Selected Papers78. Fuying Dao &, Xueqin Xie &, Hongqi Zhang &, Zhengxing Guan, Changchun Wu, Wei Su, Hongyan Lai, Dong Gao, Yuhe Yang, Yang Zhang, Lin Ning, Shi-Hao Li, Yuduo Hao, Benjamin Lebeau, Crystal Ling Chia Yin, Jian Huang, Melissa Jane Fullwood*, Hao Lin*, Hao Lv*. (2024) PlantEMS: A Comprehensive Database of Epigenetic Modification Sites Across Multiple Plant Species. Plant Communications, accepted. (2023 IF: 9.4) 77. Zahoor Ahmed, Kiran Shahzadi, Sebu Aboma Temesgen, Basharat Ahmad, Xiang Chen, Lin Ning, Hasan Zulfiqar*, Hao Lin*, Yan-Ting Jin*. (2024) A protein pre-trained model-based approach for the identification of the liquid-liquid phase separation (LLPS) proteins. International Journal of Biological Macromolecules, 277: 134146. (2023 IF: 7.7) 76. Xueqin Xie &, Changchun Wu &, Caiyi Ma, Dong Gao, Wei Su, Jian Huang, Kejun Deng*, Dan Yan*, Hao Lin*. (2024) Detecting key genes relative expression orderings as biomarkers for machine learning-based intelligent screening and analysis of Type 2 Diabetes Mellitus. Expert Systems With Applications, 255: 124702. (2023 IF: 7.5) 75. Dong-Xin Ye, Jun-Wen Yu, Rui Li, Yu-Duo Hao, Tian-Yu Wang, Hui Yang*, Hui Ding*. (2024) The prediction of Recombination Hotspot Based on Automated Machine Learning. Journal of Molecular Biology, doi:10.1016/j.jmb.2024.168653. (2022 IF: 5.6) 74. Yi Xu &, Tianyuan Liu &, Yu Yang, Juanjuan Kang, Liping Ren*, Hui Ding*, Yang Zhang*. (2024) ACVPred: Enhanced Prediction of Anti-Coronavirus Peptides by Transfer Learning combined with data augmentation. Future Generation Computer Systems, 160: 305-315. (2022 IF: 7.5) 73. Zahoor Ahmed, Kiran Shahzadi, Yanting Jin, Rui Li, Biffon Manyura Momanyi, Hasan Zulfiqar*, Lin Ning*, Hao Lin*. (2024) Identification of RNA-dependent liquid-liquid phase separation proteins using an artificial intelligence strategy. Proteomics, doi:10.1002/pmic.202400044. (2022 IF: 3.4) 72. Tianyuan Liu, Huiyuan Qiao, Zixu Wang, Xinyan Yang, Xianrun Pan, Yu Yang, Xiucai Ye*, Tetsuya Sakurai, Hao Lin*, Yang Zhang*. (2024) codLncScape provides a self-enriching framework for systematic collection and exploration of coding lncRNAs. Advanced Science, 11: e2400009. (2022 IF: 15.1) 71. Zhi-Feng Gu, Yu-Duo Hao, Tian-Yu Wang, Pei-Ling Cai, Yang Zhang, Ke-Jun Deng, Hao Lin*, Hao Lv*. (2024) Prediction of blood-brain barrier penetrating peptides based on data augmentation with Augur. BMC Biology, 22(1): 86. (2022 IF: 5.4) 70 Zhao-Yue Zhang &, Zi-Jie Sun &, Dong Gao, Yu-Duo Hao, Hao Lin*, Fen Liu*. (2024) Excavation of Gene Markers Associated with Pancreatic Ductal Adenocarcinoma Based on Interrelationships of Gene Expression. IET Systems Biology, DOI: 10.1049/syb2.12090. (2022 IF: 2.3) 69. Zhao-Yue Zhang, Zheng Zhang, Xiucai Ye*, Tetsuya Sakurai, Hao Lin*. (2024) A BERT-based model for the prediction of lncRNA subcellular localization in Homo sapiens. International Journal of Biological Macromolecules, 265(Pt 1): 130659. (2022 IF: 8.025) 68. Tianyuan Liu, Junyang Huang, Delun Luo, Liping Ren, Lin Ning, Jian Huang*, Hao Lin*, Yang Zhang*. (2024) Cm-siRPred: Predicting chemically modified siRNA efficiency based on multi-view learning strategy. International Journal of Biological Macromolecules, 264(Pt 2): 130638. (2022 IF: 8.025) 67. Jia’an Qin &, Yuhe Yang &, Chao Ai &, Zhaoshuai Ji, Wei Chen, Yingchang Song, Jiayu Zeng, Meili Duan, Wenjie Qi, Shutian Zhang, Zhuoling An, Yang Lin, Sha Xu, Kejun Deng*, Hao Lin*, Dan Yan*. (2024) Antibiotic combinations prediction based on machine learning to multicenter clinical data and drug interaction correlation. International journal of Antimicrobial Agents, 63(5): 107122. (2022 IF: 10.8) 66. Xiao-Wei Liu, Han-Lin Li, Cai-Yi Ma, Tian-Yu Shi, Tian-Yu Wang, Dan Yan, Hua Tang*, Hao Lin*, Ke-Jun Deng*. (2024) Predicting the role of the human gut microbiome in Type 1 Diabetes using machine-learning methods. Briefings in Functional Genomics, elae004. (2022 IF: 4.0) 65. Wenfei Liao*, Hao Lin. (2023) Urbanisation drives inter- and intraspecific variation in flight-related morphological traits of aquatic insects at differentlandscape scales. Insect Conservation and Diversity, 17: 287-303. (2022 IF: 3.5) 64. 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*. (2024) Predicting coronary heart disease in Chinese diabetics using machine learning. Computers in Biology and Medicine, 169: 107952. (2022 IF: 7.7) 63. Jie Gao, Yongxian Feng, Yan Yang, Yuetong Shi, Junjie Liu, Hao Lin* and Lirong Zhang*. (2023) Identification of Key DNA methylation sites related to differentially expressed genes in Lung squamous cell carcinoma. Computers in Biology and Medicine, 167: 107615. (2022 IF: 7.7) 62. Yang Zhang, Xianrun Pan, Tianyu Shi, Zhifeng Gu, Zhaochang Yang, Minghao Liu, Yi Xu,Yu Yang, Liping Ren, Xiaoming Song*, Hao Lin*, Kejun Deng*. (2024) P450Rdb: A manually curated database of reactions catalyzed by cytochrome P450 enzymes. Journal of Advanced Research, 63: 35–42. (2023 IF: 11.4) 61. Xiao-Wei Liu, Tian-Yu Shi, Dong Gao, Cai-Yi Ma, Hao Lin*, Dan Yan*, Kejun Deng*. (2023) iPADD: A Computational Tool for Predicting Potential Antidiabetic Drugs Using Machine Learning Algorithms. Journal of Chemical Information and Modeling, 63, 4960−4969. (2022 IF: 5.6) 60. 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*. (2023) A Gender Specific Risk Assessment of Coronary Heart Disease Based on Physical Examination Data. npj Digital Medicine, 6: 136. (2022 IF: 15.2) 59. Yu-He Yang, Cai-Yi Ma, Dong Gao, Xiao-Wei Liu, Shi-Shi Yuan, Hui Ding*. (2023) i2OM: Toward a better prediction of 2′-O-methylation in human RNA. International Journal of Biological Macromolecules, 239: 124247. (2021 IF: 8.025) 58. Fu-Ying Dao, Meng-Lu Liu, Wei Su, Hao Lv, Zhao-Yue Zhang, Hao Lin*, Li Liu*. (2023) AcrPred: A hybrid optimization with enumerated machine learning algorithm to predict Anti-CRISPR proteins. International Journal of Biological Macromolecules, 228: 706-714. (2021 IF: 8.025) 57. Wei Su, Xue-Qin Xie, Xiao-Wei Liu, Dong Gao, Cai-Yi Ma, Hasan Zulfiqar, Hui Yang, Hao Lin*, Xiao-Long Yu*, Yan-Wen Li*. (2023) iRNA-ac4C: a novel computational method for effectively detecting N4-acetylcytidine sites in human mRNA. International Journal of Biological Macromolecules, 277: 1174-1181. (2021 IF: 8.025) 56. Fu-Ying Dao, Hao Lv, Melissa J. Fullwood*, Hao Lin*. (2022) Accurate Identification of DNA Replication Origin by Fusing Epigenomics and Chromatin Interaction Information. Research, 2022: ID 9780293. (2021 IF: 11.036) 55. Jianqiang Xiao&, Mujiexin Liu&, Qinlai Huang, Zijie Sun, Lin Ning, Junguo Duan, Siquan Zhu, Jian Huang, Hao Lin*, Hui Yang*. (2022) Analysis and modeling of Myopia-Related Factors based on Questionnaire survey. Computers in Biology and Medicine, 150: 106162. (2021 IF: 6.698) 54. Yuhe Yang, Dong Gao, Xueqin Xie, Jiaan Qin, Jian Li, Hao Lin*, Dan Yan*, Kejun Deng*. (2022) DeepIDC: A prediction framework of injectable drug combination based on heterogeneous information and deep learning. Clinical Pharmacokinetics, 61: 1749–1759. (2021 IF: 5.577) 53. Zhao-Yue Zhang, Lin Ning, Xiucai Ye*, Yu-He Yang, Yasunori Futamura, Tetsuya Sakurai, Hao Lin*. (2022) iLoc-miRNA: Extracellular/Intracellular miRNA Prediction Using Deep BiLSTM with Attention Mechanism. Briefings in Bioinformatics, bbac395. (2021 IF: 13.994) 52. Zijie Sun&, Qinlai Huang&, Yuhe Yang, Shihao Li, Hao Lv, Yang Zhang, Hao Lin*, Lin Ning*. (2022) PSnoD: identifying potential snoRNA-disease associations based on bounded nuclear norm regularization. Briefings in Bioinformatics, 23(4): bbac240.(2020 IF: 11.622) 51. Hao Lv, Fu-Ying Dao, Hao Lin*. (2022) DeepKla: an attention mechanism-based deep neural network for protein lysine lactylation site prediction iMeta, 1(1):e11. 50. Yu-Mei Han&, Hui Yang&, Qin-Lai Huang, Zi-Jie Sun, Ming-Liang Li, Jing-Bo Zhang, Ke-Jun Deng, Shuo Chen*, Hao Lin*. (2022) Risk prediction of diabetes and pre-diabetes based on physical examination data. Mathematical Biosciences and Engineering, 19(4): 3597-3608. (2020 IF: 2.080) 49. Hongfei Li, Yue Gong, Yifeng Liu, Hao Lin*, Guohua Wang*. (2021) Detection of transcription factors binding to methylated DNA by deep recurrent neural network. Briefings in Bioinformatics, 23(1): bbab533. (2020 IF: 11.622) 48. Lirong Zhang, Yanchao Yang, Lu Chai, Qianzhong Li, Junjie Liu*, Hao Lin*, Li Liu*. (2022) A deep learning model to identify gene expression level using co-binding transcription factor signals. Briefings in Bioinformatics, 23(1): bbab501. (2020 IF: 11.622) 47. Hao Lv&, Yang Zhang&, Jia-Shu Wang, Shi-Shi Yuan, Zi-Jie Sun, Fu-Ying Dao, Zheng-Xing Guan, Hao Lin*, Ke-Jun Deng*. (2022) iRice-MS: an integrated XGBoost model for detecting multi-type post-translational modification sites in rice. Briefings in Bioinformatics, 23(1): bbab486. (2020 IF: 11.622) 46. Zhao-Yue Zhang, Zi-Jie Sun, Yu-He Yang, Hao Lin* (2022) Towards a better prediction of subcellular location of long non-coding RNA. Frontiers of Computer Science, 16(5): 165903. (2020 IF: 2.061) 45. Tianyu Cui, Yiying Dou, Puwen Tan, Zhen Ni, Tianyuan Liu, Duolin Wang, Yan Huang, Kaican Cai, Xiaoyang Zhao, Dong Xu*, Hao Lin*, Dong Wang*. (2022) RNALocate v2.0: an updated resource for RNA Subcellular Localization with increased coverage and annotation. Nucleic Acids Research, 50(D1): D333–D339. (2020 IF: 16.971) 44. Hao Lv, Fu-Ying Dao, Hasan Zulfiqar, Hao Lin*. (2021) DeepIPs: comprehensive assessment and computational identification of phosphorylation site of SARS-CoV-2 infection using a deep learning-based approach. Briefings in Bioinformatics, 22(6): bbab244. (2020 IF: 11.622) 43. Hao Lv, Fu-Ying Dao, Dan Zhang, Hui Yang, Hao Lin*. (2021) Advances in mapping the epigenetic modifications of 5-methylcytosine (5mC), N6-methyladenine (6mA), and N4-methylcytosine (4mC). Biotechnology and Bioengineering, 118(11): 4204-4216. (2020 IF: 4.530) 42. Fu-Ying Dao, Hao Lv, Wei Su, Zi-Jie Sun, Qin-Lai Huang, Hao Lin* (2021) iDHS-Deep: An integrated tool for predicting DNase I hypersensitive sites by deep neural network. Briefings in Bioinformatics, 22(5): bbab047. (2020 IF: 11.622) 41. Hao Lv&, Fu-Ying Dao&, Hasan Zulfiqar, Wei Su, Hui Ding, Li Liu*, Hao Lin* (2021) A sequence-based deep learning approach to predict CTCF-mediated chromatin loop. Briefings in Bioinformatics, 22(5): bbab031. (2020 IF: 11.622) 40. Fu-Ying Dao, Hao Lv, Dan Zhang, Zi-Mei Zhang, Li Liu*, Hao Lin*. (2021) DeepYY1: a deep learning approach to identify YY1-mediated chromatin loops. Briefings in Bioinformatics, 22(4):bbaa356. (2020 IF: 11.622) 39. Hao Lv, Fu-Ying Dao, Zheng-Xing Guan, Hui Yang, Yan-Wen Li*, Hao Lin*. (2021) Deep-Kcr: accurate detection of lysine crotonylation sites using deep learning method. Briefings in Bioinformatics, 22(4): bbaa255. (2020 IF: 11.622) 38. Hasan Zulfiqar, Shi-Shi Yuan, Qin-Lai Huang, Zi-Jie Sun, Fu-Ying Dao, Xiao-Long Yu*, Hao Lin*. (2021) Identification of Cyclin Protein Using Gradient Boost Decision Tree Algorithm. Computational and Structural Biotechnology Journal, 19: 4123–4131. (2020 IF: 7.271) 37. Jianglan Long&, Hui Yang&, Zhirui Yang&, Qingquan Jia, Liwei Liu, Lingwei Kong, Huijing Cui, Suying Ding, Qian Qin, Nana Zhang, Xingzhong Feng, Shuxun Yan, Jinfa Tang, Shuo Chen, Yumei Han, Tao Jiang, Zhen Wen, Ningning Qi, Kejun Deng, Zhi Sun*, Hao Lin*, Dan Yan* (2021) Integrated biomarker profiling of the metabolome associated with impaired fasting glucose and type 2 diabetes mellitus in large-scale Chinese patients. Clinical and Translational Medicine, 11(6): e432. (2020 IF: 11.492) 36. Hui Yang, Yamei Luo, Xiaolei Ren, Ming Wu, Xiaolin He, Bowen Peng, Kejun Deng, Dan Yan, Hua Tang*, Hao Lin* (2021) Risk Prediction of Diabetes: Big data mining with fusion of multifarious physical examination indicators. Information Fusion, 75: 140–149. (2020 IF: 12.975) 35. Wei Su, Meng-Lu Liu, Yu-He Yang, Jia-Shu Wang, Shi-Hao Li, Hao Lv, Fu-Ying Dao, Hui Yang, Hao Lin* (2021) PPD: A Manually Curated Database for Experimentally Verified Prokaryotic Promoters. Journal of Molecular Biology, 433: 166860. (2020 IF: 5.469) 34. Duolin Wang, Zhaoyue Zhang,Yuexu Jiang, Ziting Mao, Dong Wang*, Hao Lin*, Dong Xu* (2021) DM3Loc: Multi-label mRNA subcellular localization prediction and analysis based on multi-head self-attention mechanism. Nucleic Acids Research, 49(8): e46. (2020 IF: 16.971) 33. Dan Zhang&, Zhao-Chun Xu&, Wei Su, Yu-He Yang, Hao Lv, Hui Yang, Hao Lin*. (2021) iCarPS: a computational tool for identifying protein carbonylation sites by novel encoded features. Bioinformatics, 37(2): 171-177. (2020 IF: 6.937) 32. Fu-Ying Dao, Hao Lv, Hasan Zulfiqar, Hui Yang, Wei Su, Hui Gao, Hui Ding, Hao Lin*. (2021) A computational platform to identify origins of replication sites in eukaryotes. Briefings in Bioinformatics, 22(2): 1940–1950. (2020 IF: 11.622) 31. Zhao-Yue Zhang, Yu-He Yang, Hui Ding, Dong Wang*, Wei Chen*, Hao Lin*. (2021) Design powerful predictor for mRNA subcellular location prediction in Homo sapiens. Briefings in Bioinformatics, 22(1): 526–535. (2020 IF: 11.622) 30. Li Liu, Li-Rong Zhang*, Fu-Ying Dao, Yan-Chao Yang, Hao Lin*. (2021) A computational framework for identifying the transcription factors involved in enhancer-promoter loop formation. Molecular Therapy - Nucleic Acids, 23: 347-354. (2020 IF: 8.886) 29. Meng-Lu Liu, Wei Su, Jia-Shu Wang, Yu-He Yang, Hui Yang, Hao Lin*. (2020) Predicting preference of transcription factors for methylated DNA using sequence information. Molecular Therapy - Nucleic Acids, 22, 1043-1050. (2019 IF: 7.032) 28. Zi-Mei Zhang, Jia-Shu Wang, Hasan Zulfiqar, Hao Lv, Fu-Ying Dao, Hao Lin*. (2020) Early Diagnosis of Pancreatic Ductal Adenocarcinoma by Combining Relative Expression Orderings with Machine Learning Method. Frontiers in Cell and Developmental Biology, 8: 582864. (2019 IF: 5.201) 27. Hui Yang, Wuritu Yang, Fu-Ying Dao, Hao Lv, Hui Ding*, Wei Chen*, Hao Lin*. (2020) A comparison and assessment of computational method for identifying recombination hotspots in Saccharomyces cerevisiae. Briefings in Bioinformatics, 21(5): 1568-1580. (2019 IF: 8.990) 26. Hao Lv, Zi-Mei Zhang, Shi-Hao Li, Jiu-Xin Tan, Wei Chen*, Hao Lin*. (2020) Evaluation of different computational methods on 5-methylcytosine sites identification. Briefings in Bioinformatics, 21(3): 982-995. (2019 IF: 8.990) 25. Fu-Ying Dao &, Hao Lv &, Yu-He Yang, Hasan Zulfiqar, Hui Gao, Hao Lin*. (2020) Computational identification of N6-Methyladenosine sites in multiple tissues of mammals. Computational and Structural Biotechnology Journal, 18: 1084–1091. (2019 IF: 6.018) 24. Hao Lv, Fu-Ying Dao, Dan Zhang, Zheng-Xing Guan, Hui Yang, Wei Su, Meng-Lu Liu, Hui Ding, Wei Chen, Hao Lin*. (2020) iDNA-MS: an integrated computational tool for detecting DNA modification sites in multiple genomes. iScience, 23(4): 100991. (2019 IF: 4.447) 23. Zi-Mei Zhang, Jiu-Xin Tan, Fang Wang, Fu-Ying Dao, Zhao-Yue Zhang, Hao Lin*. (2020) Early Diagnosis of Hepatocellular Carcinoma Using Machine Learning Method. Frontiers in Bioengineering and Biotechnology, 8: 254. (2019 IF: 3.644) 22. Zhao-Chun Xu, Peng-Mian Feng, Hui Yang, Wang-Ren Qiu, Wei Chen*, Hao Lin*. (2019) iRNAD: a computational tool for identifying D modification sites in RNA sequence. Bioinformatics, 35 (23), 4922-4929. (2018 IF: 4.531) 21. Hao Lin*, Zhi-Yong Liang, Hua Tang, Wei Chen*. (2019) Identifying sigma70 promoters with novel pseudo nucleotide composition. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 16(4): 1316-1321. (2018 IF: 2.896) 20. Hong-Yan Lai &, Zhao-Yue Zhang &, Zhen-Dong Su, Wei Su, Hui Ding, Wei Chen*, Hao Lin*. (2019) iProEP: a computational predictor for predicting promoter. Molecular Therapy - Nucleic Acids, 17: 337-346. (2018 IF: 5.919) 19. Fu-Ying Dao, Hao Lv, Fang Wang, Chao-Qin Feng, Hui Ding*, Wei Chen*, Hao Lin*. (2019) Identify origin of replication in Saccharomyces cerevisiae using two-step feature selection technique. Bioinformatics, 35(12):2075-2083. (2018 IF: 4.531) 18. Chao-Qin Feng, Zhao-Yue Zhang, Xiao-Juan Zhu, Yan Lin, Wei Chen*, Hua Tang*, Hao Lin*. (2019) iTerm-PseKNC: a sequence-based tool for predicting bacterial transcriptional terminators. Bioinformatics, 35(9): 1469-1477. (2018 IF: 4.531) 17. Li Liu*, Qian-Zhong Li*, Wen Jin, Hao Lv, Hao Lin*. (2019) Revealing gene function and transcription relationship by reconstructing gene-level chromatin interaction. Computational and Structural Biotechnology Journal, 17: 195-205. (2018 IF: 4.72) 16. Xiao-Juan Zhu, Chao-Qin Feng, Hong-Yan Lai, Wei Chen*, Hao Lin*. (2019) Predicting protein structural classes for low-similarity sequences by evaluating different features. Knowledge-Based Systems, 163: 787-793. (2018 IF: 5.101) 15. Zhen-Dong Su, Yan Huang, Zhao-Yue Zhang, Ya-Wei Zhao, Dong Wang, Wei Chen*, Kuo-Chen Chou*, Hao Lin*. (2018) iLoc-lncRNA: predict the subcellular location of lncRNAs by incorporating octamer composition into general PseKNC. Bioinformatics, 34(24): 4196-4204. (2017 IF: 5.481) 14. Hui Yang, Hao Lv, Hui Ding, Wei Chen*, Hao Lin*. (2018) iRNA-2OM: A sequence-based predictor for identifying 2’-O-methylation sites in Homo sapiens. Journal of Computational Biology, 25(11): 1266-1277. (2017 IF: 1.191) 13. Hua Tang*, Ya-Wei Zhao, Ping Zou, Chun-Mei Zhang, Rong Chen, Po Huang, Hao Lin*. (2018) HBPred: a tool to identify growth hormone-binding proteins. International Journal of Biological Sciences, 14(8): 957-964. (2017 IF: 4.057) 12. Hui Yang, Wang-Ren Qiu, Guoqing Liu, Feng-Biao Guo, Wei Chen*, Kuo-Chen Chou*, Hao Lin*. (2018) iRSpot-Pse6NC: Identifying recombination spots in Saccharomyces cerevisiae by incorporating hexamer composition into general PseKNC. International Journal of Biological Sciences, 14(8): 883-891. (2017 IF: 4.057) 11. 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* (2017) Pro54DB: a database for experimentally verified sigma-54 promoters. Bioinformatics, 33(3): 467-469. (2016 IF: 7.307) 10. Ting Zhang, Puwen Tan, Liqiang Wang, Nana Jin, Yana Li, Lin Zhang, Huan Yang, Zhenyu Hu, Lining Zhang, Chunyu Hu, Chunhua Li, Kun Qian, Changjian Zhang, Yan Huang, KongningLi*, Hao Lin*, Dong Wang*. (2017) RNALocate: a resource for RNA Subcellular Localizations. Nucleic Acids Research, 45(D1): D135-D138. (2016 IF: 10.162) 9. Wen-Chao Li, En-Ze Deng, Hui Ding*, Wei Chen*, Hao Lin* (2015) iORI-PseKNC: a predictor for identifying origin of replication with pseudo k-tuple nucleotide composition. Chemometrics and Intelligent Laboratory Systems, 141: 100-106. (2013 IF: 2.381) 8. Hao Lin*, En-Ze Deng, Hui Ding, Wei Chen*, Kuo-Chen Chou*. (2014) iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition. Nucleic Acids Research, 42(21): 12961-12972. (2013 IF: 8.808) 7. Wen-Chao Li, Zhe-Jin Zhong, Pan-Pan Zhu, En-Ze Deng, Hui Ding*, Wei Chen*，Hao Lin*. (2014) Sequence analysis of origins of replication in the Saccharomyces cerevisiae genomes. Frontiers in Microbiology, 5: 574. (2013 IF: 3.9) 6. Hui Ding*, Shou-Hui Guo, En-Ze Deng, Lu-Feng Yuan, Feng-Biao Guo, Jian Huang, Nini Rao, Wei Chen*, Hao Lin*. (2013) Prediction of Golgi-resident protein types by using feature selection technique. Chemometrics and Intelligent Laboratory Systems, 124: 9-13. (2012 IF: 2.291) 5. Chen Ding, Lu-Feng Yuan, Shou-Hui Guo, Hao Lin*, Wei Chen*. (2012) Identification of mycobacterial membrane proteins and their types using over-represented tripeptide compositions. Journal of Proteomics, 77: 321-328. (2010 IF: 5.074) 4. Hao Lin*, Hui Ding. (2011) Predicting ion channels and their types by the dipeptide mode of pseudo amino acid composition. Journal of Theoretical Biology, 269(1): 64-69. (2011 IF: 2.208) 3. Hao Lin*, Hui Ding, Feng-Biao Guo, Jian Huang. (2010) Prediction of subcellular location of mycobacterial protein using feature selection techniques. Molecular Diversity, 14(4): 667-671. (2010 IF: 3.721) 2. Hao Lin*. (2008) The modified Mahalanobis Discriminant for predicting outer membrane proteins by using chou's pseudo amino acid composition.Journal of Theoretical Biology, 252(2): 350-356. (2008 IF: 2.454) 1. Hao Lin, Qian-Zhong Li*. (2007) Using pseudo amino acid composition to predict protein structural class: approached by incorporating 400 dipeptide components. Journal of Computational Chemistry, 28(9): 1463-1466. (2006 IF: 4.893) |