Overview

See My Google Scholar for the full publication list (Totally >200 articles; Cited>10000; H-index>50), and My Github repository for > 50 publicly available source codes and packages.

Published on Nature Mach Intell (*2), Nat Comput Sci, Chem (Cell sister journal, IF=26), Nature Comm (*2), Patterns, Elife, Nucleic Acids Res(*7, IF=17), Brief Bioinfo(*10+, IF=14), Bioinformatics(*10+, IF=6.9), J Chem Inf Model(*10+,IF=6.2), J Cheminfo (*3,IF=8.5)

& Top conferences on AI (IJCAI*3, AAAI) and Biomedicine (RECOMB, BIBM*10+, MICCAI), etc.

(# for co-first author; * for corresponding author; and First authors from collaboration groups are labelled Italic)

Book chapters & others

  1. Interview with Patterns 2022: 3(12);100653. Integrating supercomputing and artificial intelligence for life science.
  2. Yuan Q, Yuedong Yang*. Chapter 9: Sequence-Based Predictions of Residues that Bind Proteins and Peptides. Machine Learning in Bioinformatics of Protein Sequences 2023; 237-263
  3. H. Zhao, G. Taherzadeh, Y. Zhou*, and Yuedong Yang*, “Computational prediction of carbohydrate-binding proteins and binding sites.”, in Current Protocols in Protein Science, edited by G. Taylor, Chapter 2, in press, Wiley, Hoboken, NJ, 2018.
  4. Yuedong Yang*, R. Heffernan, K. Paliwal, J. Lyons, A. Dehzangi, A. Sharma, J. Wang, A. Sattar, and Y. Zhou*. SPIDER2: a package to predict secondary structure, accessible surface area, and main-chain torsional angles. Methods in Molecular Biology 2017; Predicting Protein Secondary Structure 1484:55-63.
  5. Yuedong Yang, H. Zhao, J. Wang, and Y. Zhou. SPOT-Seq: Predicting protein-RNA complex structure and RNA-binding function by fold recognition and binding affinity prediction. Methods in Molecular Biology (Protein Structure Prediction). 119-130, 2014.

Preprints

  1. J Rao, S Zheng, Y Song, J Chen, C Li, J Xie, H Yang, H Chen, Yuedong Yang*. MolRep: A Deep Representation Learning Library for Molecular Property Prediction. bioRxiv, 2022.06. 05.494905.
  2. S Zheng, Y Song, Z Pan, C Li, L Song, Yuedong Yang*. Molecular Attributes Transfer from Non-Parallel Data. arXiv 2021; arXiv:2111.15146

Selected Publications

2024

  1. [STAR1] S Chen, J Xie, R Ye, DD Xu, Yuedong Yang*. Structure-Aware Dual-Target Drug Design through Collaborative Learning of Pharmacophore Combination and Molecular Simulation. Chemical Science 2024 .
  2. [STAR2] S Zheng, J Rao, J Zhang, C Li, Yuedong Yang*. Cross-modal Graph Contrastive Learning with Cellular Images. Advanced Science 2024; doi: 10.1002/advs.202404845.
  3. [STAR2] Q Yuan; C Tian; Y Song; P Ou; M Zhu; H Zhao*; Yuedong Yang*. GPSFun: geometry-aware protein sequence function predictions with language models. Nucleic Acids Res 2024:gkae381.
  4. [STAR2] J Rao, J Xie, Q Yuan, D Liu, Z Wang, Y Lu*, S Zheng*, Yuedong Yang*. A Variational Expectation-Maximization Framework for Balanced Multi-scale Learning of Protein and Drug Interactions. Nature Comm 2024;15:4476.
  5. [STAR1] Q Yuan, C Tian, Yuedong Yang*. Genome-scale annotation of protein binding sites via language model and geometric deep learning Elife 2024; 13:RP93695.
  6. [STAR2] Y Zeng, M Luo, N Shangguan, P Shi, J Feng, J Xu, K Chen, Y Lu, W Yu, and Yuedong Yang*. Deciphering Cell Types by Integrating scATAC-seq Data with Genome Sequences Nature Computational Science 2024;4:285–298 .
  7. S Lin, J Yong, L Zhang, X Chen, L Qiao, W Pan, Yuedong Yang*, H Zhao*. Applying image features of proximal paracancerous tissues in predicting prognosis of patients with hepatocellular carcinoma. Comput Biol Med 2024;108365.
  8. [STAR1]K Chen, Y Zhou, M Ding, Y Wang, Z Ren, Yuedong Yang*. Self-supervised learning on millions of pre-mRNA sequences improves sequence-based RNA splicing prediction. Brief Bioinfo 2024;bbae163
  9. JC Xie, Y Wang, J Rao, S Zheng, Yuedong Yang*. Self-supervised Contrastive Molecular Representation Learning with Chemical Synthesis Knowledge Graph. J Chem Inf Model 2024;64(6):1945–1954 .
  10. M Ding, K Chen, Yuedong Yang*, H Zhao*. Prioritizing the pathogenicity of genomic variants through DNA, RNA, and protein-level features. Hum Genet 2024 .
  11. JC Xie, J Rao, JJ Xie, H Zhao, Yuedong Yang. Predicting Disease-gene Associations through Self-supervised Mutual Infomax Graph Convolution Network. Comput Biol Med 2024;170:108048.
  12. JJ Xie, S Chen, J Lei*, and Yuedong Yang*. DiffDec: Structure-Aware Scaffold Decoration with an End-to-End Diffusion Model. J Chem Inf Model 2024;64(7):2554–2564 .

2023

  1. [STAR1]J Rao, Z Shan, L Liu, Y Zhou, Yuedong Yang*. Retrieval-based Knowledge Augmented Vision Language Pre-training. ACM MM 2023 (CCF-A conference).
  2. D Liu, S Chen, S Zheng, S Zhang, Yuedong Yang. SE(3) Equivalent Graph Attention Network as an Energy-Based Model for Protein Side Chain Conformation. BIBM 2023 (Conference article)
  3. J Zheng, Yuedong Yang*, Zhiming Dai*. Subgraph extraction and graph representation learning for single cell Hi-C imputation and clustering. Brief Bioinfo 2023: bbad379 .
  4. W Jiang, P Wang, Q Zhou, Q Lin, Y Yao, X Huang, X Tan, S Yang, W Ye, Yuedong Yang* and Y Bao*. Tri©DB: an integrated platform of knowledgebase and reporting system for cancer precision medicine. J Trans Med 2023.
  5. X Wang, M Qi, H Zhang, Yuedong Yang*, H Zhao*. Genome-wide Association and Mendelian Randomization analysis provide insights into the shared Genetic Architecture between High-Dimensional Electrocardiographic Features and Ischemic Heart Disease. Hum Genet 2023.
  6. Wang J; Chen S; Yuan Q; Chen J; Li D; Wang L; Yuedong Yang. Predicting the Effects of Mutations on Protein Solubility Using Graph Convolution Network and Protein Language Model Representation. J Comp Chem 2023 .
  7. Y Song, Q Yuan, H Zhao, Yuedong Yang*. Accurately identifying nucleic-acid-binding sites through geometric graph learning on language model predicted structures. Brief Bioinfo 2023:bbad360 .
  8. Y Wang, Z Li, J Rao,Yuedong Yang*, Z Dai*. Gene based message passing for drug repurposing. iScience 2023; 26(9):107663 .
  9. [STAR2] Lin S, Zhang H, Qi M,DN Cooper, Yuedong Yang*, YH Yang*, H Zhao*. Inferring the genetic relationship between brain imaging-derived phenotypes and risk of complex diseases by Mendelian randomization and genome-wide colocalization. Neuroimage 2023.
  10. [STAR1] F Zheng, L Wang, Y Pang, Z Chen, Y Lu, Yuedong Yang*, J Wu*. Shocksurv: A Machine Learning Model to Accurately Predict 28-Day Mortality for Septic Shock Patients in the Intensive Care Unit. Biomed Signal Process Control 2023. Preprint .
  11. Liu H, Fan Z, Lin J, Yuedong Yang*, Ran T*, Chen H*. The recent progress of deep-learning-based in silico prediction of drug combination. Drug Discovery Today 2023 .
  12. Y Song, Q Yuan, S Chen, K Chen, Y Zhou, Yuedong Yang*. Fast and accurate protein intrinsic disorder prediction by using a pretrained language model. Brief Bioinfo 2023;bbad173.
  13. [STAR1] Y Zeng, Z Wei, Q Yuan, S Chen, W Yu, Y Lu, J Gao, Yuedong Yang*. Identifying B-cell epitopes using AlphaFold2 predicted structures and pretrained language model. Bioinformatics 2023; btad187.
  14. 宋益东,袁乾沐,杨跃东. 深度学习在蛋白质功能预测中的应用. 合成生物学 2023；DOI:10.12211/2096-8280.2022-078.
  15. [STAR2] Q Yuan, JJ Xie, JC Xie, H Zhao, Yuedong Yang*. Fast and accurate protein function prediction from sequence through pretrained language model and homology-based label diffusion. Brief Bioinfo 2023;bbad117.
  16. [STAR1] Zeng Y, Yin R, Luo M, Chen J, Pan Z, Lu Y, Yu W, Yuedong Yang*. Identifying Spatial Domain by Adapting Transcriptomics with Histology through Contrastive Learning. Brief Bioinfo 2023; bbad048.
  17. H Chen#, H Zhang#, S Wen, X Xiu, D You, H Zhao, D Wang, Yuedong Yang*, Y Shu*. Mendelian randomization suggests a potential causal effect of eosinophil count on influenza vaccination responsiveness. J Med Virol 2023 .

2022

  1. [STAR2] Rao J, Zheng S, Yuedong Yang*. Quantitative Evaluation of Explainable Graph Neural Networks for Molecular Property Prediction. Patterns 2022;100628.
  2. Tan Y, Dai L, Huang W, Guo Y, Zheng S, Lei J, Chen H*, Yuedong Yang*. DRlinker: Deep Reinforcement Learning for Optimization in Fragment Linking Design. J Chem Inf Model 2022.
  3. [STAR2] Qiu J#, Xie J#,Su S, Gao Y, Meng H, Yuedong Yang*, Liao K*. Selective functionalization of hindered meta-C–H bond of o-alkylaryl ketones promoted by automation and deep learning. Chem 2022 [PDF] .
  4. Q Yuan, S Chen, Y Wang, H Zhao, Yuedong Yang*. Alignment-free metal ion-binding site prediction from protein sequence through pretrained language model and multi-task learning. Brief Bioinfo 2022;bbac444.
  5. [STAR1] Xiu X#, Zhang H#, Xue A, Cooper DN, Yan L, Yuedong Yang*, Yang YH*, Zhao H*. Genetic evidence for a causal relationship between type 2 diabetes and peripheral artery disease in both Europeans and East Asians. BMC Medicine 2022;20:300.
  6. [STAR2]Zheng S, Tan Y, Wang Z, Li C, Zhang Z, Sang X, Chen H, Yuedong Yang*. Accelerated rational PROTAC design via deep learning and molecular simulations. Nature Machine Intelligence 2022;4:739–748 [PDF].
  7. [STAR1] Chen P, Chen J, Yan H, Mo Q, Xu Z, Liu J, Zhang W, Yuedong Yang*, Lu Y*. Improving Material Property Prediction by Leveraging the Large-Scale Computational Database and Deep Learning. J. Phys. Chem. C 2022;126(38):16297–16305 (Cover Article).
  8. [STAR2]Zeng Y, Wei Z, Yu W, Yin R, Li B, Tang Z, Lu Y, Yuedong Yang*. Spatial Transcriptomics Prediction from Histology jointly through Transformer and Graph Neural Networks. Brief Bioinfo 2022; bbac297.
  9. [STAR2] Zheng S, T Zeng, C Li, B Chen, CW Coley, Yuedong Yang*, Ruibo Wu*. Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP. Nat Comm 2022;13:3342.
  10. Zheng S, S Mai, Y Sun, H Hu*, Yuedong Yang*. Subgraph-aware Few-Shot Inductive Link Prediction via Meta-Learning. IEEE TKDE 2022; DOI: 10.1109/TKDE.2022.3177212 . [PDF].
  11. Zeng Y, Wei Z, Zhong F, Pan Z, Lu Y, Yuedong Yang*. A Parameter-free Deep Embedded Clustering Method for Single-cell RNA-seq Data. Brief Bioinfo 2022; bbac172. [PDF].
  12. Wang X, Zhou X, Rao J, Zhang Z, and Yuedong Yang. Imputing DNA Methylation by Transferred Learning Based Neural Network. J Comput Sci Tech 2022; 37(2):320.
  13. Zhang H, Xiu X, Yuedong Yang*, YH Yang*, H Zhao*. Identification of putative causal relationships between type 2 diabetes and biomarkers in East Asians by Mendelian randomization. Am J Epidem 2022;191(11):1867-76 .
  14. [STAR1] Wang P, Zheng S, Jiang Y, Li C, Liu J, Wen C, Atanas P, Qian D*, Chen H*, Yuedong Yang*. Structure-aware multi-modal deep learning for drug-protein interactions prediction. J Chem Inf Model 2022; 62(5):1308–1317. [PDF].
  15. [STAR1] Chen K, Zhao H, Yuedong Yang*. Capturing large genomic contexts for accurately predicting enhancer-promoter interactions. Brief Bioinfo 2022; bbab577 . [PDF].
  16. [STAR2] Yuan Q, Chen S, Rao J, Zheng S, Zhao H, Yuedong Yang*. AlphaFold2-aware protein-DNA binding site prediction using graph transformer. Brief Bioinfo 2022; bbab564 . [PDF].
  17. [STAR1] Zeng Y, Zhou X, Pan Z, Lu Y*, Yuedong Yang*. A Robust and Scalable Graph Neural Network for Accurate Single Cell Classification. Brief Bioinfo 2022; bbab570. [PDF].
    18. Peer Reviewed Conference Articles
  18. [STAR1] Rao J, Zheng S, Mai S, Yuedong Yang*. Communicative Subgraph Representation Learning for Multi-Relational Inductive Drug-Gene Interaction Prediction. IJCAI 2022 .
  19. Wang X, Qi M, Dong C, Zhang H, Yuedong Yang*, and Zhao H*. Accurately Identifying Coronary Atherosclerotic Heart Disease through Merged Beats of Electrocardiogram. BIBM 2022.
  20. Wang X, Zhang H, Xiu X, Qi M, Yuedong Yang*, and Huiying Zhao*. Genetic and phenotypic relationships between coronary atherosclerotic heart disease and electrocardiographic traits. BIBM 2022.
  21. Pan Z, Lin Y, Zhang H, Zeng Y, Yu W, and Yuedong Yang*. A Meta-learning based Graph-Hierarchical Clustering Method for Single Cell RNA-Seq Data. BIBM 2022.
  22. Zhong F, Zeng Y, Liu Y, and Yuedong Yang*. SCdenoise: a reference-based scRNA-seq denoising method using semi-supervised learning. BIBM 2022.

2021

  1. [STAR2] Yuan Q, Chen J, Zhao H, Zhou Y*, Yuedong Yang*. Structure-aware protein-protein interaction site prediction using deep graph convolutional network. Bioinformatics 2021; btab643.
  2. Zheng S, Z Lei, H Ai, H Chen, D Deng*, Yuedong Yang*. Deep Scaffold Hopping with Multi-modal Transformer Neural Networks. J Cheminfo 2021; 13:87.
  3. Zhang Z, Chai H, Yi Wang, Pan Z, Yuedong Yang*. Cancer survival prognosis with Deep Bayesian Perturbation Cox Network. Comput Biol Med 2021 .
  4. Yuan S, Yuedong Yang*, Hu R*. The Unfolding Multiomics Landscapes of HBV (Hepatitis B Virus)-Host Interactions. J Hepatology 2021 (IF=25).
  5. Huang Z, Li L, Zhang X, Song Y, Chen J, Zhao H, Chong Y*, Wu H, Yuedong Yang*, Shen J*, Zha Y*. A coarse-refine segmentation network for COVID-19 CT images. IET Image Processing 2021; 16(2):333-343.
  6. Chai H, Xia L, Zhang L, Yang J, Zhang Z, Qian X, Yuedong Yang*, Pan W*. An adaptive transfer-learning based deep Cox neural network for hepatocellular carcinoma prognosis prediction. Front Oncology 2021.
  7. Liu W#, Chen L#, Chen Ken#, Wu J#, Peng R, Tang Y, Chen J, Yuedong Yang*, P Li*, Z Huang*. Identification of novel single nucleotide variants with potential of mediating malfunction of microRNA in congenital heart disease. Front Cardiovasc Med 2021.
  8. Chai H, Zhang Z, Wang Y, Yuedong Yang*. Predicting bladder cancer prognosis by integrating multi-omics data through a transfer learning-based Cox proportional hazards network. CCF Trans HPC 2021 .
  9. Z Sun, S Zheng, H Zhao, Niu Z, Lu Y, Pan Y, Yuedong Yang*. To improve the predictions of binding residues with DNA, RNA, carbohydrate, and peptide via multiple-task deep neural networks. IEEE TCBB 2021; TCBB.2021.3118916 .
  10. [STAR2] Zhang H, Xiu X, Xue A, Yuedong Yang*, YH Yang*, H Zhao*. The putative causal effect of type 2 diabetes in risk of cataract: a Mendelian randomization study in East Asian. Int J Epidemiol 2021; 50(6):2024-2037.(IF=7.7).
  11. Zhou X, Chai H, Zeng Y, Zhao H, Yuedong Yang*. scAdapt: Virtual adversarial domain adaptation network for single cell RNA-seq data classification across platforms and species. Brief Bioinfo 2021, bbab281 & RECOMB 2021 (Bioinformatics Top conference)[PDF].
  12. [STAR1] Chai H, Zhou X, Zhang Z, Rao J, Zhao H, Yuedong Yang*. Integrating multi-omics data with deep learning for predicting cancer prognosis. Comput Biol Med 2021; 134:104481 [PDF].
  13. [STAR2] Rao J, Zhou X, Lu Y, Zhao H, Yuedong Yang*. Imputing Single-cell RNA-seq data by combining Graph Convolution and Autoencoder Neural Networks. iScience 2021; 24(5):102393; [PDF].
  14. Zheng F, Li L, Zhang X, Song Y, Huang Z, Chong Y, Chen Z, Zhu H, Wu J, Chen W, Lu Y, Yuedong Yang*, Zha Y*, Zhao H*, Shen J*. Accurately Discriminating COVID-19 from Viral and Bacterial Pneumonia According to CT Images Via Deep Learning. Interdiscip Sci-Comput Life Sci. 2021 Feb 27:1–13. [PDF] .
  15. Wang J, Zheng S, Chen J, Yuedong Yang*. Meta Learning for Low Resource Molecular Optimization. J Chem Inf Model 2021; [PDF].
  16. [STAR1] Song Y, Zheng S, Li L, Zhang X, Zhang X, Huang Z, Chen J, Zhao H, Jie Y, Wang R, Chong Y*, Shen J*, Zha Y*, Yuedong Yang*. Deep learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) with CT images. IEEE TCBB 2021;18(6):2775-2780. [PDF].
  17. [STAR1] 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; 13(1):7 [PDF].
    18. Peer Reviewed Conference Articles
  18. [STAR2] Chen J#, Zheng S#, Yuedong Yang*. Learning Attributed Graph Representation with Communicative Message Passing Transformer. IJCAI 2021 arxiv (AI Top conference, CCF-A, Acceptance rate=13.9%) [PDF].
  19. 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.
  20. Huang Z, H Chai, R Wang, H Wang, Yuedong Yang*, H Wu*. Integration of Patch Features through Self-Supervised Learning and Transformer for Survival Analysis on Whole Slide Images. MICCAI 2021 (Medical Image Top Conference) [PDF] .
  21. Zhang P, Zheng S, Chen J, Zhou Y*, and Yuedong Yang*. DeepANIS: Predicting antibody paratope from concatenated CDR sequences by integrating bidirectional long-short-term memory and transformer neural networks. BIBM 2021(Acceptance rate=19.6%. CCF-B).
  22. [STAR1] Chen S, Zhang S, Li X, Liu Y, and Yuedong Yang*. SEGEM: a Fast and Accurate Automatic Protein Backbone Structure Modeling Method for Cryo-EM. BIBM 2021.
  23. Y Wang, Z Zhang, H Chai, and Yuedong Yang*. Multi-omics Cancer Prognosis Analysis Based on Graph Convolution Network. BIBM 2021.
  24. H Zhang, J Wei, Z Liu, X Liu, Y Chong, Y Lu, H Zhao, and Yuedong Yang*. DGAT-onco: A differential analysis method to detect oncogenes by integrating functional information of mutations. BIBM 2021; bioRxiv.

2020

  1. [STAR2] 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 Bioinfo 2020 (IF=9.0); doi:10.1093/bib/bbaa344; [PDF].
  2. [STAR1] Lv X, Z Chen, Y Lu*, and Yuedong Yang*. An End-to-end Oxford Nanopore Basecaller Using Convolution-augmented Transformer. BIBM 2020:337-342(Bioinformatics top conference, acceptance=19.4%) bioRxiv 2020.11.09.374165 [PDF].
  3. [STAR1] Zeng Y, Zhou X, Rao J, Lu Y*, Yuedong Yang*. Accurately Clustering Single-cell RNA-seq data by Capturing Structural Relations between Cells through Graph Convolutional Network. BIBM 2020;519-522 bioRxiv 2020.09.02.278804 .
  4. 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).
  5. [STAR2] Song Y# , S Zheng# , Z Niu , Z Fu , Y 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%) [PDF].
  6. Zhou X, H Chai, H Zhao, CH 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) [PDF].
  7. [STAR2] 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 [PDF].
  8. 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 [PDF].
  9. [STAR1] 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 [PDF].
  10. [STAR1] 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 [PDF].
  11. [STAR2] 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 [PDF].
  12. [STAR1] 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 [PDF].

2019

  1. 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 [PDF].
  2. [STAR1] 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 [PDF].

2018 & before

  1. [STAR1] 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. [PDF].
  2. 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.
  3. [STAR2] Taherzadeh G, 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.
  4. 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.
  5. [STAR1] Zhao H*, 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.
  6. [STAR2] 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 Bioinfo 2018 May 1;19(3):482-494. (ESI highly cited). [ PDF ]
  7. Guruge I, 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 .
  8. 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.
  9. [STAR1] 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. (ESI highly cited)
  10. 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.
  11. [STAR2] 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.
  12. [STAR1]Hanson J*, 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) .
  13. Yuedong 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:130).
  14. Gao J, 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.
  15. Zhao H, 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.
  16. [STAR1] Heffernan R, 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.
  17. 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.
  18. [STAR2] 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.
  19. Yuedong Yang* and Y Zhou*. Effective ab initio protein conformational sampling based on predicted torsion angles. J Comp Chem 2016; 37(11):976-80.
  20. [STAR2]Heffernan R, 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).
  21. Lyons J, 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.
  22. Zhao H, 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).
  23. [STAR2] 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.
  24. Zhao H, 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.
  25. 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.
  26. 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.
  27. [STAR2] 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).
  28. [STAR1] 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. (Cited: 80)
  29. 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.
  30. 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).
  31. [STAR2] 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;Cited: 320).
  32. [STAR2] 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).
  33. 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.
  34. 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.
  35. [STAR1] 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.
  36. 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.
  37. [STAR2] 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: 250)).
  38. 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: 170).
  39. 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.
  40. 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.