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2020 – today
- 2023
[j92]Chun-Qiu Xia
, Shi-Hao Feng, Ying Xia, Xiaoyong Pan, Hong-Bin Shen:
Leveraging scaffold information to predict protein-ligand binding affinity with an empirical graph neural network. Briefings Bioinform. 24(1) (2023)- [j91]Pei-Dong Zhang, Chun-Qiu Xia, Hong-Bin Shen:
High-accuracy protein model quality assessment using attention graph neural networks. Briefings Bioinform. 24(2) (2023) - [j90]Mei-Hong Pan, Hong-Yi Xin, Chun-Qiu Xia, Hong-Bin Shen:
Few-shot classification with task-adaptive semantic feature learning. Pattern Recognit. 141: 109594 (2023) - 2022
- [j89]Hui Li, Zhaohong Deng, Haitao Yang, Xiaoyong Pan, Zhisheng Wei, Hong-Bin Shen, Kup-Sze Choi, Lei Wang, Shitong Wang, Jing Wu:
circRNA-binding protein site prediction based on multi-view deep learning, subspace learning and multi-view classifier. Briefings Bioinform. 23(1) (2022) - [j88]Yanlun Tu, Houchao Lei, Hong-Bin Shen, Yang Yang:
SIFLoc: a self-supervised pre-training method for enhancing the recognition of protein subcellular localization in immunofluorescence microscopic images. Briefings Bioinform. 23(2) (2022) - [j87]Ge Wang, Min-Qi Xue, Hong-Bin Shen, Ying-Ying Xu:
Learning protein subcellular localization multi-view patterns from heterogeneous data of imaging, sequence and networks. Briefings Bioinform. 23(2) (2022) - [j86]Biao Zhang, Dong Liu, Yang Zhang, Hong-Bin Shen, Gui-Jun Zhang:
Accurate flexible refinement for atomic-level protein structure using cryo-EM density maps and deep learning. Briefings Bioinform. 23(2) (2022) - [j85]Qunzhuo Wu, Zhaohong Deng, Xiaoyong Pan, Hong-Bin Shen, Kup-Sze Choi, Shitong Wang, Jing Wu, Dong-Jun Yu:
MDGF-MCEC: a multi-view dual attention embedding model with cooperative ensemble learning for CircRNA-disease association prediction. Briefings Bioinform. 23(5) (2022) - [j84]Shi-Hao Feng, Chun-Qiu Xia, Hong-Bin Shen:
CoCoPRED: coiled-coil protein structural feature prediction from amino acid sequence using deep neural networks. Bioinform. 38(3): 720-729 (2022) - [j83]Lujing Zheng, Zhenhuan Liu, Yang Yang, Hong-Bin Shen:
Accurate inference of gene regulatory interactions from spatial gene expression with deep contrastive learning. Bioinform. 38(3): 746-753 (2022) - [j82]Jin-Xian Hu, Yang Yang, Ying-Ying Xu, Hong-Bin Shen:
GraphLoc: a graph neural network model for predicting protein subcellular localization from immunohistochemistry images. Bioinform. 38(21): 4941-4948 (2022) - [j81]Xi-Liang Zhu, Hong-Bin Shen, Haitao Sun, Li-Xia Duan, Ying-Ying Xu:
Improving segmentation and classification of renal tumors in small sample 3D CT images using transfer learning with convolutional neural networks. Int. J. Comput. Assist. Radiol. Surg. 17(7): 1303-1311 (2022) - [j80]Chun-Qiu Xia, Shi-Hao Feng, Ying Xia, Xiaoyong Pan, Hong-Bin Shen:
Fast protein structure comparison through effective representation learning with contrastive graph neural networks. PLoS Comput. Biol. 18(3) (2022) - [j79]Yi Fang, Xiaoyong Pan, Hong-Bin Shen:
Recent Deep Learning Methodology Development for RNA-RNA Interaction Prediction. Symmetry 14(7): 1302 (2022) - [j78]Shi-Hao Feng, Chun-Qiu Xia, Pei-Dong Zhang, Hong-Bin Shen:
Ab-Initio Membrane Protein Amphipathic Helix Structure Prediction Using Deep Neural Networks. IEEE ACM Trans. Comput. Biol. Bioinform. 19(2): 795-805 (2022) - [j77]Wei Zhang, Zhaohong Deng, Jun Wang, Kup-Sze Choi, Te Zhang, Xiaoqing Luo, Hong-Bin Shen, Wenhao Ying, Shitong Wang:
Transductive Multiview Modeling With Interpretable Rules, Matrix Factorization, and Cooperative Learning. IEEE Trans. Cybern. 52(10): 11226-11239 (2022) - [j76]Qiongdan Lou, Zhaohong Deng, Kup-Sze Choi, Hong-Bin Shen, Jun Wang, Shitong Wang:
Robust Multi-Label Relief Feature Selection Based on Fuzzy Margin Co-Optimization. IEEE Trans. Emerg. Top. Comput. Intell. 6(2): 387-398 (2022) - [i3]Jiachen Li, Ye Yuan, Hong-Bin Shen:
Symbolic Expression Transformer: A Computer Vision Approach for Symbolic Regression. CoRR abs/2205.11798 (2022) - [i2]Yu-Xuan Chen, Dagan Feng, Hong-Bin Shen:
Unsupervised Difference Learning for Noisy Rigid Image Alignment. CoRR abs/2205.11829 (2022) - 2021
- [j75]Haitao Yang, Zhaohong Deng, Xiaoyong Pan, Hong-Bin Shen, Kup-Sze Choi, Lei Wang, Shitong Wang, Jing Wu:
RNA-binding protein recognition based on multi-view deep feature and multi-label learning. Briefings Bioinform. 22(3) (2021) - [j74]Hehe Wu, Xiaoyong Pan, Yang Yang, Hong-Bin Shen:
Recognizing binding sites of poorly characterized RNA-binding proteins on circular RNAs using attention Siamese network. Briefings Bioinform. 22(6) (2021) - [j73]Xiaoyong Pan, Jasper Zuallaert, Xi Wang, Hong-Bin Shen, Elda Posada Campos, Denys O. Marushchak, Wesley De Neve:
ToxDL: deep learning using primary structure and domain embeddings for assessing protein toxicity. Bioinform. 36(21): 5159-5168 (2021) - [j72]Yang Lin, Xiaoyong Pan, Hong-Bin Shen:
lncLocator 2.0: a cell-line-specific subcellular localization predictor for long non-coding RNAs with interpretable deep learning. Bioinform. 37(16): 2308-2316 (2021) - [j71]Yu-Xuan Chen, Rui Xie, Yang Yang, Lin He, Dagan Feng, Hong-Bin Shen:
Fast Cryo-EM Image Alignment Algorithm Using Power Spectrum Features. J. Chem. Inf. Model. 61(9): 4795-4806 (2021) - [j70]Wei Long, Tiange Li, Yang Yang, Hong-Bin Shen:
FlyIT: Drosophila Embryogenesis Image Annotation based on Image Tiling and Convolutional Neural Networks. IEEE ACM Trans. Comput. Biol. Bioinform. 18(1): 194-204 (2021) - [i1]Andong Li, Zhaohong Deng, Qiongdan Lou, Kup-Sze Choi, Hong-Bin Shen, Shitong Wang:
A Novel TSK Fuzzy System Incorporating Multi-view Collaborative Transfer Learning for Personalized Epileptic EEG Detection. CoRR abs/2111.08457 (2021) - 2020
- [j69]Di Wang, Ling Geng, Yu-Jun Zhao, Yang Yang, Yan Huang, Yang Zhang, Hong-Bin Shen:
Artificial intelligence-based multi-objective optimization protocol for protein structure refinement. Bioinform. 36(2): 437-448 (2020) - [j68]Ying-Ying Xu, Hong-Bin Shen, Robert F. Murphy:
Learning complex subcellular distribution patterns of proteins via analysis of immunohistochemistry images. Bioinform. 36(6): 1908-1914 (2020) - [j67]Wei Long, Yang Yang, Hong-Bin Shen:
ImPLoc: a multi-instance deep learning model for the prediction of protein subcellular localization based on immunohistochemistry images. Bioinform. 36(7): 2244-2250 (2020) - [j66]Chun-Qiu Xia, Xiaoyong Pan, Hong-Bin Shen:
Protein-ligand binding residue prediction enhancement through hybrid deep heterogeneous learning of sequence and structure data. Bioinform. 36(10): 3018-3027 (2020) - [j65]Rui Xie, Yu-Xuan Chen, Jia-Ming Cai, Yang Yang, Hong-Bin Shen:
SPREAD: A Fully Automated Toolkit for Single-Particle Cryogenic Electron Microscopy Data 3D Reconstruction with Image-Network-Aided Orientation Assignment. J. Chem. Inf. Model. 60(5): 2614-2625 (2020) - [j64]Wei-Xun Zhang, Xiaoyong Pan, Hong-Bin Shen:
Signal-3L 3.0: Improving Signal Peptide Prediction through Combining Attention Deep Learning with Window-Based Scoring. J. Chem. Inf. Model. 60(7): 3679-3686 (2020) - [j63]Xiaoyong Pan, Hong-Bin Shen:
Scoring disease-microRNA associations by integrating disease hierarchy into graph convolutional networks. Pattern Recognit. 105: 107385 (2020) - [c17]Rui Hu, Jia-Ming Cai, Wangjie Zheng, Yang Yang, Hong-Bin Shen:
NiuEM: A Nested-iterative Unsupervised Learning Model for Single-particle Cryo-EM Image Processing. BIBM 2020: 583-588
2010 – 2019
- 2019
- [j62]Yang Yang, Mingyu Zhou, Qingwei Fang, Hong-Bin Shen:
AnnoFly: annotating Drosophila embryonic images based on an attention-enhanced RNN model. Bioinform. 35(16): 2834-2842 (2019) - [j61]Xiaoyong Pan, Yong-Xian Fan, Jue Jia, Hong-Bin Shen:
Identifying RNA-binding proteins using multi-label deep learning. Sci. China Inf. Sci. 62(1): 19103:1-19103:3 (2019) - [j60]Shuo Yin, Biao Zhang, Yang Yang, Yan Huang, Hong-Bin Shen:
Clustering Enhancement of Noisy Cryo-Electron Microscopy Single-Particle Images with a Network Structural Similarity Metric. J. Chem. Inf. Model. 59(4): 1658-1667 (2019) - [j59]Yang Yang, Qingwei Fang, Hong-Bin Shen:
Predicting gene regulatory interactions based on spatial gene expression data and deep learning. PLoS Comput. Biol. 15(9) (2019) - 2018
- [j58]Hanjin Zhang, Yang Yang, Hong-Bin Shen:
Line Junction Detection Without Prior-Delineation of Curvilinear Structure in Biomedical Images. IEEE Access 6: 2016-2027 (2018) - [j57]Hanjin Zhang, Yang Yang, Hong-Bin Shen:
Detection of Curvilinear Structure in Images by a Multi-Centered Hough Forest Method. IEEE Access 6: 22684-22694 (2018) - [j56]Jing Yang, Hong-Bin Shen:
MemBrain-contact 2.0: a new two-stage machine learning model for the prediction enhancement of transmembrane protein residue contacts in the full chain. Bioinform. 34(2): 230-238 (2018) - [j55]Zhen Cao, Xiaoyong Pan, Yang Yang, Yan Huang, Hong-Bin Shen:
The lncLocator: a subcellular localization predictor for long non-coding RNAs based on a stacked ensemble classifier. Bioinform. 34(13): 2185-2194 (2018) - [j54]Xiaoyong Pan, Hong-Bin Shen:
Predicting RNA-protein binding sites and motifs through combining local and global deep convolutional neural networks. Bioinform. 34(20): 3427-3436 (2018) - [j53]Yang Yang, Xiaofeng Fu, Wenhao Qu, Yiqun Xiao, Hong-Bin Shen:
MiRGOFS: a GO-based functional similarity measurement for miRNAs, with applications to the prediction of miRNA subcellular localization and miRNA-disease association. Bioinform. 34(20): 3547-3556 (2018) - [j52]Ying-Ying Xu, Li-Xiu Yao, Hong-Bin Shen:
Bioimage-based protein subcellular location prediction: a comprehensive review. Frontiers Comput. Sci. 12(1): 26-39 (2018) - [j51]Xu-Hao Zhi, Shu Meng, Hong-Bin Shen:
High density cell tracking with accurate centroid detections and active area-based tracklet clustering. Neurocomputing 295: 86-97 (2018) - [j50]Xiaoyong Pan, Hong-Bin Shen:
Learning distributed representations of RNA sequences and its application for predicting RNA-protein binding sites with a convolutional neural network. Neurocomputing 305: 51-58 (2018) - [j49]Yu-Jiao Yang, Shuai Wang, Biao Zhang, Hong-Bin Shen:
Resolution Measurement from a Single Reconstructed Cryo-EM Density Map with Multiscale Spectral Analysis. J. Chem. Inf. Model. 58(6): 1303-1311 (2018) - [j48]Xu-Hao Zhi, Hong-Bin Shen:
Saliency driven region-edge-based top down level set evolution reveals the asynchronous focus in image segmentation. Pattern Recognit. 80: 241-255 (2018) - [j47]Wei Shao, Mingxia Liu, Ying-Ying Xu, Hong-Bin Shen, Daoqiang Zhang:
An Organelle Correlation-Guided Feature Selection Approach for Classifying Multi-Label Subcellular Bio-Images. IEEE ACM Trans. Comput. Biol. Bioinform. 15(3): 828-838 (2018) - [c16]Tiange Li, Yang Yang, Hong-Bin Shen:
HMIML: Hierarchical Multi-Instance Multi-Label Learning of Drosophila Embryogenesis Images Using Convolutional Neural Networks. BIBM 2018: 907-912 - [c15]Guowei Ji, Yang Yang, Hong-Bin Shen:
IterVM: An Iterative Model for Single-Particle Cryo-EM Image Clustering Based on Variational Autoencoder and Multi-Reference Alignment. BIBM 2018: 999-1002 - [c14]Yiqun Xiao, Jiaxun Cai, Yang Yang, Hai Zhao, Hong-Bin Shen:
Prediction of MicroRNA Subcellular Localization by Using a Sequence-to-Sequence Model. ICDM 2018: 1332-1337 - 2017
- [j46]Hang Zhou, Yang Yang, Hong-Bin Shen:
Hum-mPLoc 3.0: prediction enhancement of human protein subcellular localization through modeling the hidden correlations of gene ontology and functional domain features. Bioinform. 33(6): 843-853 (2017) - [j45]Baoji He, S. M. Mortuza, Yanting Wang, Hong-Bin Shen, Yang Zhang:
NeBcon: protein contact map prediction using neural network training coupled with naïve Bayes classifiers. Bioinform. 33(15): 2296-2306 (2017) - [j44]Xiaoyong Pan, Hong-Bin Shen:
RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach. BMC Bioinform. 18(1): 136:1-136:14 (2017) - [j43]Wei Shao, Yi Ding, Hong-Bin Shen, Daoqiang Zhang:
Deep model-based feature extraction for predicting protein subcellular localizations from bio-images. Frontiers Comput. Sci. 11(2): 243-252 (2017) - [j42]Yi-Ze Zhang, Hong-Bin Shen:
Signal-3L 2.0: A Hierarchical Mixture Model for Enhancing Protein Signal Peptide Prediction by Incorporating Residue-Domain Cross-Level Features. J. Chem. Inf. Model. 57(4): 988-999 (2017) - [j41]Jun Hu, Yang Li, Ming Zhang, Xibei Yang, Hong-Bin Shen, Dong-Jun Yu:
Predicting Protein-DNA Binding Residues by Weightedly Combining Sequence-Based Features and Boosting Multiple SVMs. IEEE ACM Trans. Comput. Biol. Bioinform. 14(6): 1389-1398 (2017) - [j40]Ngaam J. Cheung, Xueming Ding, Hong-Bin Shen:
A Nonhomogeneous Cuckoo Search Algorithm Based on Quantum Mechanism for Real Parameter Optimization. IEEE Trans. Cybern. 47(2): 391-402 (2017) - [c13]Hanjin Zhang, Yang Yang, Hong-Bin Shen:
Detection of Curvilinear Centerline by Using Hough Voting. ACPR 2017: 120-125 - [c12]Jin-Xian Hu, Ying-Ying Xu, Yang Yang, Hong-Bin Shen:
Deep Learning-Based Classification of Protein Subcellular Localization from Immunohistochemistry Images. ACPR 2017: 599-604 - [c11]Ling Geng, Hong-Bin Shen:
A protein structure refinement method using bi-objective particle swarm optimization algorithm. CISP-BMEI 2017: 1-5 - [c10]Yu-Jiao Yang, Hong-Bin Shen:
Resolution determination method of a cryo-EM density map based on multi-scale spectral signal to noise analysis. CISP-BMEI 2017: 1-5 - 2016
- [j39]Ying-Ying Xu, Fan Yang, Hong-Bin Shen:
Incorporating organelle correlations into semi-supervised learning for protein subcellular localization prediction. Bioinform. 32(14): 2184-2192 (2016) - [j38]Jing Yang, Qi-Yu Jin, Biao Zhang, Hong-Bin Shen:
R2C: improving ab initio residue contact map prediction using dynamic fusion strategy and Gaussian noise filter. Bioinform. 32(16): 2435-2443 (2016) - [j37]Jun Hu, Yang Li, Jing-Yu Yang, Hong-Bin Shen, Dong-Jun Yu:
GPCR-drug interactions prediction using random forest with drug-association-matrix-based post-processing procedure. Comput. Biol. Chem. 60: 59-71 (2016) - [j36]Jun Hu, Yang Li, Wuxia Yan, Jing-Yu Yang, Hong-Bin Shen, Dong-Jun Yu:
KNN-based dynamic query-driven sample rescaling strategy for class imbalance learning. Neurocomputing 191: 363-373 (2016) - [j35]Zhisen Wei, Ke Han, Jing-Yu Yang, Hong-Bin Shen, Dong-Jun Yu:
Protein-protein interaction sites prediction by ensembling SVM and sample-weighted random forests. Neurocomputing 193: 201-212 (2016) - [j34]Ngaam J. Cheung, Xueming Ding, Hong-Bin Shen:
Protein folds recognized by an intelligent predictor based-on evolutionary and structural information. J. Comput. Chem. 37(4): 426-436 (2016) - [j33]Ngaam J. Cheung, Xueming Ding, Hong-Bin Shen:
A Non-homogeneous Firefly Algorithm and Its Convergence Analysis. J. Optim. Theory Appl. 170(2): 616-628 (2016) - [j32]Xi Yin, Ying-Ying Xu, Hong-Bin Shen:
Enhancing the Prediction of Transmembrane β-Barrel Segments with Chain Learning and Feature Sparse Representation. IEEE ACM Trans. Comput. Biol. Bioinform. 13(6): 1016-1026 (2016) - [c9]Yi-Ze Zhang, Hong-Bin Shen:
Improve signal peptide prediction by using functional domain information. CISP-BMEI 2016: 1814-1819 - [c8]Hang Zhou, Yang Yang, Hong-Bin Shen:
A New Subcellular Localization Predictor for Human Proteins Considering the Correlation of Annotation Features and Protein Multi-localization. CCPR (2) 2016: 499-512 - 2015
- [j31]Ngaam J. Cheung, Xueming Ding, Hong-Bin Shen:
A supervised particle swarm algorithm for real-parameter optimization. Appl. Intell. 43(4): 825-839 (2015) - [j30]Peng-Jie Jing, Hong-Bin Shen:
MACOED: a multi-objective ant colony optimization algorithm for SNP epistasis detection in genome-wide association studies. Bioinform. 31(5): 634-641 (2015) - [j29]Ying-Ying Xu, Fan Yang, Yang Zhang, Hong-Bin Shen:
Bioimaging-based detection of mislocalized proteins in human cancers by semi-supervised learning. Bioinform. 31(7): 1111-1119 (2015) - [j28]Jing Yang, Bao-Ji He, Richard Jang, Yang Zhang, Hong-Bin Shen:
Accurate disulfide-bonding network predictions improve ab initio structure prediction of cysteine-rich proteins. Bioinform. 31(23): 3773-3781 (2015) - [j27]Ngaam J. Cheung, Zhenkai Xu, Xueming Ding, Hong-Bin Shen:
Modeling nonlinear dynamic biological systems with human-readable fuzzy rules optimized by convergent heterogeneous particle swarm. Eur. J. Oper. Res. 247(2): 349-358 (2015) - [j26]Feng Xiao, Hong-Bin Shen:
Prediction Enhancement of Residue Real-Value Relative Accessible Surface Area in Transmembrane Helical Proteins by Solving the Output Preference Problem of Machine Learning-Based Predictors. J. Chem. Inf. Model. 55(11): 2464-2474 (2015) - [j25]Dong-Jun Yu, Yang Li, Jun Hu, Xibei Yang, Jing-Yu Yang, Hong-Bin Shen:
Disulfide Connectivity Prediction Based on Modelled Protein 3D Structural Information and Random Forest Regression. IEEE ACM Trans. Comput. Biol. Bioinform. 12(3): 611-621 (2015) - 2014
- [j24]Dong-Jun Yu, Jun Hu, Hui Yan, Xibei Yang, Jing-Yu Yang, Hong-Bin Shen:
Enhancing protein-vitamin binding residues prediction by multiple heterogeneous subspace SVMs ensemble. BMC Bioinform. 15: 297 (2014) - [j23]Yong-Xian Fan, Hong-Bin Shen:
Predicting pupylation sites in prokaryotic proteins using pseudo-amino acid composition and extreme learning machine. Neurocomputing 128: 267-272 (2014) - [j22]Fan Yang, Ying-Ying Xu, Shitong Wang, Hong-Bin Shen:
Image-based classification of protein subcellular location patterns in human reproductive tissue by ensemble learning global and local features. Neurocomputing 131: 113-123 (2014) - [j21]Ngaam J. Cheung, Xueming Ding, Hong-Bin Shen:
OptiFel: A Convergent Heterogeneous Particle Swarm Optimization Algorithm for Takagi-Sugeno Fuzzy Modeling. IEEE Trans. Fuzzy Syst. 22(4): 919-933 (2014) - [c7]Hai-Ping Sun, Hong-Bin Shen:
A Global Eigenvalue-Driven Balanced Deconvolution Approach for Network Direct-Coupling Analysis. CCPR (2) 2014: 409-418 - [c6]Feng Xiao, Hong-Bin Shen:
Sequence-Based Prediction of Protein-Protein Binding Residues in Alpha-Helical Membrane Proteins. CCPR (2) 2014: 419-427 - [c5]Peng-Jie Jing, Hong-Bin Shen:
A Novel Two-Stage Multi-objective Ant Colony Optimization Approach for Epistasis Learning. CCPR (2) 2014: 528-535 - 2013
- [j20]Ying-Ying Xu, Fan Yang, Yang Zhang, Hong-Bin Shen:
An image-based multi-label human protein subcellular localization predictor (iLocator) reveals protein mislocalizations in cancer tissues. Bioinform. 29(16): 2032-2040 (2013) - [j19]Jing Yang, Richard Jang, Yang Zhang, Hong-Bin Shen:
High-accuracy prediction of transmembrane inter-helix contacts and application to GPCR 3D structure modeling. Bioinform. 29(20): 2579-2587 (2013) - [j18]Bairong Shen, Hong-Bin Shen, Tianhai Tian, Qiang Lü, Guang Hu:
Translational Bioinformatics and Computational Systems Medicine. Comput. Math. Methods Medicine 2013: 375641:1-375641:2 (2013) - [j17]Jian-Bo Lei, Jiang-Bo Yin, Hong-Bin Shen:
GFO: A data driven approach for optimizing the Gaussian function based similarity metric in computational biology. Neurocomputing 99: 307-315 (2013) - [j16]Dong-Jun Yu, Jun Hu, Zhenmin Tang, Hong-Bin Shen, Jian Yang, Jing-Yu Yang:
Improving protein-ATP binding residues prediction by boosting SVMs with random under-sampling. Neurocomputing 104: 180-190 (2013) - [j15]Dong-Jun Yu, Jun Hu, Yan Huang, Hong-Bin Shen, Yong Qi, Zhenmin Tang, Jing-Yu Yang:
TargetATPsite: A template-free method for ATP-binding sites prediction with residue evolution image sparse representation and classifier ensemble. J. Comput. Chem. 34(11): 974-985 (2013) - [j14]Dong-Jun Yu, Jun Hu, Jing Yang, Hong-Bin Shen, Jinhui Tang, Jing-Yu Yang:
Designing Template-Free Predictor for Targeting Protein-Ligand Binding Sites with Classifier Ensemble and Spatial Clustering. IEEE ACM Trans. Comput. Biol. Bioinform. 10(4): 994-1008 (2013) - 2012
- [j13]Ya-Nan Zhang, Dong-Jun Yu, Shu-Sen Li, Yong-Xian Fan, Yan Huang, Hong-Bin Shen:
Predicting protein-ATP binding sites from primary sequence through fusing bi-profile sampling of multi-view features. BMC Bioinform. 13: 118 (2012) - [c4]Fan Yang, Ying-Ying Xu, Hong-Bin Shen:
Automated Classification of Protein Subcellular Location Patterns on Images of Human Reproductive Tissues. IScIDE 2012: 254-262 - 2011
- [j12]Qing-Ju Jiao, Yan Huang, Hong-Bin Shen:
Large-scale mining co-expressed genes in Arabidopsis anther: From pair to group. Comput. Biol. Chem. 35(2): 62-68 (2011) - [j11]Jiang-Bo Yin, Tao Li, Hong-Bin Shen:
Gaussian kernel optimization: Complex problem and a simple solution. Neurocomputing 74(18): 3816-3822 (2011) - [j10]Jiangning Song, Hao Tan, Sarah E. Boyd, Hong-Bin Shen, Khalid Mahmood, Geoffrey I. Webb, Tatsuya Akutsu, James C. Whisstock, Robert N. Pike:
Bioinformatic Approaches for Predicting substrates of Proteases. J. Bioinform. Comput. Biol. 9(1): 149-178 (2011) - 2010
- [j9]Jiangning Song, Hao Tan, Hong-Bin Shen, Khalid Mahmood, Sarah E. Boyd, Geoffrey I. Webb, Tatsuya Akutsu, James C. Whisstock:
Cascleave: towards more accurate prediction of caspase substrate cleavage sites. Bioinform. 26(6): 752-760 (2010) - [j8]Lin Zhu, Jie Yang, Jiangning Song, Kuo-Chen Chou, Hong-Bin Shen:
Improving the accuracy of predicting disulfide connectivity by feature selection. J. Comput. Chem. 31(7): 1478-1485 (2010)
2000 – 2009
- 2006
- [j7]Hong-Bin Shen, Kuo-Chen Chou:
Ensemble classifier for protein fold pattern recognition. Bioinform. 22(14): 1717-1722 (2006) - [j6]Hong-Bin Shen, Jie Yang, Shitong Wang, Xiaojun Liu:
Attribute weighted mercer kernel based fuzzy clustering algorithm for general non-spherical datasets. Soft Comput. 10(11): 1061-1073 (2006) - [c3]Xiaojun Liu, Jie Yang, Hong-Bin Shen, Xiangyang Wang:
A New Scaling Kernel-Based Fuzzy System with Low Computational Complexity. CSR 2006: 466-474 - 2005
- [j5]Shitong Wang, Fu-Lai Chung, Hong-Bin Shen, Dewen Hu:
Cascaded centralized TSK fuzzy system: universal approximator and high interpretation. Appl. Soft Comput. 5(2): 131-145 (2005) - [j4]Shitong Wang, Korris Fu-Lai Chung, Hong-Bin Shen:
Fuzzy taxonomy, quantitative database and mining generalized association rules. Intell. Data Anal. 9(2): 207-217 (2005) - [j3]