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ORCIDGang Fang
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
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2020 – today
- 2024
[j34]Zhangjun Wu
, Gang Fang, Yifei Wang, Renli Xu:
An End-to-end Deep Clustering Method with Consistency and Complementarity Attention Mechanism for Multisensor Fault Diagnosis. Appl. Soft Comput. 158: 111594 (2024)- [j33]Gang Fang, Yiqi Liu:
Twinning quality sensors in wastewater treatment process via optimized echo state network-based soft sensors. Appl. Soft Comput. 164: 111977 (2024) - [j32]Zhihong Chen, Lisha Yao, Yanfen Cui, Yunlin Zheng, Suyun Li, Xiaorui Han, Xuewei Kang, Wenbin Liu, Xin Chen, Chu Han, Zaiyi Liu, Bingjiang Qiu, Gang Fang:
ALIEN: Attention-guided cross-resolution collaborative network for 3D gastric cancer segmentation in CT images. Biomed. Signal Process. Control. 96: 106500 (2024) - [j31]Haoyu Xiong, Leixin Yang, Gang Fang, Junwei Li, Yu Xiang, Yaping Zhang:
Robustness test-time augmentation via learnable aggregation and anomaly detection. J. Intell. Fuzzy Syst. 46(4): 8783-8798 (2024) - [j30]Yue Liu, Xiangzhen Zan, Xianbin Li, Wenbin Liu, Gang Fang:
Contrastive visual clustering for improving instance-level contrastive learning as a plugin. Pattern Recognit. 154: 110631 (2024) - [j29]Weixing Hua, Yan Chen, Xiang Zhao, Jiping Yang, Han Chen, Zhaojie Wu, Gang Fang:
Research on a Corrosion Detection Method for Oil Tank Bottoms Based on Acoustic Emission Technology. Sensors 24(10): 3053 (2024) - [c29]Haoyu Xiong, Xinchun Zhang, Leixin Yang, Yu Xiang, Gang Fang:
STAF: Pushing the Boundaries of Test-Time Adaptation towards Practical Noise Scenarios. LREC/COLING 2024: 15226-15237 - 2023
- [j28]Yunyue Elita Li, Enhedelihai Alex Nilot, Yumin Zhao, Gang Fang:
Quantifying Urban Activities Using Nodal Seismometers in a Heterogeneous Urban Space. Sensors 23(3): 1322 (2023) - [j27]Gang Fang, Uzma Ahmad, Sobia Ikhlaq, Leila Asgharsharghi:
Multi-Attribute Group Decision Making Based on Spherical Fuzzy Zagreb Energy. Symmetry 15(8): 1536 (2023) - [j26]Gang Fang, Yiqi Liu, Baoping Cai, Hongtian Chen, Daoping Huang:
A Hierarchical Soft-Sensor Using Spatiotemporal Information Transformation and ARMA With Application in Wastewater Treatment. IEEE Trans. Instrum. Meas. 72: 1-11 (2023) - [c28]JiChao Luo, Zhihong Chen, Wenbin Liu, Zaiyi Liu, Bingjiang Qiu, Gang Fang:
AdaptNet: Adaptive Learning from Partially Labeled Data for Abdomen Multi-organ and Tumor Segmentation. FLARE@MICCAI 2023: 179-193 - 2022
- [j25]Valérie de Crécy-Lagard, Rocio Amorin de Hegedus, Cecilia N. Arighi, Jill Babor, Alex Bateman, Ian Blaby, Crysten Blaby-Haas, Alan J. Bridge, Stephen K. Burley, Stacey Cleveland, Lucy J. Colwell, Ana Conesa, Christian Dallago, Antoine Danchin, Anita de Waard, Adam Deutschbauer, Raquel Dias, Yousong Ding, Gang Fang, Iddo Friedberg, John Gerlt, Joshua Goldford, Mark Gorelik, Benjamin M. Gyori, Christopher S. Henry, Geoffrey Hutinet, Marshall Jaroch, Peter D. Karp, Liudmyla Kondratova, Zhiyong Lu, Aron Marchler-Bauer, Maria Jesus Martin, Claire D. McWhite, Gaurav D. Moghe, Paul Monaghan, Anne Morgat, Christopher J. Mungall, Darren A. Natale, William C. Nelson, Seán I. O'Donoghue, Christine A. Orengo, Katherine H. O'Toole, Predrag Radivojac, Colbie Reed, Richard J. Roberts, Dmitri Rodionov, Irina A. Rodionova, Jeffrey DePons, Lana Saleh, Gloria M. Sheynkman, Françoise Thibaud-Nissen, Paul D. Thomas, Peter Uetz, David Vallenet, Erica Watson Carter, Peter Weigele, Valerie Wood, Elisha M. Wood-Charlson, Jin Xu:
A roadmap for the functional annotation of protein families: a community perspective. Database J. Biol. Databases Curation 2022(2022) (2022) - [j24]Yanhao Huo, Geng Zhao, Luoshan Ruan, Peng Xu, Gang Fang, Fengyue Zhang, Zhenshen Bao, Xin Li:
Detect the early-warning signals of diseases based on signaling pathway perturbations on a single sample. BMC Bioinform. 22-S(12): 367 (2022) - [c27]Jingpeng Ruan, Gang Fang:
Research on Improved Apriori Algorithm Based on Simplified Boolean Matrix. ICBASE 2022: 257-262 - 2021
- [c26]Shan Wang, Gang Fang:
Background Characteristics and Design Innovation Performance. EBEE 2021: 279-284 - [c25]Yuzhi Shang, Chenling Li, Qinghuai Zhang, An Hang, Gang Fang, Yuzhou Pang:
Network pharmacology-based research on the action mechanism of Caulis Sinomenii in treating rheumatoid arthritis. ISAIMS 2021: 289-295 - 2020
- [j23]Peng Xu, Geng Zhao, Zheng Kou, Gang Fang, Wenbin Liu:
Classification of Cancers Based on a Comprehensive Pathway Activity Inferred by Genes and Their Interactions. IEEE Access 8: 30515-30521 (2020) - [j22]Peng Xu, Qian Wu, Yongsheng Rao, Zheng Kou, Gang Fang, Wenbin Liu, Henry Han:
Predicting the Influence of MicroRNAs on Drug Therapeutic Effects by Random Walking. IEEE Access 8: 117347-117353 (2020) - [j21]Gang Fang, Peng Xu, Wenbin Liu:
Automated Ischemic Stroke Subtyping Based on Machine Learning Approach. IEEE Access 8: 118426-118432 (2020) - [j20]Peng Xu, Qian Wu, Deyang Lu, Jian Yu, Yongsheng Rao, Zheng Kou, Gang Fang, Wenbin Liu, Henry Han:
A systematic study of critical miRNAs on cells proliferation and apoptosis by the shortest path. BMC Bioinform. 21(1): 396 (2020) - [j19]Gang Fang, Wenbin Liu, Lixin Wang:
A machine learning approach to select features important to stroke prognosis. Comput. Biol. Chem. 88: 107316 (2020) - [c24]Cui-Ping Pu, Gang Fang, Jie Ren, Yaowen Du:
Research on Smart Home Based on MQTT. ICITEE 2020: 531-535 - [c23]Shan Wang, Gang Fang:
The Transformation Path of Sports Brands in the Context of Consumption Upgrading. MSIE 2020: 125-129
2010 – 2019
- 2019
- [j18]Wenbin Liu, Yugai Du, Gang Fang, Zheng Kou, Xianghong Wang, Henry Han:
Efficient Gaussian sample specific network marker discovery and drug enrichment analysis validation. Comput. Biol. Chem. 83 (2019) - [j17]Gang Fang, Qing Zhou, Jian Wu, Xiaoguang Qi:
The relationship between network capabilities and innovation performance. Ind. Manag. Data Syst. 119(8): 1638-1654 (2019) - [j16]Gang Fang, Izabela E. Annis, Jennifer Elston-Lafata, Samuel Cykert:
Applying machine learning to predict real-world individual treatment effects: insights from a virtual patient cohort. J. Am. Medical Informatics Assoc. 26(10): 977-988 (2019) - 2018
- [j15]Shijia Zhu, Gang Fang:
MatrixEpistasis: ultrafast, exhaustive epistasis scan for quantitative traits with covariate adjustment. Bioinform. 34(14): 2341-2348 (2018) - [j14]Gang Fang, Jiale Wang, Hong Ying:
A Novel Model for Mining Frequent Patterns Based on Embedded Granular Computing. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 26(5): 741-769 (2018) - [j13]Hongjuan Wu, Yulu Liu, Pei Yan, Gang Fang, Jing Zhong:
A frequent itemset mining algorithm based on composite granular computing. J. Comput. Methods Sci. Eng. 18(1): 247-257 (2018) - 2017
- [j12]Zhan Liu, Jialu Shan, Nicole Glassey Balet, Gang Fang:
Semantic social media analysis of Chinese tourists in Switzerland. J. Inf. Technol. Tour. 17(2): 183-202 (2017) - [c22]Wu Wang, Bin Yang, Shikai Shen, Yujian Wang, Gang Fang:
Delay and Capacity in Three-Dimensional Mobile Ad Hoc Networks with Packet Replication. NaNA 2017: 164-169 - 2016
- [c21]Yunfei Yi, Gang Fang, Yangqian Su, Jian Miao, Zhi Yin:
An Improved Artificial Bee Colony Algorithm for Solving Extremal Optimization of Function Problem. ICIC (1) 2016: 703-713 - 2015
- [j11]Nicholas Johnson, Huanan Zhang, Gang Fang, Vipin Kumar, Rui Kuang:
SubPatCNV: approximate subspace pattern mining for mapping copy-number variations. BMC Bioinform. 16: 16:1-16:12 (2015) - [j10]Gang Fang, Yue Wu, Ming Li, Jia Chen:
An Efficient Algorithm for Mining Frequent Closed Itemsets. Informatica (Slovenia) 39(1) (2015) - 2014
- [j9]Noam D. Beckmann, Sashank Karri, Gang Fang, Ali Bashir:
Detecting epigenetic motifs in low coverage and metagenomics settings. BMC Bioinform. 15(S-9): S16 (2014) - [j8]Gang Fang, Yue Wu:
A General Framework Based on Composite Granules for Mining Association Rules. Int. J. Artif. Intell. Tools 23(5) (2014) - 2013
- [j7]Gang Fang, Yue Wu:
Frequent Spatiotemporal Association Patterns Mining Based on Granular Computing. Informatica (Slovenia) 37(4) (2013) - [j6]Zhixing Feng, Gang Fang, Jonas Korlach, Tyson Clark, Khai Luong, Xuegong Zhang, Wing Wong, Eric E. Schadt:
Detecting DNA Modifications from SMRT Sequencing Data by Modeling Sequence Context Dependence of Polymerase Kinetic. PLoS Comput. Biol. 9(3) (2013) - [c20]Daifeng Wang, Eric Pan, Gang Fang, Sunita Kumari, Fei He, Doreen Ware, Sergei Maslov, Mark Gerstein:
Comparative network analysis of gene co-expression networks reveals the conserved and species-specific functions of cell-wall related genes between Arabidopsis and Poplar. BCB 2013: 689 - 2012
- [j5]Gang Fang, Gaurav Pandey, Wen Wang, Manish Gupta, Michael S. Steinbach, Vipin Kumar:
Mining Low-Support Discriminative Patterns from Dense and High-Dimensional Data. IEEE Trans. Knowl. Data Eng. 24(2): 279-294 (2012) - [c19]Nicholas Johnson, Gang Fang, Rui Kuang:
Approximate subspace pattern mining for mapping copy-number variations. BCB 2012: 616 - [c18]Gowtham Atluri, Sanjoy Dey, Gang Fang, Sean Landman, Vanja Paunic, Wen Wang, Michael S. Steinbach, Vipin Kumar:
Invited: Discovering combinatorial biomarkers. ICCABS 2012: 1-2 - [c17]Ling Hu, Yao Li, Jiang Xiong, Gang Fang:
A Filling Algorithm of Mining Constraint Frequent Neighboring Class Set. ICICA (1) 2012: 175-182 - [c16]Renzo Shamey, Juan Lin, Weethima Sawatwarakul, Gang Fang:
Evaluation of Performance of Several Color-Difference Formulae Using a New NCSU Black Experimental Dataset. CIC 2012: 185-190 - 2011
- [c15]Michael S. Steinbach, Haoyu Yu, Gang Fang, Vipin Kumar:
Using Constraints to Generate and Explore Higher Order Discriminative Patterns. PAKDD (1) 2011: 338-350 - [c14]Gang Fang, Jiang Xiong, Hong Ying, Yong-Jian Zhao:
An Algorithm of Constraint Frequent Neighboring Class Sets Mining Based on Separating Support Items. ICSI (2) 2011: 157-163 - [i1]Gang Fang, Wen Wang, Benjamin Oatley, Brian Van Ness, Michael S. Steinbach, Vipin Kumar:
Characterizing Discriminative Patterns. CoRR abs/1102.4104 (2011) - 2010
- [j4]Gang Fang, Nitin Bhardwaj, Rebecca Robilotto, Mark B. Gerstein:
Getting Started in Gene Orthology and Functional Analysis. PLoS Comput. Biol. 6(3) (2010) - [c13]Gang Fang, Jiang Xiong, Xiang-Lin Du, Xiao-Bin Tang:
Frequent neighboring class set mining. FSKD 2010: 1442-1445 - [c12]Gang Fang, Hong Ying, Jiang Xiong, Yong-Jian Zhao:
An algorithm of locating order mining based on sequence number. ICMLC 2010: 403-407 - [c11]Gang Fang, Cheng-Sheng Tu, Jiang Xiong, Zi-Quan Wang:
The application of a top-down algorithm in neighboring class set mining. ISKE 2010: 234-237 - [c10]Gang Fang, Rui Kuang, Gaurav Pandey, Michael S. Steinbach, Chad L. Myers, Vipin Kumar:
Subspace Differential Coexpression Analysis: Problem Definition and a General Approach. Pacific Symposium on Biocomputing 2010: 145-156 - [c9]Gang Fang:
An Algorithm of Alternately Mining Frequent Neighboring Class Set. ICSI (2) 2010: 588-593
2000 – 2009
- 2009
- [j3]Hugo Y. K. Lam, Ekta Khurana, Gang Fang, Philip Cayting, Nicholas Carriero, Kei-Hoi Cheung, Mark B. Gerstein:
Pseudofam: the pseudogene families database. Nucleic Acids Res. 37(Database-Issue): 738-743 (2009) - [j2]Gang Fang, Jin Xu, Shemin Zhang:
Performing DNA computation with RecA-mediated triple-stranded DNA structure. Nat. Comput. 8(1): 149-156 (2009) - [c8]Gowtham Atluri, Rohit Gupta, Gang Fang, Gaurav Pandey, Michael S. Steinbach, Vipin Kumar:
Association Analysis Techniques for Bioinformatics Problems. BICoB 2009: 1-13 - [c7]Jiang Xiong, Gang Fang, Yu-Lu Liu:
An Algorithm of Double Search Association Rules Mining Based on Digital Complementary Set. FSKD (2) 2009: 39-42 - [c6]Yu-Lu Liu, Gang Fang, Jiang Xiong, Yuan-Bin Wu:
An Efficient Algorithm of Mining Association Rules Based on Digital Pure Subset. FSKD (2) 2009: 43-46 - [c5]Gaurav Pandey, Gowtham Atluri, Gang Fang, Rohit Gupta, Michael S. Steinbach, Vipin Kumar:
Association analysis techniques for analyzing complex biological data sets. GENSiPS 2009: 1-4 - 2008
- [c4]Gang Fang, Zukuan Wei, Qian Yin:
An Algorithm of Constrained Spatial Association Rules Based on Binary. ISNN (2) 2008: 21-29 - [c3]Rohit Gupta, Gang Fang, Blayne Field, Michael S. Steinbach, Vipin Kumar:
Quantitative evaluation of approximate frequent pattern mining algorithms. KDD 2008: 301-309 - 2007
- [c2]Gang Fang, Sargur N. Srihari, Harish Srinivasan:
Generative Models for Fingerprint Individuality using Ridge Types. IAS 2007: 423-428 - [c1]Gang Fang, Zukuan Wei, Qian Yin:
The Algorithm of Objective Association Rules Mining Based on Binary. CIS 2007: 214-217
1990 – 1999
- 1998
- [j1]Gang Fang, Ting-Wei Tang:
Simulation of Bistable Laser Diodes with lnhomogeneous Excitation. VLSI Design 8(1-4): 283-287 (1998)
Coauthor Index
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