| 56 |
Yang Wang#, Tianyu Zeng#, Deqin Tang, Haipeng Cui, Ying Wan, Hua Tang*. Integrated Multi-Omics Analyses Reveal Lipid Metabolic Signature in Osteoarthritis. Journal of Molecular Biology, 2024, 4:168888. (2023 IF: 4.7)
|
2024 |
| 55 |
Yu-Han Xiu, Si-Lin Sun, Bing-Wei Zhou, Ying Wan, Hua Tang*, Hai-Xia Long*. DGSIST：Clustering Spatial Transcriptome Data based on Deep Graph Structure Infomax. Methods, 2024, 231:226-236. (2023 IF: 4.2)
|
2024 |
| 54 |
Biffon Manyura Momanyi, Sebu Aboma Temesgen, Tian-Yu Wang, Hui Gao, Ru Gao*, Hua Tang*, Li-Xia Tang*. iGATTLDA: Integrative Graph Attention and Transformer-based Model for Predicting lncRNA-Disease Associations. IET Syst Biol. 2024, 18(5):172-182. (2023 IF: 1.9)
|
2024 |
| 53 |
Xiao-Wei Liu#, Han-Lin Li#, Cai-Yi Ma, Tian-Yu Shi, Tian-Yu Wang, Dan Yan, Hua Tang*, Hao Lin*, Ke-Jun Deng*. Predicting the role of the human gut microbiome in Type 1 Diabetes using machine-learning methods. Briefings in Functional Genomics, 2024, 19:elae004. (2022 IF: 4.0)
|
2024 |
| 52 |
Hong-Qi Zhang#. Shan-Hua Liu#. Rui Li. Jun-Wen Yu. Dong-Xin Ye. Shi-Shi Yuan, Hao Lin*. Cheng-Bing Huang*, Hua Tang*. MIBPred: Ensemble Learning-Based Metal lon-Binding Protein Classifier. ACS Omega, 2024, 9(7):8439-8447. (2022 IF: 4.1)
|
2024 |
| 51 |
Biffon Manyura Momanyi, Yu-Wei Zhou, Bakanina Kissanga Grace-Mercure, Sebu Aboma Temesgen, Ahmad Basharat, Lin Ning, Lixia Tang, Hui Gao *, Hao Lin *, Hua Tang*. SAGESDA: Multi-GraphSAGE networks for predicting SnoRNA-disease associations. Current Research in Structural Biology, 2023,7:100122. (2022 IF: 2.8)
|
2023 |
| 50 |
Cai-Yi Ma, Ya-Mei Luo, Tian-Yu Zhang, Yu-Duo Hao, Xue-Qin Xie, Xiao-Wei Liu, Xiao-Lei Ren, Xiao-Lin He, Yu-Mei Han , Ke-Jun Deng, Dan Yan, Hui Yang*, Hua Tang*, Hao Lin*. Predicting coronary heart disease in Chinese diabetics using machine learning. Computers in Biology and Medicine, 2024,169: 107952. (2022 IF: 7.7)
|
2024 |
| 49 |
Yang Liu, Hanlin Li, Tianyu Zeng, Yang Wang, Hongqi Zhang, Ying Wan, Zheng Shi*, Renzhi Cao*, Hua Tang*. Integrated bulk and single-cell transcriptomes reveal pyroptotic signature in prognosis and therapeutic options of hepatocellular carcinoma by combining deep learning. Briefings in Bioinformatics, 2024, 25(1), 1–15. (2022 IF: 9.5)
|
2024 |
| 48 |
Hui Yang, Ya-Mei Luo, Cai-Yi Ma, Tian-Yu Zhang, Tao Zhou, Xiao-Lei Ren, Xiao-Lin He, Ke-Jun Deng, Dan Yan, Hua Tang*, Hao Lin*. A gender specific risk assessment of coronary heart disease based on physical examination data. Npj Digital Medicine, 2023, 6(1):136. doi: 10.1038/s41746-023-00887-8. (2022 IF: 15.2)
|
2023 |
| 47 |
Hua Tang, Qiang Tang, Qian Zhang, Pengmian Feng*. O-GlyThr: prediction of human O-linked threonine glycosites using multi-feature fusion. International journal of Biological Macromolecules. 2023, 242(Pt 2):124761. (2022 IF: 8.2)
|
2023 |
| 46 |
Hua Tang, Qin Yang, Qiang Tang, Xianhai Li, Weijun Ding*, Wei Chen*. Integrated transcriptomics unravels implications of glycosylation-regulating signature in diagnosis, prognosis and therapeutic benefits of hepatocellular carcinoma. Computers in Biology and Medicine. 2022, 148:105886. (2021 IF: 6.6978)
|
2022 |
| 45 |
Qian Zhang, Hanlin Li, Yang Liu, Jian Li, Chunling Wu*, Hua Tang*. Exosomal non-coding RNAs: new insights into the biology of hepatocellular carcinoma. Current Oncology. 2022, 29: 5383–5406. (2021 IF: 3.109) (ESI高被引论文)
|
2022 |
| 44 |
Jiamao Chen, Qian Zhang, Ting Liu, Hua Tang*. Roles of M6A Regulators in Hepatocellular Carcinoma: Promotion or Suppression. Current Gene Therapy, 2022, 22(1): 40-50. (2021 IF: 4.676)
|
2022 |
| 43 |
Ting Liu, Jiamao Chen, Qian Zhang, Kyle Hippe, Cassandra Hunt, Thu Le, Renzhi Cao, Hua Tang*. The Development of Machine Learning Methods in Discriminating Secretory Proteins of Malaria Parasite. Current Medicinal Chemistry, 2022, 29(5): 807-821. (2021 IF: 4.74)
|
2022 |
| 42 |
Hui Yang; Yamei Luo; Xiaolei Ren; Ming Wu; Xiaolin He; Bowen Peng; Kejun Deng; Dan Yan; Hua Tang*, Hao Lin*. Risk Prediction of Diabetes: Big data mining with fusion of multifarious physical examination indicators. Information Fusion, 2021, 75: 140-149. (2020 IF: 12.9746) (ESI高被引论文)
|
2021 |
| 41 |
Ting Liu; Jiamao Chen; Dan Zhang; Qian Zhang; Bowen Peng; Lei Xu*; Hua Tang*. ApoPred: Identification of Apolipoproteins and Their Subfamilies With Multifarious Features. Frontiers in Cell and Developmental Biology, 2021, 8: 621144. (2020 IF: 6.684)
|
2021 |
| 40 |
Xianhai Li, Hua Tang, Qiang Tang, Wei Chen. Decoding the Mechanism of Huanglian Jiedu Decoction in Treating Pneumonia Based on Network Pharmacology and Molecular Docking. Frontiers in Cell and Developmental Biology. 2021, 9: 638366. (2020 IF: 6.684)
|
2020 |
| 39 |
Qiang Tang, Juanjuan Kang, Jiaqing Yuan, Hua Tang, X Li, H Lin, J Huang, W Chen. DNA4mC-LIP: a linear integration method to identify N4-methylcytosine site in multiple species. Bioinformatics, 2020, 36 (11), 3327-3335. (2019 IF: 5.6103)
|
2020 |
| 38 |
Xianhai Li, Qiang Tang, Hua Tang, W Chen. Identifying Antioxidant Proteins by Combining Multiple Methods. Frontiers in Bioengineering and Biotechnology, 2020, 8: 858. (2019 IF: 3.6437)
|
2020 |
| 37 |
Hong-Fei Li, Xian-Fang Wang, Hua Tang*. Predicting Bacteriophage Enzymes and Hydrolases by Using Combined Features. Frontiers in Bioengineering and Biotechnology, 2020, 8: 183. (2019 IF: 3.6417)
|
2020 |
| 36 |
JN Sun, HY Yang, J Yao, H Ding, SG Han, CY Wu, Hua Tang*. Prediction of cyclin protein using two-step feature selection technique. IEEE Access, 2020, 8: 109535-109542. (2019 IF: 3.6417)
|
2020 |
| 35 |
Ting liu, Hua Tang*. A brief survey of Machine Learning Methods in Identification of Mitochondria Proteins in Malaria Parasite. Current Pharmaceutical Design, 2020, 26, 3049-3058. (2019 IF: 2.2082)
|
2020 |
| 34 |
Qin-Lai Huang, Lida Wang, Shu-Guang Han, Hua Tang*. Identification of 2'-O-methylation Site by Investigating Multi-feature Extracting Techniques. Comb Chem High Throughput Screen. 2020, 23(6):527-535. (2019 IF: 1.1951)
|
2020 |
| 33 |
Chao-Qin Feng, Zhao-Yue Zhang, Xiao-Juan Zhu, Yan Lin, Wei Chen, Hua Tang*, and Hao Lin*. iTerm-PseKNC: a sequence-based tool for predicting bacterial transcriptional terminators. Bioinformatics, 2019, 35(9): 1469-1477. (2018 IF: 4.5306) (ESI高被引论文)
|
2019 |
| 32 |
Jiu-Xin Tan, Shi-Hao Li, Zi-Mei Zhang, Cui-Xia Chen, Wei Chen*, Hua Tang*, Hao Lin*. Identification of hormone binding proteins based on machine learning methods. Mathematical Biosciences and Engineering, 2019, 16(4): 2466-2480. (2018 IF: 1.3129) (ESI高被引论文)
|
2019 |
| 31 |
Shi-hao Li, Jun Zhang, Ya-wei Zhao, Fu-Ying Dao, Hui Ding, Wei Chen, Hua Tang*. iPhoPred: A Predictor for Identifying Phosphorylation Sites in Human Protein. IEEE Access, 2019, 7: 177517-177528. (2018 IF: 4.0983)
|
2019 |
| 30 |
Dan Zhang, Zheng-Xing Guan, Zi-Mei Zhang, Shi-Hao Li, Fu-Ying Dao, Hua Tang*, and Hao Lin*. Recent Development of Computational Predicting Bioluminescent Proteins. Current Pharmaceutical Design, 2019, 25: 4171-4180. (2018 IF: 2.412)
|
2019 |
| 29 |
Hao Lin*, Zhi-Yong Liang, Hua Tang, Wei Chen*. Identifying sigma70 promoters with novel pseudo nucleotide composition. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2019, 16(4): 1316-1321. (2018 IF: 3.702)
|
2019 |
| 28 |
Huan-Huan Wei, Wuritu Yang, Hua Tang, Hao Lin*. The development of machine learning methods in cell-penetrating peptides identification: a brief review. Current Drug Metabolism, 2019, 20(3): 217-223. (2018 IF: 2.277)
|
2019 |
| 27 |
Hong-Yan Lai, Chao-Qin Feng, Zhao-Yue Zhang, Hua Tang, Wei Chen*, Hao Lin*. A brief survey of machine learning application in cancerlectins identification. Current Gene Therapy, 2018, doi: 10.2174/1566523218666180913112751. (2017 IF: 1.9428)
|
2018 |
| 26 |
Wang-Ren Qiu, Bi-Qian Sun, Hua Tang, Jian Huang*, Hao Lin*. Identify and analysis crotonylation sites in histone by using support vector machines. Artificial Intelligence In Medicine, 2017, 83: 75-81. (2016 IF: 2.009)
|
2017 |
| 25 |
Hao Lin*, Zhi-Yong Liang, Hua Tang, Wei Chen*. Identifying sigma70 promoters with novel pseudo nucleotide composition. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2017, DOI: 10.1109/TCBB.2017.2666141. (2016 IF: 3.702)
|
2017 |
| 24 |
Pengmian Feng, Jidong Zhang, Hua Tang, Wei Chen*, Hao Lin*. Predicting the Organelle Location of Noncoding RNAs Using Pseudo Nucleotide Compositions. Interdisciplinary Sciences-Computational Life Sciences, 2017, 9: 540–544. (2016 IF: 0.7531)
|
2017 |
| 23 |
Zhi-Yong Liang, Hong-Yan Lai, Huan Yang, Chang-Jian Zhang, Hui Yang, Huan-Huan Wei, Xin-Xin Chen, Ya-Wei Zhao, Zhen-Dong Su, Wen-Chao Li, En-Ze Deng, Hua Tang, Wei Chen*, Hao Lin*. Pro54DB: a database for experimentally verified sigma-54 promoters. Bioinformatics, 2017, 33(3): 467-469. (2016 IF: 7.307)
|
2017 |
| 22 |
Wei Chen*, Hua Tang, Hao Lin*. MethyRNA: A web-server for identification of N6-methyladenosine sites. Journal of Biomolecular Structure & Dynamics, 2017, 35(3): 683-687. (2016 IF: 3.123)
|
2017 |
| 21 |
Hua Tang*, Ya-Wei Zhao, Ping Zou, Chun-Mei Zhang, Rong Chen, Po Huang, Hao Lin*. HBPred: a tool to identify growth hormone-binding proteins. International Journal of Biological Sciences, 2018, 14(8): 957-964. (2017 IF: 4.057) (ESI高被引论文)
|
2018 |
| 20 |
Quan Zou, Kaiyang Qu, Yamei Luo, Dehui Yin, Ying Ju, Hua Tang*. Predicting Diabetes Mellitus With Machine Learning Techniques. Frontiers in Genetics. 2018, 9: 515. (2017 IF: 4.1508)
|
2018 |
| 19 |
Hua Tang*, Chunmei Zhang, Rong Chen, Po Huang, Chenggang Duan, Ping Zou*. Identification of secretory proteins of malaria parasite by feature selection technique. Letters in Organic Chemistry, 2017, 14(9): 621-624. (2016 IF: 0.43)
|
2017 |
| 18 |
Ya-Wei Zhao, Zhen-Dong Su, Wuritu Yang, Hao Lin*, Wei Chen*, Hua Tang* IonchanPred 2.0: a tool to predict ion channels and their types. International Journal of Molecular Sciences, 2017, 18: 1838. (2016 IF: 3.226)
|
2017 |
| 17 |
Fu-Ying Dao, Hui Yang, Zhen-Dong Su, Wuritu Yang, Yun Wu, Ding Hui, Wei Chen*, Hua Tang*, Hao Lin*. Recent Advances in Conotoxin Classification by using machine learning methods. Molecules, 2017, 22: 1057. (2016 IF: 2.8609)
|
2017 |
| 16 |
Hong-Yan Lai, Xin-Xin Chen, Wei Chen, Hua Tang*, Hao Lin*. Sequence-based predictive modeling to identify cancerlectins. Oncotarget, 2017, 8(17): 28169-28175. (2016 IF: 5.1678)
|
2017 |
| 15 |
Hua Tang, Ren-Zhi Cao, Wen Wang, Tie-Shan Liu, Li-Ming Wang*, Chun-Mei He*. A two-step discriminated method to identify thermophilic proteins. International Journal of Biomathematics, 2017, 10, 1750050. (2016 IF: 1.05)
|
2017 |
| 14 |
Hua Tang, Yunchun Yang, Chunmei Zhang, Rong Chen, Po Huang, Chenggang Duan, Ping Zou. Predicting presynaptic and postsynaptic neurotoxins by developing feature selection technique. BioMed Research International, 2017: 3267325. (2016 IF: 2.4763)
|
2017 |
| 13 |
Yun Wu, Yufei Zheng, Hua Tang*. Identifying the types of ion channel-targeted conotoxins by incorporating new properties of residues into pseudo amino acid composition. BioMed Research International, 2016: 3981478. (2015 IF: 2.1342)
|
2016 |
| 12 |
Chang-Jian Zhang, Hua Tang, Wen-Chao Li, Hao Lin*, Wei Chen*, Kuo-Chen Chou*. iOri-Human: identify human origin of replication by incorporating dinucleotide physicochemical properties into pseudo nucleotide composition. Oncotarget, 2016, 7(43): 69783-69793. (2015 IF: 5.0081)
|
2016 |
| 11 |
Ya-Wei Zhao, Hong-Yan Lai, Hua Tang, Wei Chen*, Hao Lin*. Prediction of phosphothreonine sites in human proteins by fusing different features. Scientific Reports, 2016, 6:34817. (2015 IF: 5.2282)
|
2016 |
| 10 |
Huan Yang, Hua Tang, Xin-Xin Chen, Chang-Jian Zhang, Pan-Pan Zhu, Hui Ding, Wei Chen*, Hao Lin*. Identification of secretory proteins in mycobacterium tuberculosis using pseudo amino acid composition. BioMed Research International, 2016: 1654623. (2015 IF: 2.1342)
|
2016 |
| 9 |
Wei Chen*, Pengmian Feng, Hua Tang, Hui Ding, Hao Lin*. RAMPred: identifying the N1-methyladenosine sites in eukaryotic transcriptomes. Scientific Reports, 2016, 6: 31080. (2015 IF: 5.2282)
|
2016 |
| 8 |
Wei Chen*, Hua Tang, Jing Ye, Hao Lin*, Kuo-Chen Chou*. iRNA-PseU: Identifying RNA pseudouridine sites. Molecular Therapy - Nucleic Acids, 2016, 5: e332. (2015 IF: 5.0477)
|
2016 |
| 7 |
Xin-Xin Chen, Hua Tang, Wen-Chao Li, Hao Wu, Wei Chen*, Hui Ding*, Hao Lin*. Identification of Bacterial Cell Wall Lyases via Pseudo Amino Acid Composition. BioMed Research International, 2016: 1654623. (2015 IF: 2.1342)
|
2016 |
| 6 |
Yun Wu, Hua Tang, Wei Chen, Hao Lin*. Predicting human enzyme family classes by using pseudo amino acid composition. Current Proteomics, 2016, 13(2): 99-104. (2015 IF: 0.59)
|
2016 |
| 5 |
Wei Chen*, Pengmian Feng, Hua Tang, Hui Ding, Hao Lin*. Identifying 2′-O-methylationation sites by integrating nucleotide chemical properties and nucleotide compositions. Genomics, 2016, 107: 255-258. (2015 IF: 2.3862)
|
2016 |
| 4 |
Hui Ding, Wuritu Yang, Hua Tang, Peng-Mian Feng, Jian Huang, Wei Chen*, Hao Lin*. PHYPred: a tool for identifying bacteriophage enzymes and hydrolases. Virologica Sinica, 2016, 31(2): 350-352. (2015 IF: 2.4147)
|
2016 |
| 3 |
Hua Tang*, Ping Zou, Chunmei Zhang, Rong Chen, Wei Chen*, Hao Lin*. Identification of apolipoprotein using feature selection technique. Scientific Reports, 2016, 6: 30441. (2015 IF: 5.2282)
|
2016 |
| 2 |
Hua Tang*, Zhen-Dong Su, Huan-Huan Wei, Wei Chen, Hao Lin*. Prediction of cell-penetrating peptides with feature selection techniques. Biochemical and Biophysical Research Communications, 2016, 477: 150-154. (2015 IF: 2.3713)
|
2016 |
| 1 |
Hua Tang*, Wei Chen, Hao Lin*. Identification of immunoglobulins using Chou’s pseudo amino acid composition with feature selection technique. Molecular BioSystems, 2016, 12: 1269-1275. (2015 IF: 2.8289)
|
2016 |