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Hong-Bin Shen
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2020 – today
- 2024
- [j100]Meihong Pan
, Hongbin Shen:
Multimodal variational contrastive learning for few-shot classification. Appl. Intell. 54(2): 1879-1892 (2024) - [j99]Hehe Wu, Xiaojian Liu, Yi Fang, Yang Yang, Yan Huang, Xiaoyong Pan
Decoding protein binding landscape on circular RNAs with base-resolution transformer models. Comput. Biol. Medicine 171: 108175 (2024) - [j98]Meihong Pan, Hongyi Xin, Hong-Bin Shen:
Semantic-Based Implicit Feature Transform for Few-Shot Classification. Int. J. Comput. Vis. 132(11): 5014-5029 (2024) - [j97]Meihong Pan
Cross-modal de-deviation for enhancing few-shot classification. Pattern Recognit. 152: 110475 (2024) - 2023
- [j96]Chun-Qiu Xia
Leveraging scaffold information to predict protein-ligand binding affinity with an empirical graph neural network. Briefings Bioinform. 24(1) (2023) - [j95]Pei-Dong Zhang
High-accuracy protein model quality assessment using attention graph neural networks. Briefings Bioinform. 24(2) (2023) - [j94]Yi Fang, Xiaoyong Pan
De novodrug design by iterative multiobjective deep reinforcement learning with graph-based molecular quality assessment. Bioinform. 39(4) (2023) - [j93]Qunzhuo Wu, Zhaohong Deng, Wei Zhang, Xiaoyong Pan
MLNGCF: circRNA-disease associations prediction with multilayer attention neural graph-based collaborative filtering. Bioinform. 39(8) (2023) - [j92]Meihong Pan
Few-shot classification with task-adaptive semantic feature learning. Pattern Recognit. 141: 109594 (2023) - [c18]Kuo Guo, Yifan Li, Hao Chen, Hong-Bin Shen, Yang Yang:
Isoform Function Prediction Based on Heterogeneous Graph Attention Networks. BIBM 2023: 522-527 - 2022
- [j91]Hui Li
circRNA-binding protein site prediction based on multi-view deep learning, subspace learning and multi-view classifier. Briefings Bioinform. 23(1) (2022) - [j90]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) - [j89]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) - [j88]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) - [j87]Qunzhuo Wu, Zhaohong Deng, Xiaoyong Pan
MDGF-MCEC: a multi-view dual attention embedding model with cooperative ensemble learning for CircRNA-disease association prediction. Briefings Bioinform. 23(5) (2022) - [j86]Shi-Hao Feng
CoCoPRED: coiled-coil protein structural feature prediction from amino acid sequence using deep neural networks. Bioinform. 38(3): 720-729 (2022) - [j85]Lujing Zheng, Zhenhuan Liu, Yang Yang
Accurate inference of gene regulatory interactions from spatial gene expression with deep contrastive learning. Bioinform. 38(3): 746-753 (2022) - [j84]Jin-Xian Hu, Yang Yang
GraphLoc: a graph neural network model for predicting protein subcellular localization from immunohistochemistry images. Bioinform. 38(21): 4941-4948 (2022) - [j83]Xi-Liang Zhu
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) - [j82]Jiachen Li
Cell clustering for spatial transcriptomics data with graph neural networks. Nat. Comput. Sci. 2(6): 399-408 (2022) - [j81]Chun-Qiu Xia
Fast protein structure comparison through effective representation learning with contrastive graph neural networks. PLoS Comput. Biol. 18(3) (2022) - [j80]Yi Fang
Recent Deep Learning Methodology Development for RNA-RNA Interaction Prediction. Symmetry 14(7): 1302 (2022) - [j79]Shi-Hao Feng
Ab-Initio Membrane Protein Amphipathic Helix Structure Prediction Using Deep Neural Networks. IEEE ACM Trans. Comput. Biol. Bioinform. 19(2): 795-805 (2022) - [j78]Wei Zhang, Zhaohong Deng
Transductive Multiview Modeling With Interpretable Rules, Matrix Factorization, and Cooperative Learning. IEEE Trans. Cybern. 52(10): 11226-11239 (2022) - [j77]Qiongdan Lou
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
- [j76]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) - [j75]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) - [j74]Xiaoyong Pan
ToxDL: deep learning using primary structure and domain embeddings for assessing protein toxicity. Bioinform. 36(21): 5159-5168 (2021) - [j73]Yang Lin
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) - [j72]Yu-Xuan Chen
Fast Cryo-EM Image Alignment Algorithm Using Power Spectrum Features. J. Chem. Inf. Model. 61(9): 4795-4806 (2021) - [j71]Wei Long, Tiange Li, Yang Yang
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
- [j70]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) - [j69]Ying-Ying Xu
Learning complex subcellular distribution patterns of proteins via analysis of immunohistochemistry images. Bioinform. 36(6): 1908-1914 (2020) - [j68]Wei Long, Yang Yang
ImPLoc: a multi-instance deep learning model for the prediction of protein subcellular localization based on immunohistochemistry images. Bioinform. 36(7): 2244-2250 (2020) - [j67]Chun-Qiu Xia
Protein-ligand binding residue prediction enhancement through hybrid deep heterogeneous learning of sequence and structure data. Bioinform. 36(10): 3018-3027 (2020) - [j66]Rui Xie, Yu-Xuan Chen
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) - [j65]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) - [j64]Xiaoyong Pan
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
- [j63]Yang Yang
AnnoFly: annotating Drosophila embryonic images based on an attention-enhanced RNN model. Bioinform. 35(16): 2834-2842 (2019) - [j62]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) - [j61]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) - [j60]Yang Yang
Predicting gene regulatory interactions based on spatial gene expression data and deep learning. PLoS Comput. Biol. 15(9) (2019) - 2018
- [j59]Hanjin Zhang, Yang Yang
Line Junction Detection Without Prior-Delineation of Curvilinear Structure in Biomedical Images. IEEE Access 6: 2016-2027 (2018) - [j58]Hanjin Zhang, Yang Yang
Detection of Curvilinear Structure in Images by a Multi-Centered Hough Forest Method. IEEE Access 6: 22684-22694 (2018) - [j57]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) - [j56]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) - [j55]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) - [j54]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) - [j53]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) - [j52]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) - [j51]Xiaoyong Pan
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) - [j50]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) - [j49]Xu-Hao Zhi
Saliency driven region-edge-based top down level set evolution reveals the asynchronous focus in image segmentation. Pattern Recognit. 80: 241-255 (2018) - [j48]Wei Shao
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
- [j47]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) - [j46]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) - [j45]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) - [j44]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) - [j43]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) - [j42]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) - [j41]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
- [j40]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) - [j39]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) - [j38]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) - [j37]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) - [j36]Zhisen Wei
Protein-protein interaction sites prediction by ensembling SVM and sample-weighted random forests. Neurocomputing 193: 201-212 (2016) - [j35]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) - [j34]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) - [j33]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
- [j32]Ngaam J. Cheung, Xueming Ding, Hong-Bin Shen:
A supervised particle swarm algorithm for real-parameter optimization. Appl. Intell. 43(4): 825-839 (2015) - [j31]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) - [j30]Ying-Ying Xu, Fan Yang, Yang Zhang
Bioimaging-based detection of mislocalized proteins in human cancers by semi-supervised learning. Bioinform. 31(7): 1111-1119 (2015) - [j29]Jing Yang, Bao-Ji He, Richard Jang, Yang Zhang
Accurate disulfide-bonding network predictions improve ab initio structure prediction of cysteine-rich proteins. Bioinform. 31(23): 3773-3781 (2015) - [j28]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) - [j27]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) - [j26]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
- [j25]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) - [j24]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) - [j23]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) - [j22]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
- [j21]Ying-Ying Xu, Fan Yang, Yang Zhang
An image-based multi-label human protein subcellular localization predictor (iLocator) reveals protein mislocalizations in cancer tissues. Bioinform. 29(16): 2032-2040 (2013) - [j20]Jing Yang, Richard Jang, Yang Zhang
High-accuracy prediction of transmembrane inter-helix contacts and application to GPCR 3D structure modeling. Bioinform. 29(20): 2579-2587 (2013) - [j19]Bairong Shen
Translational Bioinformatics and Computational Systems Medicine. Comput. Math. Methods Medicine 2013: 375641:1-375641:2 (2013) - [j18]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) - [j17]Dong-Jun Yu, Jun Hu, Zhenmin Tang
Improving protein-ATP binding residues prediction by boosting SVMs with random under-sampling. Neurocomputing 104: 180-190 (2013) - [j16]Dong-Jun Yu, Jun Hu, Yan Huang, Hong-Bin Shen, Yong Qi, Zhenmin Tang
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) - [j15]Dong-Jun Yu, Jun Hu, Jing Yang, Hong-Bin Shen, Jinhui Tang
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
- [j14]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
- [j13]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) - [j12]Jiang-Bo Yin, Tao Li, Hong-Bin Shen:
Gaussian kernel optimization: Complex problem and a simple solution. Neurocomputing 74(18): 3816-3822 (2011) - [j11]Jiangning Song
Bioinformatic Approaches for Predicting substrates of Proteases. J. Bioinform. Comput. Biol. 9(1): 149-178 (2011) - 2010
- [j10]Jiangning Song
Cascleave: towards more accurate prediction of caspase substrate cleavage sites. Bioinform. 26(6): 752-760 (2010) - [j9]Jiangning Song, Kazuhiro Takemoto, Hongbin Shen, Hao Tan, M. Michael Gromiha, Tatsuya Akutsu:
Prediction of Protein Folding Rates from Structural Topology and Complex Network Properties. Inf. Media Technol. 5(3): 980-993 (2010) - [j8]Lin Zhu, Jie Yang, Jiangning Song
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
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]Hong-Bin Shen, Jie Yang, Ningjiang Chen, Yifei Dong, Shitong Wang:
Performing clustering analysis on collaborative models. Intell. Data Anal. 9(5): 419-438 (2005) - 2004
- [j2]Shitong Wang, Korris Fu-Lai Chung, Hong-Bin Shen, Ruiqiang Zhu:
Note on the relationship between probabilistic and fuzzy clustering. Soft Comput. 8(5): 366-369 (2004) - [j1]Korris Fu-Lai Chung
Note on the relationship between probabilistic and fuzzy clustering. Soft Comput. 8(7): 523-526 (2004) - [c2]Hong-Bin Shen, Jie Yang, Shitong Wang:
Outlier Detecting in Fuzzy Switching Regression Models. AIMSA 2004: 208-215 - [c1]Hong-Bin Shen, Shitong Wang, Jie Yang:
Fuzzy Taxonomic, Quantitative Database and Mining Generalized Association Rules. Rough Sets and Current Trends in Computing 2004: 610-617
Coauthor Index
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