Journal proceedings
1.Zhong, L.,Yang, F.(通讯), Sun, S. et al. Predicting lung cancer survival prognosis based on the conditional survival bayesian network. BMC Medical Research Methodology 24, 16 (2024. 01. 24). Q1, IF=4
2.Zhang S, ..,Yang F*(通讯), Wang L, Si S, Zhang J, Xue F. Personalized prediction for multiple chronic diseases by developing the multi-task Cox learning model. PLoS Computational Biology. 2023 Sep 21;19(9):e1011396. doi: 10.1371/journal.pcbi.1011396 (IF=4.3, CCF-B,中科院一区)
3.F. Yang, F. Xue, Y. Zhang and G. Karypis, Kernelized Multitask Learning Method for Personalized Signaling Adverse Drug Reactions,IEEE Transactions on Knowledge and Data Engineering, vol. 35, no. 2, pp. 1681-1694, 1 Feb. 2023, doi: 10.1109/TKDE.2021.3108819., (IF=9.235 CCF-A, JCR Q1,中科院一区)
4.Wang, L., Zhang, J., Wang, J.Yang, F.*(通讯) et al. Wang L, Zhang J, Wang J, Xue H, Deng L, Che F, Heng X, Zheng X, Lu Z, Yang L, Tan Q.Postoperative prognostic nomogram for adult grade II/III astrocytoma in the Chinese Han population. Health Information Science and Systems. 2023 May 4;11(1):23.https://doi.org/10.1007/s13755-023-00223-0(IF=6, JCR Q2)
5.Yao, Ruiyuan,Fan Yang*(通讯), Jianing Liu, Qiang Jiao, Hong Yu, Xiushan Nie, Hongkai Li, Xin Wang, and Fuzhong Xue. Therapeutic drug combinations against COVID-19 obtained by employing a collaborative filtering method. Heliyon. 2023 Mar 1;9(3).(IF=3.776, JCR Q2)
6.Wu, P., Zhang, Q., Wang, G. et al. Dynamic feature selection combining standard deviation and interaction information. Int. J. Mach. Learn. & Cyber. 14, 1407–1426 (2023). https://doi.org/10.1007/s13042-022-01706-4 (JCR Q1,中科院三区,IF=4.377)
7.Zhang S, Zhao S, Qi Y, Li B, Wang H, Pan Z, Xue H, Jin C, Qiu W, Chen Z, Guo Q,Fan Y, Xu J, Gao Z, Wang S, Guo X, Deng L, Ni S, Xue F, Wang J, Zhao R, Li G. SPI1-induced downregulation of FTO promotes GBM progression by regulating pri-miR-10a processing in an m6A-dependent manner.Mol Ther Nucleic Acids.2022 Jan 1;27:699-717. doi: 10.1016/j.omtn.2021.12.035. (IF=10.183,JCR Q1,中科院一区)
8.Li J, Lu A, Si S, Zhang K, Tang F,Yang F*(通讯), Xue F.Exposure to various ambient air pollutants increases the risk of venous thromboembolism: A cohort study in UK Biobank.Science of The Total Environment.2022 Nov 1;845:157-165. doi: 10.1016/j.scitotenv.2022.157165. (IF=10.753,JCR Q1,中科院一区)
9.Yang F, Zhang S, Pan W, Yao R, Zhang W, Zhang Y, Wang G, Zhang Q, Cheng Y, Dong J, Ruan C, Cui L, Wu H, Xue F. Signaling repurposable drug combinations against COVID-19 by developing the heterogeneous deep herb-graph method.Briefings in Bioinformatics2022 Sep 20;23(5):bbac124. doi: 10.1093/bib/bbac124. (IF=13.994, CCF-B, JCR Q1,中科院一区,WOS:000791464100001)
10.Wu H, Zhang P, Ai Z, Wei L, Zhang H,Yang F(通讯作者), Cui L. StackTADB: a stacking-based ensemble learning model for predicting the boundaries of topologically associating domains (TADs)accurately in fruit flies.Briefings in Bioinformatics. 2022 Mar 10;23(2):bbac023. doi: 10.1093/bib/bbac023. (IF=13.994, CCF-B, JCR Q1,中科院一区, WOS:000759008700001, PubMed ID35181793)
11.Yang, Fan, Qi Zhang, Zhongshang Yuan, Saisai Teng, Lizhen Cui, Leyi Wei, and Fuzhong Xue. "Signaling Potential Therapeutic Herbal Medicine Prescription for Treating COVID-19 by Collaborative Filtering."Frontiers in Pharmacology: 12, p.759479., 2021 Dec. 24,IF=5.988 JCR Q1中科院二区,(WOS:000743029200001)
12.Fan Yang,Qi Zhang, Xiaokang Ji, Yanchun Zhang, Wentao Li, Shaoliang Peng∗, Fuzhong Xue∗Machine Learning Application in Drug Repurposing, Interdisciplinary Sciences-Computational Life Sciences, 2022 Jan 23:1-7, (IF=4.8, JCR Q2,中科院二区, WOS:000745560100002)
13.Liu, X., Yang, J., Li, H., Wang, Q., Yu, Y., Sun, X., Si, S., Hou, L., Liu, L.,Yang, F.,Yan, R., Yu, Y., Fu, Z., Lu, Z., Li, D., Xue, H., Guo, X., Xue, F., & Ji, X. (2022). Quantifying substantial carcinogenesis of genetic and environmental factors from measurement error in the number of stem cell divisions. BMC Cancer, 22(1). https://doi.org/10.1186/s12885-022-10219-w
14.Sun, Zhenchao, Hongzhi Yin, Hongxu Chen, Tong Chen, LiZhen Cui, andFan Yang. "Disease Prediction via Graph Neural Networks."IEEE Journal of Biomedical and Health Informatics, 2020 Jun 22;25(3):818-26.,(IF=7.7, CCF-C类, JCR Q1,中科院一区, WOS:000626521100021)
15.Liu, Lu, Lei Hou, Yuanyuan Yu, Xinhui Liu, Xiaoru Sun,Fan Yang, Qing Wang et al. "A novel method for controlling unobserved confounding using double confounders."BMC medical research methodology20, no. 1 (2020): 1-12., (WOS:000555106900001) (IF=4.612,中科院二区)
16.Yu Y, Li H, Sun X, Liu X, Yang F, Hou L, Liu L, Yan R, Yu Y, Jing M, Xue H, Cao W, Wang Q, Zhong H, Xue F.Identification and Estimation of Causal Effects Using a Negative-Control Exposure in Time-Series Studies With Applications to Environmental Epidemiology. Am J Epidemiol. 2021 Feb 1;190(3):468-476. doi: 10.1093/aje/kwaa172. PMID: 32830845.. (WOS:000636962000015) IF=5.363
17.Yang F, Zhang S, Wang Q, Zhang Q, Han J, Wang L, Wu X, Xue F.Analysis of the global situation of COVID-19 research based on bibliometrics. Health information science and systems. 2020 Dec;8, pp.1-10.IF=6, JCR-Q2 (WOS:000574247800001)
18.2018, WANG Xingrun, NIE Xiushan,YANG Fan, et al. Video summarization based on learning to rank. CAAI Transactions on Intelligent Systems, 13(6), 921-927. DOI: 10.11992/tis.201806013
19.2015,Fan Yang, Xiaohui Yu, and Yang Liu. SCSVM: Identifying Rumor Microblogs using Semi-Supervised Cascade Support Vector Machine, Journal of Computational Information Systems, EI
Conference proceedings
1.Hou, Meihao,Fan Yang, Lizhen Cui, and Wei Guo. "Predicting Adverse Drug-Drug Interactions via Semi-supervised Variational Autoencoders." InAsia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data, pp. 132-140. Springer, Cham, 2020., (CCF-C, NSPEC:20105894)
2.Yang, Fan, Xiaohui Yu, and George Karypis. "Signaling adverse drug reactions with novel feature-based similarity model." In2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 593-596. IEEE, 2014., CCF-B类
3.Fan Yang, Xiaohui Yu, Credibility Measuring on Massive Microblog based on Semi-Supervised Cascade SVM, China Computer Federation Artificial Intelligence (CCFAI’ 13). July 31 - August 2, 2013. Beijing, China
4.Yang, Fan, Yang Liu, Xiaohui Yu, and Min Yang. "Automatic detection of rumor on sina weibo" In Proceedings of the ACM SIGKDD workshop on mining data semantics, pp. 1-7. 2012.
专利
授权
1.国家发明专利,基于新冠蛋白质异构网络聚类的中药处方推荐方法及系统,专利号ZL202110038417.7,授权号:CN1128636364B,申请时间:2021.01.12,授权时间:2022.09.20
2.国家发明专利,一种个性化药物不良反应预测方法、系统、设备及介质,专利号:ZL202010745145.X,授权号:CN111863281B,授权时间:2021.08.06
3.国家发明专利,基于协同过滤的新型冠状病毒中药组方推荐方法及系统,专利号:ZL202110037705.0,授权号:CN112667922B,授权时间:2022.06.28
4.国家发明专利,PDIA3P1作为胶质瘤预后标志物的应用,专利号:ZL201911157613.5,授权号:CN110760587B,授权时间:2020.11.24 (8/10)
5.国家发明专利,一种传染病的流行趋势预判方法及系统,专利号:ZL202110260151.0,授权号:CN11299233B,申请日期:2021.03.10,授权日期:2022.09.16,(7/7)
6.国家发明专利,一种消化道疾病数据加密获取方法及风险预测系统,专利号:ZL202010688366.8,授权时间:2023-03-28
受理
1.国家发明专利,一种基于多任务Cox学习模型的多慢性病预测系统,申请号:202210750321.8,申请日期:2022.06.29
2.国家发明专利,一种肺癌预后预测模型构建方法及肺癌预后预测系统,申请号:202210750259.2,申请日期:2022年06月29日
3.国家发明专利,基于医学知识库的疾病数据分析方法和肺癌风险预测系统2020106874279
4.国家发明专利,逐步筛选的泌尿系统重疾指标确定方法及风险预测系统,2020106883598
5.国家发明专利,一种心脏疾病数据队列生成方法和风险预测系统,2020106883051
6.国家发明专利,一种疾病数据调度管理方法和骨癌风险预测系统,2020106871158
7.国家发明专利,一种疾病数据结构化方法及甲状腺癌风险预测系统,2020106873007
8.国家发明专利,一种骨髓血液疾病危险因素贡献率计算及风险预测系统,2020106873295
9.国家发明专利,一种妇科肿瘤疾病风险预测可视化系统,2020106873153
10.国家发明专利,全基因组致病SNP精细定位的因果关联分析方法,2021111494861
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