Microbial Bioinformatics Group

 

Representative Work

 

  1. Bo Wang1, Yanzhi Xia1, Mingyue Cheng1, Huili Luo1, Luxi Xue1, Anyue Gong1, Xu Liu, Gaoqi Liao, Jieping Song*, Kang Ning*. Insurance reimbursement for special foods and Phe levels in patients with PKU in China. JAMA Network Open, 2024, accepted. (SCI impact factor 13.8)
  2. Mingyue Cheng1, Hong Zhou1, Haobo Zhang1, Xinchao Zhang, Shuting Zhang, Hong Bai, Yuguo Zha, Dan Luo, Dan Che, Siyuan Chen, Kang Ning*, Wei Liu*. Hidden Links Between Skin Microbiome and Skin Imaging Phenome. Genomics Proteomics Bioinformatics, 2024, accepted. (SCI impact factor 9.5)
  3. Mingyue Cheng1, Shuai Luo1, Peng Zhang1, Guangzhou Xiong, Kai Chen, Chuanqi Jiang, Fangdian Yang, Hanhui Huang, Pengshuo Yang, Guanxi Liu, Yuhao Zhang, Sang Ba, Ping Yin, Jie Xiong*, Wei Miao*, Kang Ning*. A genome and gene catalog of Tibetan Plateau's aquatic microbiomes. Nature Communications, 2024, 15 (1): 1438. (SCI impact factor 16.6)
  4. Wei Xu1, Teng Wang1, Nan Wang1, Haohong Zhang1, Yuguo Zha, Lei Ji, Yuwen Chu, Kang Ning*. Artificial intelligence enabled microbiome-based diagnosis models for a broad spectrum of cancer types. Briefings in Bioinformatics, 2023, 24 (3): bbad178. doi: 10.1093/bib/bbad178. (SCI impact factor 9.5)
  5. Nan Wang1, Teng Wang1, Kang Ning*. Refining biome labeling for large-scale microbial community samples Leveraging neural networks and transfer learning. Environmental Science and Ecotechnology, 2023, 17: 100304. doi: 10.1016/j.ese.2023.100304. (SCI impact factor 12.6)
  6. Haohong Zhang1, Hui Chong1, Qingyang Yu, Yuguo Zha, Mingyue Cheng, Kang Ning*. Tracing human life trajectory using gut microbial communities by context-aware deep learning. Briefings in Bioinformatics, 2023, 24 (1): bbac629. doi: 10.1093/bib/bbac629. (SCI impact factor 9.5)
  7. Junwei Chen, Lei Ji, Guangzhou Xiong, Kang Ning*. The distinct microbial community patterns and pathogen transmission routes in Intensive Care Units. Journal of Hazardous Materials, 2023, 441: 129964. doi: 10.1016/j.jhazmat.2022.129964. (SCI impact factor 13.6)
  8. Nan Wang, Mingyue Cheng, Kang Ning*. Overcoming regional limitations: Transfer learning for cross-regional microbial-based diagnosis of diseases . Gut, 2022, 72 (10): 2004-2006. doi: 10.1136/gutjnl-2022-328216. (SCI impact factor 24.5)
  9. Hui Chong1, Yuguo Zha1, Qingyang Yu1, Mingyue Cheng, Guangzhou Xiong, Nan Wang, Xinhe Huang, Shijuan Huang, Chuqing Sun, Sicheng Wu, Wei-Hua Chen, Luis Pedro Coelho, Kang Ning*. EXPERT: Transfer Learning-enabled context-aware microbial community classification. Briefings in Bioinformatics, 2022, 23 (6): bbac396. doi: 10.1093/bib/bbac396. (SCI impact factor 9.5)
  10. Qian Zhou1, Xue Zhu1, Yangzhen Li, Pengshuo Yang, Shengpeng Wang, Kang Ning*, Songlin Chen*. Intestinal microbiome-mediated resistance against vibriosis for Cynoglossus semilaevis. Microbiome, 2022, 10(1):153. doi: 10.1186/s40168-022-01346-4. (SCI impact factor 15.5)
  11. Mingyue Cheng1, Yan Zhao1, Yazhou Cui, Chaofang Zhong, Yuguo Zha, Shufeng Li, Guangxiang Cao, Mian Li, Lei Zhang*, Kang Ning*, Jinxiang Han*. Stage-specific roles of microbial dysbiosis and metabolic disorders in rheumatoid arthritis. Annals of the Rheumatic Diseases, 2022, 81 (12): 1669-1677. doi: 10.1136/ard-2022-222871. (SCI impact factor 27.4)
  12. Chaofang Zhong1, Chaoyun Chen 1, Xi Gao, Chongyang Tan, Hong Bai*, Kang Ning*. Multi-omics profiling reveals comprehensive microbe-plant-metabolite regulation patterns for medicinal plant Glycyrrhiza uralensis Fisch. Plant Biotechnology Journal, 2022, (10) : 1874-1887. doi: 10.1111/pbi.13868. (SCI impact factor 13.8)
  13. Pengshuo Yang, Shiguang Hao, Maozhen Han, Junjie Xu, Shaojun Yu, Chaoyun Chen, Houjin Zhan*, Kang Ning*. Analysis of Antibiotic Resistance Genes Reveals Its Important Role in Influencing the Community Structure of Ocean Microbiome. Science of the Total Environment, 2022, 823: 153731. doi: 10.1016/j.scitotenv.2022.153731. (SCI impact factor 9.8)
  14. Yuguo Zha1, Hui Chong1, Pengshuo Yang1, Kang Ning*. Microbial Dark Matter: from Discovery to Applications. Genomics Proteomics Bioinformatics, 2022, 20 (5): 867-881. doi: 10.1016/j.gpb.2022.02.007. (SCI impact factor 9.5)
  15. Lu Zhang1, Lei Ji1, Kang Ning*, Zhi Wang*. Linkage and driving mechanisms of antibiotic resistome in surface-groundwater and their responses to the land use and seasonal variation. Water Research, 2022, 215: 118279. doi: 10.1016/j.watres.2022.118279. (SCI impact factor 12.8)
  16. Yuguo Zha, Kang Ning*. Ontology-aware Neural Network: A general framework for pattern mining from microbiome data. Briefings in Bioinformatics, 2022, 23 (2): bbac005. doi: 10.1093/bib/bbac005. (SCI impact factor 9.5)
  17. Yan Zhao1,Mingyue Cheng1, Liang Zou, Luxu Yin, Xue Zhu, Yuguo Zha , Lei Zhang*, Kang Ning*, Jinxiang Han*. Hidden link in gut-joint axis: gut microbes promote rheumatoid arthritis at early stage by enhancing ascorbate degradation. Gut , 2022, 71 (5): 1041-1043. doi: 10.1136/gutjnl-2021-325209. (SCI impact factor 24.5)
  18. Yuguo Zha1, Hui Chong1, Hao Qiu, Kai Kang, Yuzheng Dun, Zhixue Chen, Xuefeng Cui*, Kang Ning*. Ontology-Aware Deep Learning Enables Ultrafast and Interpretable Source Tracking among Sub-Million Microbial Community Samples from Hundreds of Niches. Genome Medicine, 2022, 14 (1): 43. doi: 10.1186/s13073-022-01047-5. (SCI impact factor 12.3)
  19. Lei Ji1, Lu Zhang1, Zhi Wang*, Xue Zhu, Kang Ning*. High biodiversity and distinct assembly patterns of microbial communities in groundwater compared with surface water. Science of the Total Environment, 2022, 834: 155345. doi: 10.1016/j.scitotenv.2022.155345. (SCI impact factor 9.8)
  20. Kang Ning, Lei Ji1, Lu Zhang1, Xue Zhu, Huimin Wei, Maozhen Han, Zhi Wang*. Is rice-crayfish co-culture a better aquaculture model: from the perspective of antibiotic resistome profiles. Environmental Pollution, 2022, 292 (Pt B): 118450. doi: 10.1016/j.envpol.2021.118450. (SCI impact factor 8.9)
  21. Pengshuo Yang, Wei Zheng, Kang Ning*, Yang Zhang*. Decoding the link of microbiome niches with homologous sequences enables accurately targeted protein structure prediction. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2021, 118 (49): e2110828118. doi: 10.1073/pnas.2110828118. (SCI impact factor 11.1)
  22. Mo Zhu1, Kai Kang1, Kang Ning*. Meta-Prism: Ultra-fast and highly accurate microbial community structure search utilizing dual-indexing and parallel computation. Briefings in Bioinformatics, 2021, 22 (1): 557-567. doi: 10.1093/bib/bbaa009. (SCI impact factor 9.5)
  23. Wanglin Liu1, Mingyue Cheng1, Jinman Li1, Peng Zhang, Hang Fan, Qinghe Hu, Maozhen Han, Longxiang Su, Huaiwu He, Yigang Tong*, Kang Ning*, Yun Long*. Classification of the Gut Microbiota of Patients in Intensive Care Units During Development of Sepsis and Septic Shock.Genomics Proteomics Bioinformatics, 2020, 18 (6):696-707. doi: 10.1016/j.gpb.2020.06.011. (SCI impact factor 9.5)
  24. Zhi Wang*, Maozhen Han, Enhua Li, Xi Liu, Huimin Wei, Chao Yang, Shaoyong Lu*, Kang Ning*. Distribution of antibiotic resistance genes in an agriculturally disturbed lake in China: their links with microbial communities, antibiotics, and water quality. Journal of Hazardous Material. 2020, 393: 122426. doi: 10.1016/j.jhazmat.2020.122426. (SCI impact factor 13.6)
  25. Maozhen Han1, Kun Yang 1, Pengshuo Yang, Chaofang Zhong , Chaoyun Chen ,Song Wang* , Qunwei Lu* ,Kang Ning* . Stratification of Athletes' Gut Microbiota: The Multifaceted Hubs associated with Dietary Factors, Physical Characteristics and Performance. Gut Microbes, 2020,12 (1): 1-18. doi: 10.1080/19490976.2020.1842991. (SCI impact factor 12.2)
  26. Hong Liu1, Maozhen Han1, Shuai Cheng Li1, Guangming Tan, Shiwei Sun, Zhiqiang Hu, Pengshuo Yang, Rui Wang, Yawen Liu, Feng Chen, Jianjun Peng, Hong Peng, Hongxing Song, Yang Xia, Liqun Chu, Quan Zhou, Feng Guan, Jing Wu*, Dongbo Bu*, Kang Ning*. Resilience of Human Gut Microbial Communities for the Long Stay with Multiple Dietary Shifts. Gut , 2019,68 (12): 2254-2255. doi: 10.1136/gutjnl-2018-317298. (SCI impact factor 24.5)
  27. Yan Wang1, Qiang Shi1, Pengshuo Yang1, Chengxin Zhang1, Golam Mortuza, Zhidong Xue*, Kang Ning*, Yang Zhang*.Fueling ab initio folding with marine microbiome enables structure and function predictions of new protein families. Genome Biology , 2019, 20 (1): 229. doi: 10.1186/s13059-019-1823-z. (SCI impact factor 12.3)
  28. Yigang Tong*, Kang Ning*. The Fast Track for Microbiome Research. Genomics Proteomics Bioinformatics, 2019, 17 (1): 1-3. doi: 10.1016/j.gpb.2019.04.001. (SCI impact factor 9.5)
  29. Mingyue Cheng, Kang Ning*. Stereotype About Enterotype: the Old and New Ideas. Genomics Proteomics Bioinformatics, 2019, 17 (1): 4-12. doi: 10.1016/j.gpb.2018.02.004. (SCI impact factor 9.5)
  30. Maozhen Han1, Melissa Dsouza1, Chunyu Zhou1, Hongjun Li, Junqian Zhang, Chaoyun Chen, Qi Yao, Chaofang Zhong, Hao Zhou, Jack A Gilbert*, Zhi Wang*, Kang Ning*. Agricultural Risks Factors Influence Microbial Ecology in Honghu Lake. Genomics Proteomics Bioinformatics , 2019, 17 (1): 76-90. doi: 10.1016/j.gpb.2018.04.008. (SCI impact factor 9.5)
  31. Houjin Zhang*, Kang Ning*. The Tara Oceans Project: New opportunities and greater challenges ahead. Genomics Proteomics Bioinformatics, 2015, 13 (5):275-277. doi: 10.1016/j.gpb.2015.08.003. (SCI impact factor 9.5)

 

Publications

Journal papers

  1. Bo Wang1, Yanzhi Xia1, Mingyue Cheng1, Huili Luo1, Luxi Xue1, Anyue Gong1, Xu Liu, Gaoqi Liao, Jieping Song*, Kang Ning*. Insurance reimbursement for special foods and Phe levels in patients with PKU in China. JAMA Network Open, 2024, accepted. (SCI impact factor 13.8)
  2. Mingyue Cheng1, Hong Zhou1, Haobo Zhang1, Xinchao Zhang, Shuting Zhang, Hong Bai, Yuguo Zha, Dan Luo, Dan Che, Siyuan Chen, Kang Ning*, Wei Liu*. Hidden Links Between Skin Microbiome and Skin Imaging Phenome. Genomics Proteomics Bioinformatics, 2024, accepted. (SCI impact factor 9.5)
  3. Mingyue Cheng1, Shuai Luo1, Peng Zhang1, Guangzhou Xiong, Kai Chen, Chuanqi Jiang, Fangdian Yang, Hanhui Huang, Pengshuo Yang, Guanxi Liu, Yuhao Zhang, Sang Ba, Ping Yin, Jie Xiong*, Wei Miao*, Kang Ning*. A genome and gene catalog of Tibetan Plateau's aquatic microbiomes. Nature Communications, 2024, 15 (1): 1438. (SCI impact factor 16.6)
  4. Yuli Zhang1, Haohong Zhang1, Bingqiang Liu*, Kang Ning*. Highly accurate and interpretable diagnosis of pancreatic cancer by integrative modeling using gut microbiome and exposome data. iScience, 2024, doi: 10.2139/ssrn.4510602. (SCI impact factor 6.107)
  5. Yuguo Zha, Cheng Chen, Qihong Jiao, Xiaomei Zeng*, Xuefeng Cui*, Kang Ning*. Comprehensive profiling of antibiotic resistance genes in diverse environments and novel function discovery. The Innovation Life, 2024, accepted.
  6. Haobo Zhang1, Si Liu1, Yi Wang, Hanhui Huang, Lukang Sun, Youyuan Yuan, Liming Cheng, Xin Liu*，Kang Ning*. Deep learning enhanced the diagnosis power of glycome for multiple cancers based on serum samples. iScience, 2024, 27 (1), 108715. doi: 10.1016/j.isci.2023.108715. (SCI impact factor 6.107)
  7. Chaofang Zhong , Gang Hu, Cong Hu, Chaohao Xu , Zhonghua Zhang*，Kang Ning*. Pan-genome analysis reveals genetic characteristics and nitrogen fixation profile of Bradyrhizobium. iScience, 2024, 27 (2): 108948. doi: 10.1016/j.isci.2024.108948. (SCI impact factor 6.107)
  8. Si Liu1, Chang Tu1, Haobo Zhang1, Hanhui Huang, Yuanyuan Liu, Yi Wang, Liming Cheng, Bi-Feng Liu, Kang Ning*, Xin Liu*. Noninvasive serum N-glycans associated with ovarian cancer diagnosis and precancerous lesion prediction. Journal of Ovarian Research, 2024, Jan 27; 17 (1): 26. doi: 10.1186/s13048-024-01350-2. (SCI impact factor 4.000)
  1. Lei Ji, Haohong Zhang, Geng Tian, Shuxue Xi, Yuwen Chu, Yumeng Zhang, Jinyang Liu, Kang Ning*, Jialiang Yang*. Tumor microenvironment interplay amid microbial community, host gene expression and pathological features elucidates cancer heterogeneity and prognosis risk . The Innovation Life, 2023, 1 (2): 100028. https://doi.org/10.59717/j.xinn-life.2023.100028.
  2. Xuebo Li, Xuelian Yuan, Xiumin Zhu, Changjun Li, Lei Ji, Kebo Lv, Geng Tian, Kang Ning*, Jialiang Yang*. A meta-analysis of tissue microbial biomarkers for recurrence and metastasis in multiple cancer types. Journal of Medical Microbiology, 2023, 72 (8). doi: 10.1099/jmm.0.001744. (SCI impact factor 3)
  3. Pengshuo Yang1, Jialiang Yang1, Haixia Long, Kaimei Huang, Lei Ji, Hanyang Lin, Xiuli Jiang, Geng Tian*, Kang Ning*. MicroEXPERT: Microbiome profiling platform with cross-study metagenome-wide association analysis functionality. iMeta, 2023, 2: e131. https://doi.org/10.1002/imt2.131.
  4. Xue Zhu, Pengshuo Yang, Guangzhou Xiong, Huimin Wei, Lu Zhang, Zhi Wang* , Kang Ning*. Microbial biogeochemical cycling reveals the sustainability of the rice-crayfish coculture model. iScience, 2023, 26 (5): 106769. doi: 10.1016/j.isci.2023.106769. (SCI impact factor 5.8)
  5. Wei Xu1, Teng Wang1, Nan Wang1, Haohong Zhang1, Yuguo Zha, Lei Ji, Yuwen Chu, Kang Ning*. Artificial intelligence enabled microbiome-based diagnosis models for a broad spectrum of cancer types. Briefings in Bioinformatics, 2023, 24 (3): bbad178. doi: 10.1093/bib/bbad178. (SCI impact factor 9.5)
  6. Nan Wang1, Teng Wang1, Kang Ning*. Refining biome labeling for large-scale microbial community samples Leveraging neural networks and transfer learning. Environmental Science and Ecotechnology, 2023, 17: 100304. doi: 10.1016/j.ese.2023.100304. (SCI impact factor 12.6)
  7. Haohong Zhang1, Kang Ning*. Utilizing Tumor Microenvironment Microbial Profiles and Host Gene Expressions for Reliable Survival Subtyping in Liver Hepatocellular Carcinoma. Gut, 2023, 72 (Suppl 1): A151–A153. (abstract). (SCI impact factor 24.5)
  8. Lei Ji1, Haohong Zhang1, Kang Ning*, Jialiang Yang*. Disentangling the Complex Interplay of Pathological Images, Tumor Microbes and Tumor Microenvironment and Elucidation of the Intertumor Heterogeneity. Gut, 2023, 72 (Suppl 1): A84–A86. (abstract). (SCI impact factor 24.5)
  9. Yuli Zhang1, Haohong Zhang1, Kang Ning*, Binqiang Liu*. Integration of Gut Microbiome and Exposome Data through Artificial Intelligence Enables Accurate Diagnosis of Pancreatic Cancer with High Fidelity and Interpretability. Gut, 2023, 72 (Suppl 1): A74–A76. (abstract). (SCI impact factor 24.5)
  10. Wenyan Ding1, Guangzhou Xiong1, Mingyue Cheng1, Longxiang Su*, Kang Ning*, Yun Long*. Enterotype-dependent microbial response to cardiac surgery with cardiopulmonary bypass. Gut, 2023, 72 (Suppl 1): A87–A89. (abstract). (SCI impact factor 24.5)
  11. Yayi Yuan, Dongjing Chai, Ruifeng Zhang, Jiao Cheng, Juancong Dong, Hongyan Liu, Zhongxin Zhang, Xuhong Dang*, Kang Ning*. Effects of Neutron and Gamma Rays Combined Irradiation on the Transcriptional Profile of Human Peripheral Blood. Radiation Research, 2023, 200: 65–79. doi: 10.1667/RADE-22-00147.2. (SCI impact factor 3.4)
  12. 赖奇龙, 姚帅, 查毓国, 白虹*, 宁康*. 微生物组生物合成基因簇发掘方法及应用前景. 合成生物学, 2023, 4 (2): 611-627. doi: 10.12211/2096-8280.2022-075.
  13. Guangzhou Xiong, Lei Ji, Mingyue Cheng, Kang Ning*. Niche-based microbial community assemblage in urban transit systems and the influence of city characteristics. Microbiology Spectrum, 2023, 11 (2): e0016723. doi: 10.1128/spectrum.00167-23. (SCI impact factor 3.7)
  14. Pengshuo Yang1, Xue Zhu1, Kang Ning*. Microbiome-based enrichment pattern mining has enabled a deeper understanding of the biome–species–function relationship. Communications Biology, 2023, 6 (1): 391. doi: 10.1038/s42003-023-04753-x. (SCI impact factor 5.9)
  15. Haohong Zhang1, Hui Chong1, Qingyang Yu, Yuguo Zha, Mingyue Cheng, Kang Ning*. Tracing human life trajectory using gut microbial communities by context-aware deep learning. Briefings in Bioinformatics, 2023, 24 (1): bbac629. doi: 10.1093/bib/bbac629. (SCI impact factor 9.5)
  16. Junwei Chen, Lei Ji, Guangzhou Xiong, Kang Ning*. The distinct microbial community patterns and pathogen transmission routes in Intensive Care Units. Journal of Hazardous Materials, 2023, 441: 129964. doi: 10.1016/j.jhazmat.2022.129964. (SCI impact factor 13.6)
  17. Yuxue Li1, Gang Xie1, Yuguo Zha1, Kang Ning*. GAN-GMHI: a generative adversarial network augmented the gut microbiome-based health index by profoundly improved discrimination power. Journal of Genetics and Genomics, 2023, 50 (12): 1026-1028. doi: 10.1016/j.jgg.2023.03.009. (SCI impact factor 5.9)
  1. Xue Zhu1, Qi Yao1, Pengshuo Yang, Dan Zhao, Ronghua Yang*, Hong Bai*, Kang Ning*. Multi-omics approaches for in-depth understanding of therapeutic mechanism for Traditional Chinese Medicine. Frontiers in Pharmacology, 2022, 13: 1031051. doi: 10.3389/fphar.2022.1031051. (SCI impact factor 5.6)
  2. Qinglong Wu1, Kang Ning1, Xiaoxiao Zhao1, Feng Liao, Min Wang, Longgang Chang, Yanmin Liu, Jinmiao Chen*, Ming Zhao*, Zhangran Chen*. Editorial: The Role of Omics Characteristics in the Diagnosis, Treatment, and Prognosis of Autoimmune Diseases. Frontiers in Immunology, 2022, 13: 1069918. doi: 10.3389/fimmu.2022.1069918. (SCI impact factor 7.3)
  3. Nan Wang, Mingyue Cheng, Kang Ning*. Overcoming regional limitations: Transfer learning for cross-regional microbial-based diagnosis of diseases . Gut, 2022, 72 (10): 2004-2006. doi: 10.1136/gutjnl-2022-328216. (SCI impact factor 24.5)
  4. Yongmei Lan1, Kang Ning1, Yanqing Ma, Jin Zhao, Caihong Ci, Xiao Yang, Fulong An, Zilong Zhang, Yan An, Mingyue Cheng*. HDL-C as a potential medium between depletion of Lachnospiraceae genera and hypertension under high-calorie diet. Microbiology Spectrum, 2022, 10 (6): e0234922. doi: 10.1128/spectrum.02349-22. (SCI impact factor 3.7)
  5. Chaofang Zhong, Kang Ning*, Gang Hu*. Pan-genome analysis of Campylobacter: Insights on the genomic diversity and virulence profile. Microbiology Spectrum, 2022, 10 (5): e0102922. doi: 10.1128/spectrum.01029-22. (SCI impact factor 3.7)
  6. Hui Chong1, Yuguo Zha1, Qingyang Yu1, Mingyue Cheng, Guangzhou Xiong, Nan Wang, Xinhe Huang, Shijuan Huang, Chuqing Sun, Sicheng Wu, Wei-Hua Chen, Luis Pedro Coelho, Kang Ning*. EXPERT: Transfer Learning-enabled context-aware microbial community classification. Briefings in Bioinformatics, 2022, 23 (6): bbac396. doi: 10.1093/bib/bbac396. (SCI impact factor 9.5)
  7. Qian Zhou1, Xue Zhu1, Yangzhen Li, Pengshuo Yang, Shengpeng Wang, Kang Ning*, Songlin Chen*. Intestinal microbiome-mediated resistance against vibriosis for Cynoglossus semilaevis. Microbiome, 2022, 10(1):153. doi: 10.1186/s40168-022-01346-4. (SCI impact factor 15.5)
  8. Mingyue Cheng1, Yan Zhao1, Yazhou Cui, Chaofang Zhong, Yuguo Zha, Shufeng Li, Guangxiang Cao, Mian Li, Lei Zhang*, Kang Ning*, Jinxiang Han*. Stage-specific roles of microbial dysbiosis and metabolic disorders in rheumatoid arthritis. Annals of the Rheumatic Diseases, 2022, 81 (12): 1669-1677. doi: 10.1136/ard-2022-222871. (SCI impact factor 27.4)
  9. Pengshuo Yang1, Jidong Lang1, Hongjun Li, Jinxiang Lu, Hanyang Lin, Geng Tian Hong Bai*, Jialiang Yang*, Kang Ning*. TCM-Suite: A comprehensive and holistic platform for Traditional Chinese Medicine component identification and network pharmacology analysis. iMeta, 2022, 1: e47. doi: 10.1002/imt2.47.
  10. Lei Ji,Zhi Wang*, Lu Zhang, Xue Zhu, Kang Ning*. Determining the primary sources of groundwater bacterial communities in a large-scale plain area: Microbial source tracking and interpretation for different land use patterns. Agriculture Ecosystems and Environment, 2022, 338：108092. doi: 10.1016/j.agee.2022.108092. (SCI impact factor 6.6)
  11. Chaofang Zhong1, Chaoyun Chen 1, Xi Gao, Chongyang Tan, Hong Bai*, Kang Ning*. Multi-omics profiling reveals comprehensive microbe-plant-metabolite regulation patterns for medicinal plant Glycyrrhiza uralensis Fisch. Plant Biotechnology Journal, 2022, (10) : 1874-1887. doi: 10.1111/pbi.13868. (SCI impact factor 13.8)
  12. Kai Kang, Hui Chong, Kang Ning*. Meta-Prism 2.0: Enabling algorithm and web server for ultra-fast, memory-efficient, and accurate analysis among millions of microbial community samples. GigaScience, 2022, 11 : giac073. (SCI impact factor 9.2)
  13. Yan Zhao1,Mingyue Cheng1, Liang Zou, Luxu Yin, Xue Zhu, Yuguo Zha , Lei Zhang*, Kang Ning*, Jinxiang Han*. Hidden link in gut-joint axis: gut microbes promote rheumatoid arthritis at early stage by enhancing ascorbate degradation. Gut , 2022, 71 (5): 1041-1043. doi: 10.1136/gutjnl-2021-325209. (SCI impact factor 24.5)
  14. Xue Zhu, Lei Ji, Mingyue Cheng, Huimin Wei, Zhi Wang*, Kang Ning*. Sustainability of the rice-crayfish co-culture aquaculture model: Microbiome profiles based on multi-kingdom analyses. Environmental Microbiome, 2022, 17 (1): 27. doi: 10.1186/s40793-022-00422-4. (SCI impact factor 7.9)
  15. Chaoyun Chen1, Chaofang Zhong1, Xi Gao, Chongyang Tan, Hong Bai*, Kang Ning*. Glycyrrhiza uralensis Fisch. Root-associated microbiota: the multifaceted hubs associated with environmental factors, growth status and accumulation of secondary metabolites. Environmental Microbiome, 2022, 17 (1): 23. doi: 10.1186/s40793-022-00418-0. (SCI impact factor 7.9)
  16. Yuguo Zha1, Hui Chong1, Hao Qiu, Kai Kang, Yuzheng Dun, Zhixue Chen, Xuefeng Cui*, Kang Ning*. Ontology-Aware Deep Learning Enables Ultrafast and Interpretable Source Tracking among Sub-Million Microbial Community Samples from Hundreds of Niches. Genome Medicine, 2022, 14 (1): 43. doi: 10.1186/s13073-022-01047-5. (SCI impact factor 12.3)
  17. Lei Ji1, Lu Zhang1, Zhi Wang*, Xue Zhu, Kang Ning*. High biodiversity and distinct assembly patterns of microbial communities in groundwater compared with surface water. Science of the Total Environment, 2022, 834: 155345. doi: 10.1016/j.scitotenv.2022.155345. (SCI impact factor 9.8)
  18. Qi Yao1, Xue Zhu1, Maozhen Han, Chaoyun Chen, Wei Li, Hong Bai, Kang Ning*. Decoding herbal materials of TCM preparations with the multi-barcode sequencing approach. Scientific Reports, 2022, 12 (1): 5988. doi: 10.1038/s41598-022-09979-z. (SCI impact factor 4.6)
  19. Yuguo Zha1, Hui Chong1, Pengshuo Yang1, Kang Ning*. Microbial Dark Matter: from Discovery to Applications. Genomics Proteomics Bioinformatics, 2022, 20 (5): 867-881. doi: 10.1016/j.gpb.2022.02.007. (SCI impact factor 9.5)
  20. Lu Zhang1, Lei Ji1, Kang Ning*, Zhi Wang*. Linkage and driving mechanisms of antibiotic resistome in surface-groundwater and their responses to the land use and seasonal variation. Water Research, 2022, 215: 118279. doi: 10.1016/j.watres.2022.118279. (SCI impact factor 12.8)
  21. Cheng Chen1, Yuguo Zha1, Daming Zhu, Kang Ning*, Xuefeng Cui*. ContactLib-ATT: A Structure-Based Search Engine for Homologous Proteins. IEEE-ACM Transactions on Computational Biology and Bioinformatics, 2022, 20 (6): 3421-3429. doi: 10.1109/TCBB.2022.3197802. (SCI impact factor 4.5)
  22. Mingyue Cheng1, Hong Liu1, Maozhen Han1, Shuai Cheng Li, Dongbo Bu, Shiwei Sun, Zhiqiang Hu, Pengshuo Yang, Rui Wang, Yawen Liu, Feng Chen, Jianjun Peng, Hong Peng, Hongxing Song, Yang Xia, Liqun Chu, Quan Zhou, Feng Guan, Jing Wu*, Guangming Tan*, Kang Ning*. Microbiome resilience and health implications for people in half-year travel. Frontiers in Immunology, 2022, 13: 848994. doi: 10.3389/fimmu.2022.848994. (SCI impact factor 7.3)
  23. Pengshuo Yang, Shiguang Hao, Maozhen Han, Junjie Xu, Shaojun Yu, Chaoyun Chen, Houjin Zhan*, Kang Ning*. Analysis of Antibiotic Resistance Genes Reveals Its Important Role in Influencing the Community Structure of Ocean Microbiome. Science of the Total Environment, 2022, 823: 153731. doi: 10.1016/j.scitotenv.2022.153731. (SCI impact factor 9.8)
  24. Yuguo Zha, Kang Ning*. Ontology-aware Neural Network: A general framework for pattern mining from microbiome data. Briefings in Bioinformatics, 2022, 23 (2): bbac005. doi: 10.1093/bib/bbac005. (SCI impact factor 9.5)
  25. Pengshuo Yang, Kang Ning*. How much metagenome data is needed for protein structure prediction: The advantages of targeted approach from the ecological and evolutionary perspectives. iMeta, 2022, 1: e9. doi: 10.1002/imt2.9.
  26. Die Dai, Jiaying Zhu, Chuqing Sun, Min Li, Jinxin Liu, Sicheng Wu, Kang Ning , Li-jie He* , Xing-Ming Zhao* , Wei-Hua Chen*. GMrepo v2: a curated human gut microbiome database with special focus on disease markers and cross-dataset comparison. Nucleic Acids Research, 2022, 50 (D1): D777-D784. doi: 10.1093/nar/gkab1019. (SCI impact factor 14.9)
  27. Kang Ning, Lei Ji1, Lu Zhang1, Xue Zhu, Huimin Wei, Maozhen Han, Zhi Wang*. Is rice-crayfish co-culture a better aquaculture model: from the perspective of antibiotic resistome profiles. Environmental Pollution, 2022, 292 (Pt B): 118450. doi: 10.1016/j.envpol.2021.118450. (SCI impact factor 8.9)
  1. Xue Zhu, Gaichao Hong, Ying Li, Pengshuo Yang, Mingyue Cheng, Lei Zhang, Yuxue Li, Lei Ji, Gangping Li, Chaoyun Chen, Chaofang Zhong, Yu Jin, Min Yang, Hanhua Xiong, Wei Qian, Zhen Ding, Kang Ning* , Xiaohua Hou*. Understanding of the site-specific microbial patterns towards accurate identification for patients with diarrhea-predominant irritable bowel syndrome. Microbiology Spectrum, 2021, 9 (3): e0125521. doi: 10.1128/Spectrum.01255-21. (SCI impact factor 3.7)
  2. Pengshuo Yang, Wei Zheng, Kang Ning* , Yang Zhang*. Decoding the link of microbiome niches with homologous sequences enables accurately targeted protein structure prediction. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2021, 118 (49): e2110828118. doi: 10.1073/pnas.2110828118. (SCI impact factor 11.1)
  3. Mingyue Cheng, Xueling Ge, Chaofang Zhong, Ruiqing Fu, Kang Ning*, Shuhua Xu*. Micro-co-evolution of Host Genetics with Gut Microbiome in Three Chinese Ethnic Groups. Journal of Genetics and Genomics, 2021, 48 (11): 972-983. doi: 10.1016/j.jgg.2021.09.002. (SCI impact factor 5.9)
  4. Dongni Yu, Mingyue Cheng, Lixin Guo, Wenli Liu, Ye Liu, Kang Ning*, Yigang Tong, Xuejiao Yan, Lei Qiu, Haimei Qi*. Influence of Oral Nutritional Agents rich in Soluble Dietary Fiber on Intestinal Flora of Elderly Males with Malnutrition. Aging Medicine, 2021, 4 (3): 162-168. doi: 10.1002/agm2.12174.
  5. Tao Bai1, Xue Zhu1, Xiang Zhou, Denise Grathwohl, Pengshuo Yang, Yuguo Zha, Yu Jin, Hui Chong, Qingyang Yu, Nora Isberner, Dongke Wang, Lei Zhang, K. Martin Kortüm, Jun Song, Leo Rasche, Hermann Einsele, Kang Ning*, Xiaohua Hou*. Reliable and Interpretable Mortality Prediction With Strong Foresight in COVID-19 Patients: An International Q2 Study From China and Germany. Frontiers in Artificial Intelligence , 2021, 4: 672050. doi: 10.3389/frai.2021.672050.
  6. Mingyue Cheng1, Zhangyu Cheng1, Yiyan Yu, Wangjie Liu, Ruihao Li, Zhenyi Guo, Jiyue Qin, Zhi Zeng, Lin Di, Yufeng Mo, Chunxiu Pan, Yuanhao Liang, Jinman Li, Yigang Tong, Yunjun Yan*, Yi Zhan*, Kang Ning*. An Engineered Genetic Circuit for Lactose Intolerance Alleviation.BMC Biology, 2021, 19 (1): 137. doi: 10.1186/s12915-021-01070-9. (SCI impact factor 5.4)
  7. Ping Hu, Xiuyi Chen, Xufeng Chu, Yi Ye, Yi Wang, Maozhen Han, Xue Yang, Jiaying Yuan, Li Zha, Chun-Xia Yang, Xiao-Rong Qi, Kang Ning, Bo Xiong, Xiong-Fei Pan*, An Pan*. Association of gut microbiota during early pregnancy with risk of incident gestational diabetes mellitus: a nested case-control study. Journal of Clinical Endocrinology & Metabolism, 2021, 106 (10): e4128-e4141. doi: 10.1210/clinem/dgab346. (SCI impact factor 5.8)
  8. Lixiao Wang1, Maozhen Han1, Xi Li, Bingbing Yu, Huading Wang, Amjed Ginawi, Kang Ning*, Yunjun Yan*. Mechanisms of niche-neutrality balancing can drive the assembling of microbial community. Molecular Ecology, 2021, 30 (6): 1492-1504. doi: 10.1111/mec.15825. (SCI impact factor 4.9)
  9. Yuguo Zha，Hui Chong , Kang Ning*. Microbiome sample comparison and search: from pair-wise calculation to model-based matching. Frontiers in Microbiology, 2021, 12: 642439. doi: 10.3389/fmicb.2021.642439. (SCI impact factor 5.2)
  10. Xue Zhu1, Jiyue Qin1, Chongyang Tan , Kang Ning*. The seasonal changes of the gut microbiome of the population living in traditional lifestyles are represented by characteristic species-level and functionallevel SNP enrichment patterns. BMC Genomics, 2021, 22 (1): 83. doi: 10.1186/s12864-021-07372-0. (SCI impact factor 4.4)
  11. Chaofang Zhong, Lusheng Wang*, Kang Ning*.Integrating pan-genome with metagenome for microbial community profiling. Computational and Structural Biotechnology Journal, 2021, 19: 1458-1466. doi: 10.1016/j.csbj.2021.02.021. (SCI impact factor 6)
  12. Mo Zhu1, Kai Kang1, Kang Ning*. Meta-Prism: Ultra-fast and highly accurate microbial community structure search utilizing dual-indexing and parallel computation. Briefings in Bioinformatics, 2021, 22 (1): 557-567. doi: 10.1093/bib/bbaa009. (SCI impact factor 9.5)
  1. Chaofang Zhong, Lusheng Wang*, Kang Ning*. Pan-genome study of Thermococcales reveals extensive genetic diversity and genetic evidence of thermophilic adaption. Environmental Microbiology, 2020, 23 (7): 3599-3613. doi: 10.1111/1462-2920.15234. (SCI impact factor 5.1)
  2. Wanglin Liu1, Mingyue Cheng1, Jinman Li1, Peng Zhang, Hang Fan, Qinghe Hu, Maozhen Han, Longxiang Su, Huaiwu He, Yigang Tong*, Kang Ning*, Yun Long*. Classification of the Gut Microbiota of Patients in Intensive Care Units During Development of Sepsis and Septic Shock.Genomics Proteomics Bioinformatics, 2020, 18 (6):696-707. doi: 10.1016/j.gpb.2020.06.011. (SCI impact factor 9.5)
  3. Maozhen Han, Yuguo Zha, Hui Chong, Chaofang Zhong, Kang Ning*. Utilizing microbiome approaches to assist source tracking, treatment and prevention of COVID-19: Review and Assessment. Computational and Structural Biotechnology Journal, 2020, 18: 3615-3622. doi: 10.1016/j.csbj.2020.11.027. (SCI impact factor 6)
  4. Maozhen Han1, Kun Yang1, Pengshuo Yang, Chaofang Zhong, Chaoyun Chen, Song Wang*, Qunwei Lu*,Kang Ning*. Stratification of Athletes' Gut Microbiota: The Multifaceted Hubs associated with Dietary Factors, Physical Characteristics and Performance. Gut Microbes, 2020, 12 (1): 1-18. doi: 10.1080/19490976.2020.1842991. (SCI impact factor 12.2)
  5. Pengshuo Yang, Chongyang Tan, Maozhen Han, Lin Cheng, Xuefeng Cui, Kang Ning*. Correlation-Centric Network (CCN) representation for microbial co-occurrence patterns: new insights for microbial ecology.NAR Genomics and Bioinformatics, 2020, 2 (2): lqaa042. doi: 10.1093/nargab/lqaa042.
  6. Xue Zhu, Xi Li, Wenjie Wang, Kang Ning*. Bacterial contamination screening and interpretation for biological laboratory environments.Medicine in Microecology, 2020, 5: 100021. doi: 10.1016/j.medmic.2020.100021.
  7. Runzhi Zhang1, Gao Xi1, Hong Bai*, Kang Ning*. Traditional Chinese Medicine and gut microbiome: Their respective and concert effects on healthcare.Frontiers in Pharmacology, 2020, 11: 538. doi: 10.3389/fphar.2020.00538. (SCI impact factor 5.6)
  8. Zhi Wang*, Maozhen Han, Enhua Li, Xi Liu, Huimin Wei, Chao Yang, Shaoyong Lu*, Kang Ning*. Distribution of antibiotic resistance genes in an agriculturally disturbed lake in China: their links with microbial communities, antibiotics, and water quality.Journal of Hazardous Material, 2020, 393: 122426. doi: 10.1016/j.jhazmat.2020.122426.(SCI impact factor 13.6)
  9. 韩毛振1, 朱雪1, 宁康*. “水土不服”和肠道菌群：永远在旅行的小家伙们. 科学(上海), 2020, 72 (4): 33-35.
  10. Lixiao Wang1, Maozhen Han1, Xi Li, Amjed Ginawi, Kang Ning*, Yunjun Yan*. Niche and Neutrality Work Differently in Microbial Communities in Fluidic and Non-fluidic Ecosystems.Molecular Ecology, 2020, 79 (3): 527-538. doi: 10.1007/s00248-019-01439-y. (SCI impact factor 4.9)
  11. Wei Miao*, Lirong Song, Sang Ba, Longxian Zhang, Guiquan Guan, Zhang Zhang, Kang Ning. Protist 10,000 Genomes Project.The Innovation, 2020, 1 (3): 100058. doi: 10.1016/j.xinn.2020.100058.
  1. Hong Liu1, Maozhen Han1, Shuai Cheng Li1, Guangming Tan, Shiwei Sun, Zhiqiang Hu, Pengshuo Yang, Rui Wang, Yawen Liu, Feng Chen, Jianjun Peng, Hong Peng, Hongxing Song, Yang Xia, Liqun Chu, Quan Zhou, Feng Guan, Jing Wu*, Dongbo Bu*, Kang Ning*. Resilience of Human Gut Microbial Communities for the Long Stay with Multiple Dietary Shifts. Gut , 2019, 68 (12): 2254-2255. doi: 10.1136/gutjnl-2018-317298. (SCI impact factor 31.793)
  2. Runzhi Zhang, Xue Zhu, Hong Bai*, Kang Ning*. Network Pharmacology Databases for Traditional Chinese Medicine: Review and Assessment.Frontiers in Pharmacology, 2019, 10: 123. doi: 10.3389/fphar.2019.00123. (SCI impact factor 5.81)
  3. Chaofang Zhong, Maozhen Han, Pengshuo Yang, Chaoyun Chen, Hui Yu, Lusheng Wang*,Kang Ning*. Comprehensive Analysis Reveals the Evolution and Pathogenicity of Aeromonas: viewed from both single isolated species and microbial community.mSystems, 2019, 4 (5): e00252-19. doi: 10.1128/mSystems.00252-19. (SCI impact factor 6.496)
  4. Sicheng Wu1, Chuqing Sun1, Yanze Li, Teng Wang, Longhao Jia, Senying Lai, Yaling Yang, Pengyu Luo, Die Dai, Yong-Qing Yang, Qibin Luo, Na L Gao, Kang Ning, Li-jie He*, Xing-Ming Zhao*, Wei-Hua Chen*. GMrepo: a database of curated and consistently annotated human gut metagenomes.Nucleic Acids Research, 2019, 48 (D1): D545-D553. doi: 10.1093/nar/gkz764. (SCI impact factor 16.971)
  5. Yan Wang1, Qiang Shi1, Pengshuo Yang1, Chengxin Zhang1, Golam Mortuza, Zhidong Xue*, Kang Ning*, Yang Zhang*.Fueling ab initio folding with marine microbiome enables structure and function predictions of new protein families. Genome Biology , 2019, 20 (1): 229. doi: 10.1186/s13059-019-1823-z.(SCI impact factor 17.906)
  6. Han Zhao, Shaliu Fu, Yifei Yu, Zhanbing Zhang, Ping Li, Qin Ma, Wei Jia, Kang Ning, Shen Qu, Qi Liu*. MetaMed:Linking microbiota functions with medicine therapeutics.mSystems, 2019, 4 (5): e00413-19. doi: 10.1128/mSystems.00413-19. (SCI impact factor 6.496)
  7. Mingyue Cheng, Le Cao, Kang Ning*. Microbiome big-data mining and applications using single-cell technologies and metagenomics approaches towards precision medicine.Frontiers in Genetics, 2019, 10: 972. doi: 10.3389/fgene.2019.00972. (SCI impact factor 4.599)
  8. Chaoyun Chen, Zhangyu Cheng, Ruiqiao He, Maozhen Han, Yuguo Zha, Pengshuo Yang, Qi Yao, Hao Zhou, Chaofang Zhong, Kang Ning*. The seasonal dynamics and the influence of human activities on campus outdoor microbial communities. Frontiers in Microbiology, 2019, 10: 1579. doi: 10.3389/fmicb.2019.01579. (SCI impact factor 5.64)
  9. Wang Xi1, Yan Gao1, Zhangyu Cheng, Chaoyun Chen, Maozhen Han, Pengshuo Yang, Guangzhou Xiong, Kang Ning*. Using QC-Blind for quality control and contamination screening of bacteria DNA sequencing data without reference genome. Frontiers in Microbiology, 2019, 10: 1560. doi: 10.3389/fmicb.2019.01560. (SCI impact factor 5.64 )
  10. Yigang Tong*, Kang Ning*. The Fast Track for Microbiome Research. Genomics Proteomics Bioinformatics, 2019, 17 (1): 1-3. doi: 10.1016/j.gpb.2019.04.001. (SCI impact factor 9.5)
  11. Hong Bai, Xianhong Li, Hongjun Li, Jialiang Yang, Kang Ning*. Biological ingredient complement chemical ingredient in the assessment of the quality of TCM preparations. Scientific Reports, 2019, 9 (1): 5853. doi: 10.1038/s41598-019-42341-4. (SCI impact factor 4.379)
  12. Chaoyun Chen1, Andreas Harst1, Wuxin You, Jian Xu, Kang Ning*, Ansgar Poetsch*. Proteomic study uncovers molecular principles of single-cell level phenotypic heterogeneity in lipid storage of Nannochloropsis oceanica. Biotechnology for Biofuels, 2019, 12: 21. doi: 10.1186/s13068-019-1361-7. (SCI impact factor 6.04)
  13. Pengshuo Yang, Shaojun Yu, Lin Cheng, Kang Ning*. Meta-Network: Optimized species-species network analysis for microbial communities. BMC Genomics, 2019, 20 (Suppl 2) : 187. doi: 10.1186/s12864-019-5471-1. (SCI impact factor 3.969)
  14. Mingyue Cheng, Kang Ning*. Stereotype About Enterotype: the Old and New Ideas. Genomics Proteomics Bioinformatics, 2019, 17 (1): 4-12. doi: 10.1016/j.gpb.2018.02.004. (SCI impact factor 9.5)
  15. Maozhen Han1, Melissa Dsouza1, Chunyu Zhou1, Hongjun Li, Junqian Zhang, Chaoyun Chen, Qi Yao, Chaofang Zhong, Hao Zhou, Jack A Gilbert*, Zhi Wang*, Kang Ning*. Agricultural Risks Factors Influence Microbial Ecology in Honghu Lake. Genomics Proteomics Bioinformatics , 2019, 17 (1): 76-90. doi: 10.1016/j.gpb.2018.04.008. (SCI impact factor 9.5)
  16. Chongyang Tan1, Wei Cui1, Xinping Cui*, Kang Ning*. Strain-GeMS: Optimized subspecies identification from microbiome data based on accurate variant modeling. Bioinformatics, 2019, 35 (10): 1789-1791. doi: 10.1093/bioinformatics/bty844.(SCI impact factor 6.937)
  1. Maozhen Han, Pengshuo Yang, Chaofang Zhong, Kang Ning*. The Human Gut Virome in Hypertension. Frontiers in Microbiology, 2018,9: 3150. doi: 10.3389/fmicb.2018.03150. (SCI impact factor 5.64)
  2. Qian Zhou, Xiaoqun Su, Gongchao Jing, Songlin Chen*, Kang Ning*. RNA-QC-chain: comprehensive and fast quality control for RNA-Seq data. BMC Genomics, 2018, 19 (1): 144. doi: 10.1186/s12864-018-4503-6. (SCI impact factor 3.969)
  3. 曹乐, 宁康. 昆虫肠道的宏基因组学：微生物大数据的新疆界. 微生物学报, 2018, 58 (6): 964-984. doi: 10.13343/j.cnki.wsxb.20170353.
  4. Chaofang Zhong, Maozhen Han, Shaojun Yu, Pengshuo Yang, Hongjun Li, Kang Ning*. Pan-genome analyses of 24 Shewanella strains re-emphasize the diversification of their functions yet evolutionary dynamics of metal-reducing pathway. Biotechnology for Biofuels, 2018, 11: 193. doi: 10.1186/s13068-018-1201-1. (SCI impact factor 6.04)
  1. Chaofang Zhong, Shaojun Yu, Maozhen Han, Jiahuan Chen, Kang Ning*. Heterogeneous circRNA expression profiles and regulatory functions among HEK293T single cells. Scientific reports, 2017, 7 (1): 14393. doi: 10.1038/s41598-017-14807-w. (SCI impact factor 4.379)
  2. Run-zhi Zhang, Shao-jun Yu, Hong Bai*, Kang Ning*. TCM-Mesh: The database and analytical system for network pharmacology analysis for TCM preparations. Scientific reports, 2017, 7 (1): 2821. doi: 10.1038/s41598-017-03039-7. (SCI impact factor 4.379)
  3. Dan Wang, Shuaicheng Li, Fei Guo, Kang Ning, Lusheng Wang. Core-genome scaffold comparison reveals the prevalence that inversion events are associated with pairs of inverted repeats. BMC Genomics, 2017, 18 (1): 268. doi: 10.1186/s12864-017-3655-0. (SCI impact factor 3.969)
  4. 张国庆, 宁康, 职晓阳, 刘婉, 徐萍, 周豪魁, 胡黔楠, 赵国屏. 建设微生物组大数据中心 发挥长期科学影响. 中国科学院院刊, 2017, 32 (3): 280-289.
  5. Yin-Ying Wang, Hong Bai, Runzhi Zhang, Kang Ning, Xing-Ming Zhao*. Predicting new indications of compounds with a network pharmacology approach: Liuwei Dihuang Wan as case studies. oncotarget, 2017, 8 (55): 93957-93968. doi: 10.18632/oncotarget.21398. (SCI impact factor 5.168)
  6. Kang Ning*,Xinming Zhao, Ansgar Poetsch, WeiHua Chen, Jialiang Yang. Computational Molecular Networks and Network Pharmacology. BioMed research international, 2017, 8 (55): 93957–93968. doi: 10.1155/2017/7573904. (SCI impact factor 3.411)
  7. Jifang Yan, Guohui Chuai,Tao Qi,Fangyang Shao,Chi Zhou,Chenyu Zhu, Kang Ning, Yuan He, Qi Liu. MetaTopics: an integration tool to analyze microbial community profile by topic model. BMC Genomics, 2017, 18 (1): 962. doi: 10.1186/s12864-016-3257-2. (SCI impact factor 3.969)
  8. Gongchao Jing, Zheng Sun, Honglei Wang, Yanhai Gong, Shi Huang, Kang Ning, Jian Xu, Xiaoquan Su. Parallel-META 3: Comprehensive taxonomical and functional analysis platform for efficient comparison of microbial communities. Scientific reports, 2017, 7: 40371. doi: 10.1038/srep40371. (SCI impact factor 4.379)
  1. Jiahuan Chen, Qian Zhou, Yangfan Wang, Kang Ning*. Single-cell SNP analyses and interpretations based on RNA-Seq data for colon cancer research. Scientific reports, 2016, 6: 34420. doi: 10.1038/srep34420. (SCI impact factor 4.379)
  2. LiJuan Su, LeLe Yang, Shi Huang, XiaoQuan Su, Yan Li, FengQin Wang, EnTao Wang, Jian Xu, AnDong Song, Kang Ning*. Comparative Gut Microbiomes of Four Species Representing the Higher and the Lower Termites.Journal of Insect Science, 2016, 16 (1): 97. doi: 10.1093/jisesa/iew081. (SCI impact factor 1.857)
  3. Gabriel Murillo, Na You, Xiaoquan Su, Wei Cui, Kang Ning and Xinping Cui*. MultiGeMS: detection of SNVs from multiple samples using model selection on high-throughput sequencing data. Bioinformatics, 2016, 32 (10): 1486-92. doi: 10.1093/bioinformatics/btv753 10. (SCI impact factor 6.937)
  4. Maozhen Han1, Yanhai Gong1, Chunyu Zhou1, Junqian Zhang, Zhi Wang, Kang Ning*. Comparison and Interpretation of Taxonomical Structure of Bacterial Communities in Two Types of Lakes on Yun-Gui plateau of China. Scientific reports, 2016, 6: 30616. doi: 10.1038/srep30616. (SCI impact factor 4.379)
  5. Shuyan Tang1, Wang Xi1, Zhangyu Cheng1, Lei Yin, Ruihao Li, Guozhao Wu, Wangjie Liu, Junjie Xu, Shuaiying Xiang, Yanxiao Zheng, Qian Ge, Kang Ning*, Yunjun Yan*, Yi Zhan*. A Living Eukaryotic Autocementation Kit from Surface Display of Silica Binding Peptides on Yarrowia lipolytica. ACS synthetic biology, 2016, 5 (12): 1466-1474. doi: 10.1021/acssynbio.6b00085. (SCI impact factor 5.11)
  1. Houjin Zhang*, Kang Ning*. The Tara Oceans Project: New opportunities and greater challenges ahead. Genomics Proteomics Bioinformatics, 2015, 13 (5):275-277. doi: 10.1016/j.gpb.2015.08.003. (SCI impact factor 9.5)
  2. Jianhua Fan, Kang Ning, Xiaowei Zeng, Yuanchan Luo, Dongmei Wang, Jianqiang Hu, Jing Li, Hui Xu, Jianke Huang, Minxi Wan, Weiliang Wang, Daojing Zhang, Guomin Shen, Conglin Run, Junjie Liao, Lei Fang, Shi Huang, Xiaoyan Jing, Xiaoquan Su, Anhui Wang, Lili Bai, Zanmin Hu, Jian Xu, Yuanguang Li. Genomic foundation of starch-to-lipid switch in oleaginous Chlorella spp. Plant Physiology, 2015, 169 (4): 2444-2461. doi: 10.1104/pp.15.01174. (SCI impact factor 8.34)
  3. Shiwei Sun, Xuetao Wang, Xing Gao, Lihui Ren, Xiaoquan Su, Dongbo Bu, Kang Ning*. Condensing Raman spectrum for single-cell phenotype analysis. BMC Bioinformatics, 2015, 16 (S18): S15. doi: 10.1186/1471-2105-16-S18-S15. (SCI impact factor 3.169)
  4. Chao Wang, Haicang Zhang, Wei-Mou Zheng, Jianwei Zhu, Bing Wang, Kang Ning, Shiwei Sun, Shuai Cheng Li, Dongbo Bu*. FALCON@home: a high-throughput protein structure prediction server based on remote homologue recognition. Bioinformatics, 2015, 32 (3): 462-464. doi: 10.1093/bioinformatics/btv581.(SCI impact factor 6.937)
  5. Dongdong Meng, Yu Ying, Xiaohua Chen, Ming Lv, Kang Ning, Lushan Wang, Fuli Li*. Distinct roles for carbohydrate-binding modules of glycoside hydrolase 10 (GH10) and GH11 xylanases from caldicellulosiruptor sp. strain F32 in thermostability and catalytic efficiency. Applied and Environmental Microbiology, 2015, 81 (6):2006-2014. doi: 10.1128/AEM.03677-14. (SCI impact factor 4.077)
  6. Xiaojun Wang, Xiaoquan Su, Xinping Cui, Kang Ning*. MetaBoot: a machine learning framework of taxonomical biomarker discovery for different microbial communities based on metagenomic data. PeerJ 2015, 3: e993. doi: 10.7717/peerj.993. (SCI impact factor 2.353)
  7. 宁康, 陈挺. 生物医学大数据的现状与展望. 科学通报, 2015, 60 (5/6): 534-546.
  8. 白虹, 宁康, 王长云. 运用基于高通量测序和大数据挖掘的元基因组学方法分析中药制剂的物种成分. 药学学报, 2015, 3: 272-277.
  9. 陈嘉焕, 孙政, 王晓君, 苏晓泉, 宁康. 元基因组学及其在转化医学中的应用. 遗传, 2015, 7: 645-654.
  1. Qian Zhou, Xiaoquan Su, Kang Ning*. Assessment of quality control approaches for metagenomic data analysis. Scientific Reports, 2014, 4: 6957. doi: 10.1038/srep06957. (SCI impact factor 4.379)
  2. Lihui Ren, Xiaoquan Su, Yun Wang, Jian Xu, Kang Ning*. QSpec: online control and data analysis system for single-cell Raman spectroscopy. PeerJ, 2014, 2: e436. doi: 10.7717/peerj.436. (SCI impact factor 2.353)
  3. Qian Zhou1, Z.Lewis Liu1, Kang Ning1, Anhui Wang, Xiaowei Zeng, Jian Xu. Genomic and transcriptome analyses reveal that MAPK- and phosphatidylinositol-signaling pathways mediate tolerance to 5-hydroxymethyl-2-furaldehyde for industrial yeast Saccharomyces cerevisiae. Scientific Reports, 2014, 4: 6556. doi: 10.1038/srep06556. (SCI impact factor 4.379)
  4. Xiaoquan Su, Jianqiang Hu, Shi Huang, Kang Ning*. Rapid comparison and correlation analysis among massive number of microbial community samples based on MDV data model. Scientific Reports, 2014, 4: 6393. doi: 10.1038/srep06393. (SCI impact factor 4.379)
  5. Peng Yang, Xiaoquan Su, Le Ouyang, Honnian Chua, Xiaoli Li, Kang Ning*. Microbial community pattern detection in human body habitats via ensemble clustering framework. BMC Systems Biology, 2014, 8 (Suppl 4): S7. doi: 10.1186/1752-0509-8-S4-S7. (SCI impact factor 2.048)
  6. Jianqiang Hu, Dongmei Wang, Jing Li, Kang Ning*, Jian Xu*. Genome-wide identification of transcription factors and transcription-factor binding sites in oleaginous microalgae Nannochloropsis. Scientific Reports, 2014, 4: 5454. doi: 10.1038/srep05454. (SCI impact factor 4.379)
  7. Xinwei Cheng, Xiaoquan Su, Xiaohua Chen, Huanxin Zhao, Cuipei Bo, Jian Xu, Hong Bai*, Kang Ning*. Biological ingredient analysis of traditional Chinese medicine preparation based on high-throughput sequencing: the story for Liuwei Dihuang Wan. Scientific Reports, 2014, 4: 5147. doi: 10.1038/srep05147. (SCI impact factor 4.379)
  8. Xiaoquan Su, Weihua Pan, Baoxing Song, Jian Xu, Kang Ning*. Parallel-META 2.0: Enhanced metagenomic data analysis with functional annotation, high performance computing and advanced visualization. PLoS ONE, 2014, 9 (3): e89323. doi: 10.1371/journal.pone.0089323. (SCI impact factor 3.24)
  9. Xiaoquan Su, Xuetao Wang, Gongchao Jing, Kang Ning*. GPU-Meta-Storms: Computing the structure similarities among massive amount of microbial community samples using GPU. Bioinformatics, 2014, 30 (7): 1031-1033. doi: 10.1093/bioinformatics/btt736. (SCI impact factor 6.937)
  10. Fang Yang1, Kang Ning1, Xingzhi Chang, Xiao Yuan, Qichao Tu, Tong Yuan, Ye Deng, Christopher L Hemme, Joy Van Nostrand, Xinping Cui, Zhili He, Zhenggang Chen, Dawei Guo, Jiangbo Yu, Yue Zhang, Jizhong Zhou, Jian Xu. Saliva microbiota carry caries-specific functional gene signatures. PLoS ONE, 2014, 9 (2): e76458. doi: 10.1371/journal.pone.0076458. (SCI impact factor 3.24)
  11. Jing Li1, Danxiang Han1, Dongmei Wang1, Kang Ning1, Jia Jing, Wei Li, Jing Xiaoyan, Huang Shi, Chen Jie, Li Yantao, Qiang Hu, Jian Xu. Choreography of transcriptomes and lipidomes of nannochloropsis reveals the mechanisms of oil synthesis in Microalgae. Plant Cell, 2014, 26 (4): 1645-1665. doi: 10.1105/tpc.113.121418. (SCI impact factor 11.277)
  12. Dongmei Wang1, Kang Ning1, Jing Li1, Jianqiang Hu, Danxiang Han, Hui Wang, Xiaowei Zeng, Xiaoyan Jing, Qian Zhou, Xiaoquan Su, Xingzhi Chang, Anhui Wang, Wei Wang, Jing Jia, Li Wei, Yi Xin, Yinghe Qiao, Ranran Huang, Jie Chen, Bo Han, Russell T. Hill, Yonathan Zohar, Feng Chen, Qiang Hu, Jian Xu. Nannochloropsis genomes reveal evolution of microalgal oleaginous traits. PLoS Genetics, 2014, 10 (1): e1004094. doi: 10.1371/journal.pgen.1004094. (SCI impact factor 5.917)
  13. Qian Zhou, Xiaoquan Su, Gongchao Jing, Kang Ning*. Meta-QC-Chain: Comprehensive and Fast Quality Control Method for Metagenomic Data. Genomics. Proteomics & Bioinformatics, 2014, 12 (1): 52-56. doi: 10.1016/j.gpb.2014.01.002. (SCI impact factor 7.691)
  14. Xinwei Cheng, Xiaohua Chen, Xiaoquan Su, Huanxin Zhao, Maozhen Han, Cunpei Bo, Jian Xu, Hong Bai, Kang Ning*. DNA extraction protocol for biological ingredient analysis of Liuwei Dihuang Wan. Genomics. Proteomics & Bioinformatics, 2014, 12 (3): 137-143. doi: 10.1016/j.gpb.2014.03.002. (SCI impact factor 7.691)
  15. 苏晓泉, 宋宝兴, 王雪涛, 马新乐, 徐健, 宁康. Meta-Mesh——元基因组数据分析系统. 生物工程学报, 2014, 30 (1): 6-17.
  1. Qian Zhou, Xiaoquan Su, Anhui Wang, Jian Xu, Kang Ning*. QC-Chain: Fast and holistic quality control method for next-generation sequencing data. PLoS ONE, 2013, 8 (4): e60234. doi: 10.1371/journal.pone.0060234. (SCI impact factor 3.24)
  2. 程新玮, 赵焕新, 宁康, 白虹. DNA条形码技术在中药质量评价中的研究进展. 食品与药品, 2013, 4: 295-299.
  1. Baoxing Song, Xiaoquan Su, Kang Ning*. MetaSee: An interactive and extendable visualization toolbox for metagenomic sample analysis and comparison. PLoS ONE, 2012, 7 (11): e48998. doi: 10.1371/journal.pone.0048998. (SCI impact factor 3.24)
  2. Yun Wang, Yin Chen, Qian Zhou, Shi Huang, Kang Ning, Jian Xu, Robert M. Kalin, Stephen Rolfe, Wei E. Huang*. A culture-independent approach to unravel uncultured bacteria and functional genes in a complex microbial community. PLoS ONE, 2012, 7 (10): e47530. doi: 10.1371/journal.pone.0047530. (SCI impact factor 3.24)
  3. Xiaoquan Su, Jian Xu, Kang Ning*. Meta-storms: efficient search for similar microbial communities based on a novel indexing scheme and Ssimilarity score for metagenomic data. Bioinformatics, 2012, 28 (19): 2493-2501. doi: 10.1093/bioinformatics/bts470. (SCI impact factor 6.937)
  4. Kang Ning, Damian Fermin, Alexey I. Nesvizhskii. Comparative analysis of different label-free mass spectrometry based protein abundance estimates and their correlation with RNA-Seq gene expression data. Journal of. Proteome Research, 2012, 11 (4): 2261-2271. doi: 10.1021/pr201052x. (SCI impact factor 3.780)
  5. Na You, Gabriel Murillo, Xiaoquan Su, Xiaowei Zheng, Jian Xu, Kang Ning, Shoudong Zhang, Jiankang Zhu, Xinping Cui. SNP calling using genotype model selection on high-throughput sequencing data. Bioinformatics, 2012, 28 (5): 643-650. doi: 10.1093/bioinformatics/bts001. (SCI impact factor 6.937)
  6. Fang Yang, Xiaowei Zeng, Kang Ning, Kuanliang Liu, Chienchi Lo,Wei Wang, Jie Chen, Dongmei Wang, Ranran Huang, Xingzhi Chang, Patrick S Chain, Gary Xie, Junqi Ling, Jian Xu. Saliva microbiomes distinguish caries-active from healthy human populations. ISME Journal, 2012, 6 (1): 1-10. doi: 10.1038/ismej.2011.71. (SCI impact factor 10.302)
  1. Xiaoquan Su, Jian Xu, Kang Ning*. Parallel-META: efficient metagenomic data analysis based on high-performance computation. BMC Systems Biology, 2011, 6 (S1): S16. doi: 10.1186/1752-0509-6-S1-S16. (SCI impact factor 2.048)
  2. 凌均棨, 杨芳, 曾晓维, 宁康, 陈劼, Chien-Chi Lo, Patrick S.Chain, Gary Xie,徐健. 龋活跃人群和健康人群的唾液微生物菌群的宏基因组研究. 中华口腔医学会牙体牙髓病学专业委员会. 全国第八次牙体牙髓病学学术会议论文汇编.中华口腔医学会牙体牙髓病学专业委员会, 2011, 3.
  3. Kang Ning, Damian Fermin, Alexey I. Nesvizhskii*. Computational analysis of unassigned high-quality MS/MS spectra in proteomic data sets. Proteomics, 2010, 10 (14): 2712-2718. doi: 10.1002/pmic.200900473. (SCI impact factor 3.984)
  4. Kang Ning*, Damian Fermin. SAW: A method to identify splicing eents from RNA-Seq data based on splicing fingerprints. PLoS ONE, 2010, 5 (8): e12047. doi: 10.1371/journal.pone.0012047. (SCI impact factor 3.24)
  5. Kang Ning, Hoong Kee Ng, Sriganesh Srihari, Hon Wai Leong, Alexey I Nesvizhskii*. Examination of the relationship between essential genes in PPI network and hub proteins in reverse nearest neighbor Topology. BMC Bioinformatics, 2010, 11: 505. doi: 10.1186/1471-2105-11-505. (SCI impact factor 3.169)
  6. Sriganesh Srihari, Kang Ning*, Hon Wai Leong*. MCL-CAw: A refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure. BMC Bioinformatics, 2010, 11: 504. doi: 10.1186/1471-2105-11-504. (SCI impact factor 3.169)
  7. Kang Ning, Alexey I. Nesvizhskii. The utility of mass spectrometry-based proteomic data for validation of novel alternative splice forms reconstructed from RNA-Seq Data: A preliminary assessment. BMC Bioinformatics, 2010, 11 (S11): S14. doi: 10.1186/1471-2105-11-S11-S14. (SCI impact factor 3.169)
  8. Kang Ning. Deposition and Extension Approach to find longest common subsequence for thousands of long sequences. Computational Biology and Chemistry, 2010, 34 (3): 149-157. doi: 10.1016/j.compbiolchem.2010.05.001. (SCI impact factor 2.877)
  9. Kang Ning, Hon Wai Leong*. The multiple sequence sets: problem and heuristic algorithms. Journal of Combinatorial Optimization. 2010, 22 (4): 778-796. doi: (SCI impact factor 1.195, premium in Combinatorics)
  10. Kang Ning, Hoong Kee Ng, Hon Wai Leong. Analysis of the relationships among longest common subsequences, shortest common supersequences and patterns and its application on pattern discovery in biological sequences. International Journal of Data Mining and Bioinformatics, 2011, 5 (6): 611-625. doi: 10.1504/ijdmb.2011.045413. (SCI impact factor 0.667)
  11. Hoong Kee Ng1, Kang Ning1, Hon Wai Leong. Two-phase filtering strategy for efficient peptide identification from mass spectrometry. J Proteomics Bioinformatics, 2010, 3: 121-129. doi: 10.4172/jpb.1000130.
  12. Hon Nian Chua1, Kang Ning1, Wing-Kin Sung, Hon Wai Leong, Limsoon Wong. Using indirect protein-protein interactions for protein complex prediction. Journal of Bioinformatics and Computational Biology, 2008, 6 (3): 435-466. doi: 10.1142/s0219720008003497. (SCI impact factor 1.122)
  13. Kang Ning1, Nan Ye1, Hon Wai Leong. On preprocessing and antisymmetry in de novo peptide sequencing: improving efficiency and accuracy. Journal of Bioinformatics and Computational Biology, 2008, 6 (3): 467-492. doi: 10.1142/s0219720008003503. (SCI impact factor 1.122)
  14. Ket Fah Chong, Kang Ning, Hon Wai Leong, Pavel Pevzner. Modeling and characterization of multi-charge mass spectra for peptide sequencing. Journal of Bioinformatics and Computational Biology, 2006, 4 (6): 1329-1352. doi: 10.1142/s021972000600248x. (SCI impact factor 1.122)
  15. Kang Ning, Hon Wai Leong. Towards a better solution to the shortest common supersequence problem: The deposition and reduction algorithm. BMC Bioinformatics, 2006, 7 (Suppl 4): S12. doi: 10.1186/1471-2105-7-S4-S12. (SCI impact factor 3.169, 5 citations)
  16. Kang Ning, Kwok Pui Choi, Hon Wai Leong, Louxin Zhang. A post-processing method for optimizing synthesis strategy for oligonucleotide microarrays. Nucleic Acids Research, 2005, 33 (17): e144. doi: 10.1093/nar/gni147.(SCI impact factor 16.971)

 

Book Chapters

 

  1. Kang Ning and Yi Zhan. Synthetic Biology and iGEM: Techniques, Development and Safety Concerns: An Omics Big-data Mining Perspective, ISBN: 978-9819924592, 2023, Springer. https://link.springer.com/book/10.1007/978-981-99-2460-8
  2. Kang Ning*. Methodologies of Multi-Omics Data Integration and Data Mining：Techniques and Applications, ISBN: 978-981-19-8209-5, 2023, Springer. https://link.springer.com/book/10.1007/978-981-19-8210-1
  3. 宁康、李玉雪、计磊、查毓国、杨朋硕.AI赋能的微生物组大数据挖掘：方法与应用, 上海科学技术出版社，2023. http://www.sstp.cn/index.php/hotbook/3380.html
  4. Kang Ning*. Traditional Chinese Medicine and Diseases: An Omics Big-data Mining Perspective, ISBN: 978-981-19-4770-4, 2022, Springer. https://link.springer.com/book/10.1007/978-981-19-4771-1
  5. Kang Ning*. Microbiome and Big-Data Mining. Integrative Bioinformatics, pp 197-222, 2022. Springer (Book Chapter). https://link.springer.com/chapter/10.1007/978-981-16-6795-4_10
  6. 宁康、白虹、计磊、钟朝芳.生物统计学：生物大数据的概率统计模型与机器学习方法, 华中科技大学出版社，2022. http://product.dangdang.com/29608303.html
  7. 宁康、白虹、钟朝芳、计磊.生物统计学习题与详解, 华中科技大学出版社，2022. http://product.dangdang.com/11382622270.html
  8. 丁明跃、刘笔锋、赵元弟、宁康、刘欣、薛宇、肖鹏、尉迟明、马军、陈威等.生物医学工程与信息技术概论, 华中科技大学出版社，2021. http://product.dangdang.com/694520382.html
  9. Maozhen Han, Pengshuo Yang, Hao Zhou, Hongjun Li and Kang Ning*. Metagenomics and Single-Cell Omics Data Analysis for Human Microbiome Research. Translational Biomedical Informatics: A Precision Medicine Perspective, 117-137, 2016. Springer (Book Chapter). https://link.springer.com/chapter/10.1007/978-981-10-1503-8_6
  10. Kang Ning and Jian Xu. Bioinformatics in microbial metagenomics: Status and prospects. Industrial Biotechnology ，2011. Science Press (China).

 

Educational papers

 

  1. 宁康*, 李玉雪, 王波, 白虹. 人工智能时代，生物信息学课程体系如何变革？中国计算机学会通讯, 2024, 已接收.
  2. 白虹, 杨敏, 艾阳, 刘亚丰, 宁康*. 微生物学实验模块化教学体系探索与实践.实验室研究与探索, 2024, 已接收.
  3. 白虹, 程铭悦, 王莎莎, 白云, 刘亚丰, 宁康*. 融合生物信息技术的微生物学实验教学改革探索.高校生物学教学研究: 电子版, 2023, 13 (1): 48-51.
  4. 白虹, 王莎莎, 宁康 , 刘亚丰. 纳米药物制剂实验课程教学实践探索.实验室科学, 2021, 4: 137-140.

 

Peer reviewed conference papers

 

  1. Xiaoquan Su, Gongchao Jing, Shi Huang, Jian Xu and Kang Ning*. Application of Meta-Mesh on the analysis of microbial communities from human associated-habitats. IEEE ISB, 2014.
  2. Xiaoquan Su, Xuetao Wang, Jian Xu and Kang Ning*. GPU-Meta-Storms: Computing the similarities among massive microbial communities using GPU. IEEE Systems Biology doi:10.1109/ISB, 2013.
  3. Fang, Wei, Xingzhi Chang, Xiaoquan Su, Jian Xu, Zhang Deli and Kang Ning*. A machine learning framework of functional biomarker discovery for different microbial communities based on metagenomic data. Systems Biology (ISB), 2012 IEEE 6th International Conference on Systems Biology. IEEE, 2012, 106-112.
  4. Xiaoquan Su, Jian Xu and Kang Ning*. An Open-source collaboration environment for metagenomics research. 2011 IEEE 7th International Conference on e-Science. IEEE , 2011, 7-14.
  5. Xiaoquan Su, Jian Xu and Kang Ning*. Parallel-META: A high-performance computational pipeline for metagenomic data analysis. 2011 IEEE 5th International Conference on Systems Biology. 2011, 173-178.
  6. Kang Ning and Alexey I. Nesvizhskii*. The utility of mass spectrometry-based proteomic data for validation of novel alternative splice forms reconstructed from RNA-Seq data: A preliminary assessment. GIW 2010, 2010.
  7. Sriganesh Srihari, Kang Ning1 and Hon Wai Leong. Refining markov clustering for protein complex prediction by core-attachment. GIW 2009, 2009. Genome Informatics Series Vol. 23, page 159-168. (1Corresponding author, 1 citation)
  8. Sriganesh Srihari, Hoong Kee Ng, Kang Ning and Hon Wai Leong. Detecting hubs and quasi cliques in scale-free networks. ICPR 2008, 2008. IEEE Catalog Number: CFP08182; ISBN: 978-1-4244-2175-6; ISSN: 1051-4651. (EI indexed)
  9. Kang Ning, Hoong Kee Ng and Hon Wai Leong. An accurate and efficient algorithm for peptide and PTM identification by tandem mass spectrometry. GIW 2007, 2007. Genome Informatics Series, 19: 119-130.
  10. Kang Ning and Hon Wai Leong. Algorithm for peptide sequencing by tandem mass spectrometry based on better preprocess and anti-symmetric computational model. CSB 2007, 2007. Computational Systems Bioinformatics: CSB 2007 Conference Proceedings, 6: 19-30. (2 citations)
  11. Hon Nian Chua1, Kang Ning1, Wing-Kin Sung, Hon Wai Leong and Limsoon Wong. A novel algorithm for protein complex prediction based on PPI networks. CSB 2007, 2007. Computational Systems Bioinformatics: CSB 2007 Conference Proceedings, page 97-110. (1Co-first authors)
  12. Hoong Kee Ng, Kang Ning and Hon Wai Leong. A new approach for similarity queries of biological sequences in databases. PAKDD 2007, 2007. Lecture Notes in Computer Science, Vol. 4426, page 728-736. (EI indexed, 1 citation)
  13. Kang Ning, Ket Fah Chong and Hon Wai Leong. De Novo peptide sequencing for mass spectra based on multi-charge strong Tags. APBC 2007, 2007. Series on Advances in Bioinformatics and Computational Biology, Vol. 5, page 287-296. (3 citations)
  14. Kang Ning and Hon Wai Leong. The distribution and deposition algorithm for the multiple oligo nucleotide arrays. GIW 2006, 2006. Genome Informatics. 17 (2): 89-99. (1 citation)
  15. Kang Ning, Hoong Kee Ng and Hon Wai Leong. PepSOM: An algorithm for peptide identification by tandem mass spectrometry based on SOM. GIW 2006, 2006. Genome Informatics 17 (2): 194-205. (3 citations)
  16. Kang Ning, Hoong Kee Ng and Hon Wai Leong. Finding patterns in biological sequences by longest common subsequences and shortest common supersequences. BIBE 2006, 2006. Sixth IEEE International Symposium on BioInformatics and BioEngineering (BIBE 2006), ISBN 0-7695-2727-2, page 53-60. (EI indexed, 2 citations)
  17. Kang Ning and Hon Wai Leong. Towards a better solution to the shortest common supersequence problem: A post processing approach. Proceeding of the First International Multi-symposiums on Computer and Computational Sciences (IMSCCS|06), IEEE Computer Society Press, ISBN 0-7695-2581-4, Vol. 1, page 84-90. (EI indexed, 4 citations)
  18. Kang Ning and Hon Nian Chua. Automated identification of protein classification and detection of annotation errors in protein databases using statistical approaches. KDLL 2006, 2006. Lecture Notes in Computer Science, Vol. 3886, page 123-138.
  19. Kang Ning, Ket Fah Chong and Hon Wai Leong. A database search algorithm for identification of peptides with multiple charges using tandem mass spectrometry. BioDM 2006, 2006. Lecture Notes in Computer Science, Vol. 3916, page 2-13. (EI indexed, 3 citations)
  20. Ket Fah Chong, Kang Ning, Hon Wai Leong and Pavel Pevzner. Characterization of multi-charge mass spectra for peptide sequencing. APBC 2006, 2006. Proceedings of 4th Asia-Pacific Bioinformatics Conference, page 109-119. (2 citations)

 

Patent Of Invention

 

  1. 樊昌鑫，裘豪，王博涵，霍修楠，石家诚，梁元浩，张东方，占艺，谢尚县，闫云君，宁康。基因重组质粒、基因重组毕赤酵母及秸秆纤维脱胶应用, 授权公开号：CN114262716B.
  2. 周茜，宁康，朱雪，陈松林。一种筛选抗哈维氏弧菌病半滑舌鳎的标记组合和筛选半滑舌鳎抗病个体的方法, 授权公开号：CN114990243B.
  3. 宁康，秦季玥，朱雪，谭重阳。一种基于SNP鉴定个体肠道菌群类型的方法, 授权公开号：CN110827917B.
  4. 宁康，白虹，杨朋硕，卢璟详，邹欣桐，李洪军。一种基于matK基因的未知植物物种识别数据库的构建方法与数据库, 授权公开号：CN111681704B.
  5. 宁康，白虹，高溪，陈超云，钟超芳，程铭悦，谭重阳。一种药用植物共生微生物鉴定方法及其应用, 专利申请号：CN201911075058.1.
  6. 宁康，秦季玥，朱雪，谭重阳。一种基于SNP鉴定个体肠道菌群类型的方法, 专利申请号：CN201911075063.2.
  7. 宁康，白虹，杨朋硕，卢璟详，邹欣桐，李洪军。一种基于matK基因的未知植物物种识别数据库的构建方法与数据库, 专利申请号：CN202010319607.1.
  8. 宁康，李冠兰，刘剑，李锐豪，陈超云，朱雪。一种基于DNA编码技术的图片存储方法, 专利申请号：CN202010319479.0.
  9. 宁康，韩毛振，杨朋硕，钟超芳。一种人类肠道病毒网络的构建与分析方法, 专利申请号：CN202010319541.6.
  10. 宁康，奚望，高岩，成章昱，陈超云，韩毛振。一种高通量测序的微生物数据处理方法, 专利申请号：CN201811130694.5, 授权公开号：CN109273053B.
  11. 宁康，韩毛振，杨朋硕，钟朝芳。一种肠道病毒组的高通量检测方法及应用.专利申请号：CN201811130676.7, 授权公开号：CN 109215736B.
  12. 宁康、杨朋硕、余少俊、韩毛振.微生物群中物种的关联性挖掘方法, CN201910342119.X.
  13. 宁康、白虹、姚奇、朱雪.中药复方制剂的生物成分分析方法, CN201910334789.7.
  14. 宁康、白虹、李洪军.基于ITS2鉴定植物物种的方法及设备, CN201910335741.8.
  15. 宁康、陈超云、何睿乔、成章昱、韩毛振、查毓国、杨朋硕、姚奇、周豪、钟朝芳. 确定环境因素与菌群结构和功能相关性的方法及设备,CN201910334811.8.
  16. 宁康、韩毛振、杨朋硕、钟朝芳.一种肠道病毒组的高通量检测方法及应用, CN201811130676.7.
  17. 宁康、奚望、高岩、成章昱、陈超云、韩毛振.一种高通量测序的微生物数据处理方法, CN201811130694.5 .
  18. 宁康、李锐豪、陈超云、朱雪. 酵母DNA的保真存储方法, CN201811249175.0 .
  19. 宁康、李希、朱雪、王雯婕. 一种实验室的微生物污染鉴别方法, CN201811130690.7.
  20. 宁康、谭重阳、杨鹏硕、韩毛振. 确定肠道细菌亚种的方法及设备, CN201811249167.6.
  21. 宁康、曹乐、周纯羽、朱雪. 海洋珊瑚菌群结构分析、基因挖掘方法及设备, CN201811252030.6.
  22. 宁康、钱晓波、陈超云、杨朋硕. 一种高通量测序的RNA数据处理方法, CN201811130687.5.
  23. 宁康、白虹、李洪军、张润之、朱雪. 中药制剂非处方物种化学成分致病的分析方法及设备, CN201811249212.8.
  24. 宁康、白虹、张润之、余少俊. 中药及中药制剂的网络药理分析方法以及系统, CN201710820809.2.
  25. 周茜、宁康、苏晓泉、徐健. 基于多核CPU硬件的高通量转录组测序数据质量控制方法, CN201410205571.9, 授权公开号：CN105095686B.
  26. 宁康、王静. 一种中药制剂非处方物种化学成分的网络药理分析方法, CN201510026994.9
  27. 任立辉、宁康、苏晓泉、徐健、肖航. 活体单细胞拉曼分析平台数字控制系统和方法, CN201410579147.0, 授权公开号：CN105588827B.
  28. 宁康、胡建强、苏晓泉、徐健. 一种利用DNA进行信息存储的编码方法和解码方法, CN201410163020.0.
  29. 任立辉、宁康、籍月彤、王允、徐健、黄巍. 单细胞表现型数据库系统和搜索引擎, CN201310105207.0, 授权公开号：CN104077307B.
  30. 宁康、白虹、苏晓泉、程新玮、赵焕新、徐健、陈晓华. 一种基于高通量测序技术的中药制剂生物成分分析方法, CN201310612193.1.
  31. 任立辉、宁康、马波、徐健、黄巍. 活体单细胞分选电子控制系统, CN201210567603.0, 授权公开号：CN103897985B.
  32. 宁康、苏晓泉、徐健. 基于GPGPU和多核CPU硬件的高性能元基因组数据分析系统, CN201210055384.8.
  33. 周茜、宁康、苏晓泉、徐健. 基于多核CPU和GPGPU硬件的高通量测序数据质量控制系统, CN201210478392.3.

 

Software Copyright

 

  1. 宁康. 可用于人体微生物的超快速和高度精确的微生物群落结构搜索工具软件[简称：Meta-Prism]V1.0, 2021SR0794756.
  2. 苏晓泉、周茜、宁康、徐健. 并行化高通量测序数据质量控制软件 1.0, 2013SR080803.
  3. 任立辉、宁康、苏晓泉、徐健. 单细胞拉曼光谱模拟系统软件, 2013SR079944.
  4. 任立辉、宁康、苏晓泉、徐健. 单细胞拉曼光谱系统控制软件. 2013SR015642.
  5. 苏晓泉、宁康、徐健. 元基因组数据库索引与搜索系统, 2013SR000258.
  6. 宁康、苏晓泉、徐健. 基于GPGPU 和多核心CPU 硬件的元基因组数据分析软件 2.0, 2012SR055051.

 

 

 

 

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