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Selected Publications. See Google Scholar for the full publication list (Totally >100 articles; Cited>4000; H-index=31)

    Preprints

  1. S Zheng, Z Lei, H Ai, H Chen, D Deng*, Yuedong Yang*. Deep Scaffold Hopping with Multi-modal Transformer Neural Networks. chemRxiv 13011767
  2. Zhe Sun, Shuangjia Zheng, Huiying Zhao, Zhangming Niu, Yutong Lu, Yi Pan, Yuedong Yang*. To improve the predictions of binding residues with DNA, RNA, carbohydrate, and peptide via multiple-task deep neural networks. bioRxiv 2020.02.11.943571
  3. Jiahua Rao, Xiang Zhou, Yutong Lu, Huiying Zhao, Yuedong Yang*. Imputing Single-cell RNA-seq data by combining Graph Convolution and Autoencoder Neural Networks. bioRxiv 2020.02.05.935296
  4. Hua Chai, Xiang Zhou, Zifeng Cui, Jiahua Rao, Zheng Hu, Yutong Lu, Huiying Zhao, Yuedong Yang*. Integrating multi-omics data with deep learning for predicting cancer prognosis. bioRxiv 807214 .
  5. Haoyang Zhang, Junkang Wei, Zifeng Liu, Xun Liu, Yutian Chong, Yutong Lu, Huiying Zhao, Yuedong Yang*. DGAT-onco: A powerful method to detect oncogenes by integrating differential mutational analysis and functional impacts of somatic mutations bioRxiv 2020.02.15.947085

    2021

  6. Ying Song, Shuangjia Zheng, Liang Li, Xiang Zhang, Xiaodong Zhang, Ziwang Huang, Jianwen Chen, Huiying Zhao, Yusheng Jie, Ruixuan Wang, Yutian Chong*, Jun Shen*, Yunfei Zha*, Yuedong Yang*. Deep learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) with CT images medRxiv 2020.02.23.20026930 (TCBB, In press)
  7. Chen J, Zheng S, Zhao H, Yuedong Yang*. Structure-aware Protein Solubility Prediction From Sequence Through Graph Convolutional Network And Predicted Contact Map. J Cheminfo 2021 Feb 8;13(1):7 .
  8. Zhou X, Chai H, Zeng Y, Zhao H, Luo C*,Yuedong Yang*. scAdapt: Virtual adversarial domain adaptation network for single cell RNA-seq data classification across platforms and species. biorxiv RECOMB 2021 (Bioinformatics Top conference, In press).
  9. Mai S#, Zheng S#, Yuedong Yang*, Hu H*. Communicative Message Passing for Inductive Relation Reasoning. AAAI 2021(AI Top conference, CCF-A, acceptance=21%) arxiv 2012.08911.


  10. 2020

  11. Zheng S#, Rao J#, Song Y, Zhang J, Xiao X, Fang EF, Yuedong Yang*, Niu Z*. PharmKG: A Dedicated Knowledge Graph Benchmark for Biomedical Data Mining. Brief In Bioinfo 2020 (IF=9.0); doi:10.1093/bib/bbaa344.
  12. Xuan Lv, Zhiguang Chen, Yutong Lu*, and Yuedong Yang*. An End-to-end Oxford Nanopore Basecaller Using Convolution-augmented Transformer. BIBM 2020 (Bioinformatics top conference, acceptance=19.4%) bioRxiv 2020.11.09.374165.
  13. Yuansong Zeng, Xiang Zhou, Jiahua Rao, Yutong Lu*, Yuedong Yang*. Accurately Clustering Single-cell RNA-seq data by Capturing Structural Relations between Cells through Graph Convolutional Network. BIBM 2020 (accepted) bioRxiv 2020.09.02.278804 .
  14. Zheng S, Zhang J, Rao J, Xiao X, Menpes-Smith W, JY Chen, Yuedong Yang* and Z Niu*. Biomedical Knowledge Graph of COVID-19: Construction and Applications. SIGKDD 2020 (BioKDD workshop).
  15. Ying Song# , Shuangjia Zheng# , Zhangming Niu , Zhang-hua Fu , Yutong Lu and Yuedong Yang*. Communicative Representation Learning on Attributed Molecular Graphs. IJCAI 2020 (AI Top conference, DOI: 10.24963/ijcai.2020/388, CCF-A, Acceptance rate=12.6%).
  16. Xiang Zhou, Hua Chai, Huiying Zhao, Ching-Hsing Luo*, Yuedong Yang*. Imputing missing RNA-seq data from DNA methylation by using transfer learning based neural network. Gigascience 2020 (IF=6.0; doi:10.1093/gigascience/giaa076).
  17. Ke Y, Rao J, Zhao H, Lu Y, Xiao N*, Yuedong Yang*. Accurate Prediction of Genome-wide RNA Secondary Structure Profile Based on Extreme Gradient Boosting. Bioinformatics. 2020 May 28: 36(17):4576-82. doi: 10.1093/bioinformatics/btaa534 .
  18. Lv X, Chen J, Lu Y, Chen Z, Xiao N*, Yuedong Yang*. Accurately Predicting Mutation-Caused Stability Changes from Protein Sequences Using Extreme Gradient Boosting. J Chem Inf Model. 2020 Apr 27;60(4):2388-2395. doi: 10.1021/acs.jcim.0c00064 .
  19. Cai Y, Li X, Sun Z, Lu Y, Zhao H, Hanson J, Paliwal K, Litfin T, Zhou Y*, Yuedong Yang*. SPOT-Fold: Fragment-Free Protein Structure Prediction Guided by Predicted Backbone Structure and Contact Map. J Comput Chem. 2020 Mar 30;41(8):745-750. doi: 10.1002/jcc.26132.
  20. Zheng S, Rao J, Zhang Z, Xu J*, Yuedong Yang*. Predicting Retrosynthetic Reactions Using Self-Corrected Transformer Neural Networks. J Chem Inf Model. 2020 Jan 27;60(1):47-55. doi: 10.1021/acs.jcim.9b00949 .
  21. Chen S, Sun Z, Lin L, Liu Z, Liu X, Chong Y, Lu Y, Zhao H*, Yuedong Yang*. To Improve Protein Sequence Profile Prediction through Image Captioning on Pairwise Residue Distance Map. J Chem Inf Model. 2020 Jan 27;60(1):391-399. doi: 10.1021/acs.jcim.9b00438.
  22. Zheng S#, Y Li#, S Chen, J Xu* and Yuedong Yang*. Predicting Drug Protein Interaction using Quasi-Visual Question Answering System. Nature Machine Intelligence 2020;2(1):134-140.

  23. 2019

  24. Chen K, Lu Y, Zhao H, Yuedong Yang*. Predicting the change of exon splicing caused by genetic variant using support vector regression. Hum Mutat. 2019 Sep;40(9):1235-1242. doi: 10.1002/humu.23785.
  25. Chen P, Ke Y, Lu Y, Du Y, Li J, Yan H, Zhao H, Zhou Y, Yuedong Yang*. DLIGAND2: an improved knowledge-based energy function for protein-ligand interactions using the distance-scaled, finite, ideal-gas reference state. J Cheminform. 2019 Aug 7;11(1):52. doi: 10.1186/s13321-019-0373-4.

  26. 2018 & before

  27. Atack JM#, Yuedong Yang#, Seib KL, Zhou Y, Jennings MP. A survey of Type III restriction-modification systems reveals numerous, novel epigenetic regulators controlling phase-variable regulons; phasevarions. Nucleic Acids Res. 2018 Apr 20;46(7):3532-3542. doi: 10.1093/nar/gky192. PMID: 29554328.
  28. Hanson J, Paliwal K, Litfin T, Yuedong Yang*, Zhou Y*. Accurate prediction of protein contact maps by coupling residual two-dimensional bidirectional long short-term memory with convolutional neural networks. Bioinformatics. 2018 Dec 1;34(23):4039-4045. doi: 10.1093/bioinformatics/bty481. PMID: 29931279.
  29. G Taherzadeh, Y Zhou, AW Liew, Yuedong Yang*. Structure-based prediction of protein-peptide binding regions using Random Forest. Bioinformatics 2018 Feb 1;34(3):477-484.
  30. J Gao, Yuedong Yang*, Y Zhou*. Grid-based prediction of torsion angle probabilities of protein backbone and its application to discrimination of protein intrinsic disorder regions and selection of model. BMC bioinformatics 2018;19 (1), 29.
  31. H. Zhao*, Yuedong Yang*, Y. Lu, M. Mort, D. N. Cooper, and Y. Zhou*. Quantitative mapping of genetic similarity in human heritable diseases by shared mutations. Human Mutation 2018. Hum Mutat. 2018 Feb;39(2):292-301.
  32. Yuedong Yang , J Gao, J Wang, R Heffernan, J Hanson, K Paliwal, and Y Zhou. Sixty-five years of long march in protein secondary structure prediction: the final stretch? Brief in Bioinformatics 2018 May 1;19(3):482-494. (ESI highly cited)
  33. I Guruge, G Taherzadeh, J Zhan, Y Zhou*, Yuedong Yang*. B‐factor profile prediction for RNA flexibility using support vector machines. J Comput Chem 2018;39(8), 407-411
  34. H Zhao*, DR Nyholt, YH Yang, J Wang, Yuedong Yang*. Improving the detection of pathways in genome-wide association studies by combined effects of SNPs from Linkage Disequilibrium blocks. Scientific Rep 2017. 7,3512.
  35. Heffernan R, Yuedong Yang*, Paliwal K, Zhou Y*. Capturing Non-Local Interactions by Long Short Term Memory Bidirectional Recurrent Neural Networks for Improving Prediction of Protein Secondary Structure, Backbone Angles, Contact Numbers, and Solvent Accessibility. Bioinformatics. 2017 Sep 15;33(18):2842-2849
  36. T Litfin, Y Zhou*, Yuedong Yang*. SPOT-Ligand 2: Improving structure-based virtual screening by binding-homology search on an expanded structural template library. Bioinformatics 2017 Apr 15;33(8):1238-1240.
  37. Yuedong Yang, X Li, H Zhao, J Zhan, J Wang, and Y Zhou. Genome-scale characterization of RNA tertiary structures and their functional impact by RNA solvent accessibility prediction. RNA 2017. 23(1), 14-22 .
  38. J Hanson*, Yuedong Yang*, K Paliwal, and Y Zhou*. Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks. Bioinformatics 2017. 33 (5): 685-692.(ESI highly cited)
  39. Y Yang, R Heffernan, K Paliwal, J Lyons, A Dehzangi, A Sharma, J Wang, A Satter, Y Zhou*. SPIDER2: A Package to Predict Secondary Structure, Accessible Surface Area, and Main-Chain Torsional Angles by Deep Neural Networks. Prediction of Protein Secondary Structure, 2017; 55-63 (Book chapter, cited:110)
  40. J Gao, Yuedong Yang*, Y Zhou*. Predicting the errors of predicted local backbone angles and nonlocal solvent-accessibilities of proteins by deep neural networks. Bioinformatics 2016. 32 (24): 3768-3773.
  41. H Zhao, D Fan, D Nyholt, Yuedong Yang*. Enrichment of SNPs in functional categories reveals genes affecting complex traits. Human Mutation 2016 Aug;37(8):820-6.
  42. R. Heffernan, K. Paliwal, J. Lyons, A. Dehzangi, A. Sharma, J. Wang, A. Sattar, Y. Zhou* and Yuedong Yang*. Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins. Bioinformatics 2016; 32(6):843-9.
  43. G Taherzadeh, Y Zhou, AW Liew, Yuedong Yang*. Sequence-based Prediction of Protein-Carbohydrate Binding Sites Using Support Vector Machines. J Chem Inf Model 2016; 56(10), 2115-2122.
  44. Yuedong Yang, J Zhan, Y Zhou. SPOT-Ligand: Fast and effective structure-based virtual screening by binding homology search according to ligand and receptor similarity. J Comp Chem 2016 Jul 5;37(18):1734-9.
  45. Yuedong Yang* and Y Zhou*. Effective ab initio protein conformational sampling based on predicted torsion angles. J Comp Chem 2016; 37(11):976-80.
  46. R. Heffernan, K. Paliwal, J. Lyons, A. Dehzangi, A. Sharma, J. Wang, A. Sattar, Yuedong Yang* and Y. Zhou*. Improving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning. Scientific Reports 2015; 5:11476 (Cited:240; ESI Highly cited)
  47. J. Lyons, A. Dehzangi*, R. Heffernan, Yuedong Yang*, Y. Zhou, A. Sharma, J. Wang, K. Paliwal*. Advancing the accuracy of protein fold recognition by utilizing profiles from hidden markov models. IEEE T Nanobioscience 2015, 14(7), 761-772.
  48. H Zhao, Yuedong Yang*, M Itzsteinc, Y Zhou*. Carbohydrate-binding protein identification by coupling structural similarity search with binding affinity prediction. J Comput Chem. 2014 Nov 15;35(30):2177-83. doi: 10.1002/jcc.23730. (Cover Article)
  49. J Lyons, A Dehzangi, R Heffernan, A Sharmaa, K Paliwal, A Sattar, Y Zhou*, Yuedong Yang*. Predicting backbone Calpha angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network. J Comput Chem. 2014; 35(28):2040-6. doi: 10.1002/jcc.23718.
  50. H Zhao, W Wang, Yaoqi Zhou*, and Yuedong Yang*. Predicting DNA-Binding Proteins and Binding Residues by Complex Structure Prediction and Application to Human Proteome. Plos One 2014; 9(5), e96694.
  51. Zhao H#, Yuedong Yang#, Janga SC, Kao CC, Zhou Y. Prediction and validation of the unexplored RNA-binding protein atlas of the human proteome. Proteins. 2014 Apr;82(4):640-7.
  52. Zhao H#, Yuedong Yang#, Zhou Y. Prediction of RNA binding proteins comes of age from low resolution to high resolution. Mol Biosyst. 2013 Aug 27;9(10):2417-25.
  53. Zhao H#, Yuedong Yang#, Hai Lin, Xinjun Zhang, Matthew Mort, David N. Cooper, Yunlong Liu*, and Yaoqi Zhou*. DDIG-in: discriminating between disease-associated and neutral non-frameshifting micro-indels. Genome Biology. 2013 Mar 13;14(3):R23.(IF=14)
  54. Yuedong Yang, Zhan J, Zhao H, Zhou Y. A new size-independent score for pairwise protein structure alignment and its assessment by structure classification and nucleic-acid binding prediction. Proteins. 2012 Aug;80(8):2080-8.
  55. Lu T#, Yuedong Yang#, Yao B, Liu S, Zhou Y, Zhang C. Template-based structure prediction and classification of transcription factors in Arabidopsis thaliana. Protein Sci. 2012 Mar 30; 21(6):828-838
  56. Zhao H#, Yuedong Yang#, Zhou Y. Highly accurate and high-resolution function prediction of RNA binding proteins by fold recognition and binding affinity prediction. RNA Biology. 2011 Nov 1;8(6).
  57. Yuedong Yang, Faraggi E, H Zhao, Zhou Y. Improving protein fold recognition and template-based modeling by employing probabilistic-based matching between predicted one-dimensional structural properties of the query and corresponding native properties of templates. Bioinformatics 2011 Aug 1;27(15):2076-82. (ESI highly cited)
  58. Zhao H#, Yuedong Yang#, Zhou Y. Structure-based prediction of RNA-binding domains and RNA-binding sites and application to structural genomics targets. Nucleic Acids Res. 2011 Apr;39(8):3017-25. (IF=11)
  59. Dai L#, Yuedong Yang#, Kim H and Zhou Y. Improving computational protein design by using structure-derived sequence profile. Proteins. 2010 Aug 1;78(10):2338-48.
  60. Zhao H#, Yuedong Yang#, Zhou Y. Structure-based prediction of DNA-binding proteins by structural alignment and a volume-fraction corrected DFIRE-based energy function. Bioinformatics. 2010 Aug 1;26(15):1857-63.
  61. Faraggi E#, Yuedong Yang#, Zhang S, Zhou Y. Predicting continuous local structure and the effect of its substitution for secondary structure in fragment-free protein structure prediction. Structure (Cell Press). 2009 Nov 11;17(11):1515-27.
  62. Xu B#, Yuedong Yang#, Liang H, Zhou Y. An all-atom knowledge-based energy function for protein-DNA threading, docking decoy discrimination, and prediction of transcription factor binding profiles. Proteins. 2009 Aug 15;76(3):718-30.
  63. Yuedong Yang, Zhou Y. Specific interactions for ab initio folding of protein terminal regions with secondary structures. Proteins. 2008 Aug;72(2):793-803. (Cited: 210))
  64. Yuedong Yang, Zhou Y. Ab initio folding of terminal segments with secondary structures reveals the fine difference between two closely related all-atom statistical energy functions. Protein Sci. 2008 Jul;17(7):1212-9. (Cited: 120)
  65. Yuedong Yang, Liu H. Genetic algorithms for protein conformation sampling and optimization in a discrete backbone dihedral angle space. J Comput Chem. 2006 Oct;27(13):1593-602.
  66. Ding H#, Yuedong Yang#, Zhang J, Wu J, Liu H, Shi Y. Structural basis for SUMO-E2 interaction revealed by a complex model using docking approach in combination with NMR data. Proteins. 2005 Dec 1;61(4):1050-8.