Bioinformatics, Volume 35, Issue 14, July 2019, Pages i200–i207, https://doi.org/10.1093/bioinformatics/btz376

9. Wang, Zhenxing, and Yadong Wang. 2019. “Extracting a Biologically Latent Space of Lung Cancer Epigenetics with Variational Autoencoders.” BMC Bioinformatics 20 (18): 1–7.

10. Zhan, Qing, Nan Wang, Shuilin Jin, Renjie Tan, Qinghua Jiang, and Yadong Wang. 2019. “ProbPFP: A Multiple Sequence Alignment Algorithm Combining Hidden Markov Model Optimized by Particle Swarm Optimization with Partition Function.” BMC Bioinformatics 20 (18): 1–10.

11. Wang, Yongtian, Liran Juan, Jiajie Peng, Tianyi Zang, and Yadong Wang. 2019. “Prioritizing Candidate Diseases-Related Metabolites Based on Literature and Functional Similarity.” BMC Bioinformatics 20 (18): 1–11.

12. Zhang, Tianjiao, Rongjie Wang, Qinghua Jiang, and Yadong Wang. 2019. “An Information Gain-Based Method for Evaluating the Classification Power of Features Towards Identifying Enhancers.” Current Bioinformatics 14.

13. Liu, Yongzhuang, Jian Liu, and Yadong Wang. 2019. “DNMFilter_Indel: Filtering de Novo Indels in Parent-Offspring Trios.” In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 1758–61.

14. Wang, Tao, Junpeng Ruan, Quanwei Yin, Xianjun Dong, and Yadong Wang. 2019. “An Automated Quality Control Pipeline for EQTL Analysis with RNA-Seq Data.” In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 1780–86.

15. Quan, Wei, Bo Liu, and Yadong Wang. 2019. “SALT: A Fast, Memory-Efficient and SNP-Aware Short Read Alignment Tool.” In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 1774–79.

16. Quan, Wei, Guangri Quan, Bo Liu, and Yadong Wang. 2019. “A Bidirectional Fuzzy Index and Approximate Search Algorithm for Next Generation Sequencing.” In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 293–97.

17. Li, Jie, Zhun Zhao, Li Zhou, and Yadong Wang. 2019. “Y-SPCR: A New Dimensionality Reduction Method for Gene Expression Data Classification.” In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 401–8.

18. Zhao, Tianyi, Yang Hu, Tianyi Zang, and Yadong Wang. 2019. “Integrate GWAS, EQTL, and MQTL Data to Identify Alzheimer’s Disease-Related Genes.” Frontiers in Genetics 10: 1021–1021.

19. Wang, Rongjie, Tianyi Zang, and Yadong Wang. 2019. “Human Mitochondrial Genome Compression Using Machine Learning Techniques.” Human Genomics 13 (1): 49.

20. Wang, Yongtian, Chenxi Nie, Tianyi Zang, and Yadong Wang. 2019. “Predicting CircRNA-Disease Associations Based on CircRNA Expression Similarity and Functional Similarity.” Frontiers in Genetics 10: 832–832.

21. Li, Jie, Qiaosheng Zhang, Zhuo Chen, Dechen Xu, and Yadong Wang. 2019. “A Network-Based Pathway-Extending Approach Using DNA Methylation and Gene Expression Data to Identify Altered Pathways.” Scientific Reports 9 (1): 11853.

22. Li, Junyi, Huinian Li, Li Zhang, Qingzhe Xu, Yuan Ping, Xiaozhu Jing, Wei Jiang, Bo Liu, and Yadong Wang. 2019. “Prediction of Human LncRNAs Based on Integrated Information Entropy Features.” In International Conference on Intelligent Computing, 333–43.

23. Li, Junyi, Li Zhang, Huinian Li, Yuan Ping, Qingzhe Xu, Rongjie Wang, Renjie Tan, Zhen Wang, Bo Liu, and Yadong Wang. 2019. “Integrated Entropy-Based Approach for Analyzing Exons and Introns in DNA Sequences.” BMC Bioinformatics 20 (8): 283–283.

24. Sun, Mingrui, Tengfei Min, Tianyi Zang, and Yadong Wang. 2019. “CDL4CDRP: A Collaborative Deep Learning Approach for Clinical Decision and Risk Prediction.” Processes 7 (5): 265.

25. Sun, Yanran, Qiaosheng Zhang, Guoshuang Feng, Zhen Chen, Chao Gao, Shuguang Liu, Ruidong Zhang, Han Zhang, Xueling Zheng, and Wenyu Gong. 2019. “An Improved Advanced Fragment Analysis-Based Classification and Risk Stratification of Pediatric Acute Lymphoblastic Leukemia.” Cancer Cell International 19 (1): 110.

26. Li, Jie, Dong Wang, and Yadong Wang. 2019. “IBI: Identification of Biomarker Genes in Individual Tumor Samples.” Frontiers in Genetics 10: 1236.

27. Zhao, Tianyi, Donghua Wang, Yang Hu, Ningyi Zhang, Tianyi Zang, and Yadong Wang. 2019. “Identifying Alzheimer’s Disease-Related MiRNA Based on Semi-Clustering.” Current Gene Therapy 19 (4): 216–23.

28. L. Wang, X. Wang and Y. Wang, "An Approximate Bufferless Network-on-Chip," in IEEE Access, vol. 7, pp. 141516-141532, 2019, doi: 10.1109/ACCESS.2019.2943922.

2018

1. Chu, Yan-Shuo, Mingxiang Teng, and Yadong Wang. 2019. “Simulating Genetically Heterozygous Genomes in the Tumour Tissue According to Its Clonal Evolution History.” International Journal of Computational Biology and Drug Design 12 (2): 143–52.

2. Wang, Dong, Jie Li, Rui Liu, and Yadong Wang. 2018. “Optimizing Gene Set Annotations Combining GO Structure and Gene Expression Data.” BMC Systems Biology 12 (9): 133.

3. Wang, Zhenxing, and Yadong Wang. 2018. “Exploring DNA Methylation Data of Lung Cancer Samples with Variational Autoencoders.” In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 1286–89.

4. Guan, Dengfeng, Bo Liu, and Yadong Wang. 2018. “DeSPI: Efficient Classification of Metagenomics Reads with Lightweight de Bruijn Graph-Based Reference Indexing.” In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 265–69.

5. Wang, Yongtian, Liran Juan, Chunpu Liu, Tianyi Zang, and Yadong Wang. 2018. “Identifying Candidate Diseases-Related Metabolites Based on Disease Similarity.” In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 1281–85.

6. Guo, Hongzhe, Bo Liu, Dengfeng Guan, Yilei Fu, and Yadong Wang. 2018. “Fast Variation-Aware Read Alignment with DeBGA-VARA.” In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 227–33.

7. Zhan, Qing, Nan Wang, Shuilin Jin, Renjie Tan, Qinghua Jiang, and Yadong Wang. 2018. “ProbPFP: A Multiple Sequence Alignment Algorithm Combining Partition Function and Hidden Markov Model with Particle Swarm Optimization.” In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 1290–95.

8. Wang, Fuxu, Mingrui Sun, Tengfei Min, Yueying Wang, Chunpu Liu, Tianyi Zang, and Yadong Wang. 2018. “Analysis for Early Seizure Detection System Based on Deep Learning Algorithm.” In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2382–89.

9. Wang, Yongtian, Liran Juan, Jiajie Peng, Tianyi Zang, and Yadong Wang. 2018. “Predicting Candidate Disease-Related LncRNAs Based on Network Random Walk.” In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 524–31.

10. Wang, Ling, and Yadong Wang. 2018. “A Network-on-Chip Accelerator for Genome Variant Analysis.” In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 775–79.

11. Wang, Rongjie, Yang Bai, Yan-Shuo Chu, Zhenxing Wang, Yongtian Wang, Mingrui Sun, Junyi Li, Tianyi Zang, and Yadong Wang. 2018. “DeepDNA: A Hybrid Convolutional and Recurrent Neural Network for Compressing Human Mitochondrial Genomes.” In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 270–74.

12. Chu, Yanshuo, Chenxi Nie, and Yadong Wang. 2018. “P-SCNAClonal: Somatic Copy Number Alterations Based Tumor Subclonal Population Inferring Method.” In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 1693–98.

13. Sun, Mingrui, Fuxu Wang, Tengfei Min, Tianyi Zang, and Yadong Wang. 2018. “Prediction for High Risk Clinical Symptoms of Epilepsy Based on Deep Learning Algorithm.” IEEE Access 6: 77596–605.

14. Wang, Rongjie, Junyi Li, Yang Bai, Tianyi Zang, and Yadong Wang. 2018. “BdBG: A Bucket-Based Method for Compressing Genome Sequencing Data with Dynamic de Bruijn Graphs.” PeerJ 6.

15. Peng, Jiajie, Hansheng Xue, Weiwei Hui, Junya Lu, Bolin Chen, Qinghua Jiang, Xuequn Shang, and Yadong Wang. 2018. “An Online Tool for Measuring and Visualizing Phenotype Similarities Using HPO.” BMC Genomics 19 (6): 89–97.

16. Xue, Hanqing, Jie Li, Haozhe Xie, and Yadong Wang. 2018. “Review of Drug Repositioning Approaches and Resources.” International Journal of Biological Sciences 14 (10): 1232–44.

17. Wang, Zhenxing, XiaoLiang Wu, and Yadong Wang. 2018. “A Framework for Analyzing DNA Methylation Data from Illumina Infinium HumanMethylation450 BeadChip.” BMC Bioinformatics 19 (5): 115.

18. Chu, Yanshuo, Mingxiang Teng, and Yadong Wang. 2018. “Modeling and Correct the GC Bias of Tumor and Normal WGS Data for SCNA Based Tumor Subclonal Population Inferring.” BMC Bioinformatics 19 (5): 112–112.

19. Wang, Guohua, Ximei Luo, Jianan Wang, Jun Wan, Shuli Xia, Heng Zhu, Jiang Qian, and Yadong Wang. 2018. “MeDReaders: A Database for Transcription Factors That Bind to Methylated DNA.” Nucleic Acids Research 46.

2017

1. Cui, Xiao-fei, Ya-dong Wang, Guang-ri Quan, Yong-dong Xu, and Shawn X. Wang. 2017. “K-Mer Similarity: A Rapid Similarity Search Algorithm for Probe Design.” In .

2. Peng, Jiajie, Honggang Wang, Junya Lu, Weiwei Hui, Yadong Wang, and Xuequn Shang. 2017. “Identifying Term Relations Cross Different Gene Ontology Categories.” BMC Bioinformatics 18 (16): 573–573.

3. Wang, Yongtian, Liran Juan, Yanshuo Chu, Rongjie Wang, Tianyi Zang, and Yadong Wang. 2017. “FNSemSim: An Improved Disease Similarity Method Based on Network Fusion.” In 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 630–33.

4. Chu, Yanshuo, Mingxiang Teng, Zhenxing Wang, Yongtian Wang, and Yadong Wang. 2017. “Pre-SCNAClonal: Efficient GC Bias Correction for SCNA Based Tumor Subclonal Populations Inferring.” In 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 262–65.

5. Wang, Rongjie, Yang Bai, Qianlong Cheng, Tianyi Zang, and Yadong Wang. 2017. “A Bucket Index Correction Based Method for Compression of Genomic Sequencing Data.” In 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 634–37.

6. Wang, Zhenxing, Yanshuo Chu, Yongtian Wang, and Yadong Wang. 2017. “A Framework for Analyzing DNA Methylation Data from Illumina Infinium HumanMethylation450 BeadChip.” In 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 1688–93.

7. Chu, Yanshuo, Ling Wang, Rongjie Wang, Mingxiang Teng, and Yadong Wang. 2017. “Pysubsim-Tree: A Package for Simulating Tumor Genomes According to Tumor Evolution History.” In 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2195–97.

8. Chu, Yanshuo, Zhenxing Wang, Rongjie Wang, Ningyi Zhang, Jie Li, Yang Hu, Mingxiang Teng, and Yadong Wang. 2017. “WDNfinder: A Method for Minimum Driver Node Set Detection and Analysis in Directed and Weighted Biological Network.” Journal of Bioinformatics and Computational Biology 15 (5): 1750021.

9. Zhang, Qiaosheng, Jie Li, Dong Wang, and Yadong Wang. 2017. “Finding Disagreement Pathway Signatures and Constructing an Ensemble Model for Cancer Classification.” Scientific Reports 7 (1): 10044.

10. Peng, Jiajie, Hansheng Xue, Yukai Shao, Xuequn Shang, Yadong Wang, and Jin Chen. 2017. “A Novel Method to Measure the Semantic Similarity of HPO Terms.” International Journal of Data Mining and Bioinformatics 17 (2): 173–88.

11. Wang, Zhuo, Shuilin Jin, Guiyou Liu, Xiurui Zhang, Nan Wang, Deliang Wu, Yang Hu, Chiping Zhang, Qinghua Jiang, and Li Xu. 2017. “DTWscore: Differential Expression and Cell Clustering Analysis for Time-Series Single-Cell RNA-Seq Data.” BMC Bioinformatics 18 (1): 270.

12. Zhang, Xinjun, Meng Li, Hai Lin, Xi Rao, Weixing Feng, Yuedong Yang, Matthew Mort, David N. Cooper, Yue Wang, and Yadong Wang. 2017. “RegSNPs-Splicing: A Tool for Prioritizing Synonymous Single-Nucleotide Substitution.” Human Genetics 136 (9): 1279–89.

13. Peng, Jiajie, Hongxiang Li, Yongzhuang Liu, Liran Juan, Qinghua Jiang, Yadong Wang, and Jin Chen. 2017. “Erratum to: InteGO2: A Web Tool for Measuring and Visualizing Gene Semantic Similarities Using Gene Ontology.” BMC Genomics 18 (1): 262–262.

14. Peng, Jiajie, Kun Bai, Xuequn Shang, Guohua Wang, Hansheng Xue, Shuilin Jin, Liang Cheng, Yadong Wang, and Jin Chen. 2017. “Predicting Disease-Related Genes Using Integrated Biomedical Networks.” BMC Genomics 18 (1): 1043–1043.

15. Yao, Haobin, Tak Wah Lam, H. F. Ting, Siu-Ming Yiu, Yadong Wang, and Bo Liu. 2017. “Accurate Annotation of Metagenomic Data without Species-Level References.” International Journal of Data Mining and Bioinformatics 19 (4): 283–97.

2016

1. Zhang, Qiaosheng, Jie Li, Haozhe Xie, Hanqing Xue, and Yadong Wang. 2016. “A Network-Based Pathway-Expanding Approach for Pathway Analysis.” BMC Bioinformatics 17 (17): 536–536.

2. Zhou, Ao, Yadong Wang, Yunlong Liu, Weixing Feng, and Howard J. Edenberg. 2016. “Characterizing the Roles of Long Non-Coding RNA in Rat Alcohol Preference.” In 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 167–73.

3. Xie, Haozhe, Jie Li, Qiaosheng Zhang, and Yadong Wang. 2016. “Comparison among Dimensionality Reduction Techniques Based on Random Projection for Cancer Classification.” Computational Biology and Chemistry 65: 165–72.

4. Hu, Yang, Lingling Zhao, Zhiyan Liu, Hong Ju, Hongbo Shi, Peigang Xu, Yadong Wang, and Liang Cheng. 2016. “DisSetSim: An Online System for Calculating Similarity between Disease Sets.” In 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 8:28.

5. Yao, Haobin, Tak Wah Lam, H. F. Ting, Siu-Ming Yiu, Yadong Wang, and Bo Liu. 2017. “Accurate Annotation of Metagenomic Data without Species-Level References.” International Journal of Data Mining and Bioinformatics 19 (4): 283–97.

6. Peng, Jiajie, Hansheng Xue, Yukai Shao, Xuequn Shang, Yadong Wang, and Jin Chen. 2016. “Measuring Phenotype Semantic Similarity Using Human Phenotype Ontology.” In 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 763–66.

7. Tan, Renjie, Jixuan Wang, Xiaoliang Wu, Guoqiang Wan, Rongjie Wang, Rui Ma, Zhijie Han, Wenyang Zhou, Shuilin Jin, and Qinghua Jiang. 2016. “ERDS-Pe: A Paired Hidden Markov Model for Copy Number Variant Detection from Whole-Exome Sequencing Data.” In 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 141–44.

8. Wang, Rongjie, Mingxiang Teng, Yang Bai, Tianyi Zang, and Yadong Wang. 2016. “DMcompress: Dynamic Markov Models for Bacterial Genome Compression.” In 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 776–79.

9. Liu, Bo, Hongzhe Guo, Michael Brudno, and Yadong Wang. 2016. “DeBGA: Read Alignment with de Bruijn Graph-Based Seed and Extension.” Bioinformatics 32 (21): 3224–32.

10. Zhu, Shijia, and Yadong Wang. 2016. “Hidden Markov Induced Dynamic Bayesian Network for Recovering Time Evolving Gene Regulatory Networks.” Scientific Reports 5 (1): 17841–17841.

11. Guan, Dengfeng, Bo Liu, and Yadong Wang. 2016. “DeSPI: Efficient Classification of Metagenomic Reads with Lightweight de Bruijn Graph-Based Reference Indexing.” BioRxiv, 80200.

12. Peng, Jiajie, Hongxiang Li, Yongzhuang Liu, Liran Juan, Qinghua Jiang, Yadong Wang, and Jin Chen. 2016. “InteGO2: A Web Tool for Measuring and Visualizing Gene Semantic Similarities Using Gene Ontology.” BMC Genomics 17 (5): 530–530.

13. Hu, Yang, Ying Zhang, Jun Ren, Yadong Wang, Zhenzhen Wang, and Jun Zhang. 2016. “Statistical Approaches for the Construction and Interpretation of Human Protein-Protein Interaction Network.” BioMed Research International 2016: 5313050.

14. Feng, Weixing, Sen Zhao, Dingkai Xue, Fengfei Song, Ziwei Li, Duojiao Chen, Bo He, Yangyang Hao, Yadong Wang, and Yunlong Liu. 2016. “Improving Alignment Accuracy on Homopolymer Regions for Semiconductor-Based Sequencing Technologies.” BMC Genomics 17 (7): 521.

15. Hu, Yang, Wenyang Zhou, Jun Ren, Lixiang Dong, Yadong Wang, Shuilin Jin, and Liang Cheng. 2016. “Annotating the Function of the Human Genome with Gene Ontology and Disease Ontology.” BioMed Research International 2016: 4130861.

16. Feng, Weixing, Sen Zhao, Dingkai Xue, Fengfei Song, Ziwei Li, Duojiao Chao, Bo He, Yangyang Hao, Yadong Wang, and Yunlong Liu. 2016. “Improving Alignment Accuracy on Homopolymer Regions for Semiconductor-Based Sequencing Technologies.” PMC.

17. Shen, Changyu, Yang Hu, Xiaochun Li, Yadong Wang, Peng-Sheng Chen, and Alfred E. Buxton. 2016. “Identification of Subpopulations with Distinct Treatment Benefit Rate Using the Bayesian Tree.” Biometrical Journal 58 (6): 1357–75.

18. Zhang, Tianjiao, Yang Hu, Xiaoliang Wu, Rui Ma, Qinghua Jiang, and Yadong Wang. 2016. “Identifying Liver Cancer-Related Enhancer SNPs by Integrating GWAS and Histone Modification ChIP-Seq Data.” BioMed Research International 2016: 2395341–2395341.

19. Liu, Bo, Dixian Zhu, and Yadong Wang. 2016. “DeBWT: Parallel Construction of Burrows–Wheeler Transform for Large Collection of Genomes with de Bruijn-Branch Encoding.” Bioinformatics 32 (12): 174–82.

20. Liu, Bo, Dengfeng Guan, Mingxiang Teng, and Yadong Wang. 2016. “RHAT: Fast Alignment of Noisy Long Reads with Regional Hashing.” Bioinformatics 32 (11): 1625–31.

21. Zhang, Tianjiao, Yue Jiang, Liang Cheng, Yang Hu, and Yadong Wang. 2016. “Latent Semantic Analysis- and Hierarchical Clustering-Based Method for Detecting Remote Protein Homology.” Current Proteomics 13 (2): 92–98.

22. Peng, Jiajie, Tao Wang, Jixuan Wang, Yadong Wang, and Jin Chen. 2016. “Extending Gene Ontology with Gene Association Networks.” Bioinformatics 32 (8): 1185–94.

23. Liu, Yongzhuang, Jian Liu, Jianguo Lu, Jiajie Peng, Liran Juan, Xiaolin Zhu, Bingshan Li, and Yadong Wang. 2016. “Joint Detection of Copy Number Variations in Parent-Offspring Trios.” Bioinformatics 32 (8): 1130–37.

24. Zhang, Qiaosheng, Jie Li, Hanqing Xue, Leilei Kong, and Yadong Wang. 2016. “Network-Based Methods for Identifying Critical Pathways of Complex Diseases: A Survey.” Molecular BioSystems 12 (4): 1082–89.

25. Ontology, Gene, Jiajie Peng, Yongzhuang Liu, Liran Juan, Qinghua Jiang, Yadong Wang, and Jin Chen. 2016. “InteGO2: A Web Tool for Measuring and Visualizing Gene Semantic Similarities Using.”