陈伯林
发布日期：2024-04-06 浏览次数：次
教育教学 Education and teaching 招生信息 教育教学 西北工业大学计算机学院，副教授，博士生导师。研究方向包括数据挖掘、机器学习、生物信息学、领域大数据分析等，具体的研究问题包括人类复杂疾病动态演化机制及发病机理研究、癌症与帕金森疾病阶段相关生物标志物识别、动态复杂网络的构建与分析、复杂场景下的数据挖掘问题研究等。主持国家自然科学基金项目2项，国家重点研发子课题1项，陕西省自然科学基金项目1项，发表学术论文50余篇。Positions for master students in Computational Biology are now available. I am interested in recruiting high-caliber undergraduate students who have expertise in the areas of computer science, or applied mathematics. The students who are self-motivated and have publications in relevant scientific journals are encourages to apply. Email: blchen[AT]nwpu.edu.cn 本科课程（1）：课程编号：U10M11127课程名称：数据科学的数学方法 (Mathematical methods in data science)开课信息：面向大数据专业大二第二学期学生、48课时、3学分课程获得的资助信息：(a) 2020年度校级教育教学改革研究项目(b) 2020年度新工科建设典型案例 本科课程（2）：课程编号：U10M11125课程名称：生物大数据分析 (Biological big data analysis)开课信息：面向大数据专业大三第一学期学生、40课时、2学分 硕士课程（1）：课程编号：M10M22023 （中文授课）课程名称：计算生物学 (Computational Biology)开课信息：面向硕士一年级学生、40课时、2学分 硕士课程（2）：课程编号：M10M22031 （全英文授课）课程名称：生物信息学导论 (Introduction to Bioinformatics)开课信息：面向硕士留学生、40课时、2学分
教育教学
科学研究 Scientific Research 研究案例1：人类复杂疾病动态演化机制及发病机理研究利用大规模生物网络分析的方法，识别哪些基因跟复杂疾病有关系，并将该问题的研究粒度从泛癌、到特定癌症、再到特定癌症发病阶段不断细化，通过大数据分析的方法研究疾病发病机理，为实验分析提供理论依据。研究案例2：帕金森疾病的早诊标记物设计与分析与唐都医院合作，基于miRNA表达数据分析，对帕金森疾病各个阶段的演变机理进行分析，从共性和个性两个维度分别刻画各个阶段的生物标记物，帮助设计PD的早诊的诊断试剂盒。研究案例3：新冠相关药物设计将新冠相关药物设计转化为高维空间中的非等维数据聚类与类中心合成的问题，借助现有的跟SARS，新冠或冠状病毒相关的抑制剂的特征，组合出新的潜在药物，并对各个结果的成药性进行评价，为药物设计提供依据研究案例4：基因表达数据的个性化分析与应用与上海东方医院合作，开发了针对小样本的基因表达数据的分析工具包，将差异表达基因识别与相关功能分析作为一个任务同时分析，解决了现有分析工具中的多个痛点问题。研究案例5：XXXXX异常信号预警分析与某研究所合作，针对XXXXX的数据，对XXXX进行综合分析，为异常信号检测提供依据。研究案例6：数据驱动的材料基因学算法研究与材料学院合作，成立材料基因学交叉学科，利用数据驱动的方式，研究复合材料的成分、结构、工艺与性能之间的关系模型，并构建数据存储、数据检索与数据挖掘于一体的综合分析平台。研究案例7：时序数据的异常检测与国家电网相关公司合作，面向高压输送站点的时序传感器数据进行分析，设计系统异常的检测算法与分析工具，为提升输送站点的远程管理提供理论依据和技术支撑。研究案例8：基于CT图像的Nuss手术最佳矫形板设计与西安市儿童医院合作，开发面向Nuss手术的最佳矫形板设计方案，通过对术前的CT图片进行预处理、三维重建以及有限元分析，评估不同矫形板的预后效果，给出最佳的手术方案推荐。拓展的研究方向：大数据分析与应用具有大数据存储、大数据管理与大数据分析的全链条分析经历，研制了我国第一个工程数据库管理系统。同时具有数学专业和计算机专业的教育与工作背景，以及医学院的访问研究经历，能够同时理解数据分析人员与医疗人员的思维模式。Research areasResearch areas include but not limit to computational and systems biology, genomic and proteomic data analysis, disease gene identification, protein complex identification, dynamic network analysis, gene methylation data analysis etc. Grant Information[4] The mechanism of carcinogenesis and the identification of driving factors based on dynamic network analyses supported by the National Natural Science Foundation of China (NSFC), No. 61972320, CNY 620K, 2020-2023[3] Feature self-learning method for complex disease gene identification supported by the National Natural Science Foundation of China (NSFC), No. 61602386, CNY 190K, 2017-2019[2] Identifying disease related genes by using multiple data integration and logistic regression supported by the Northwestern Polytechnical University (NPU) under the name of the fundamental research funds for the central Universities, No. 3102015JSJ0011, CNY 100K, 2015-2016[1] Identifying disease related genes by using multiple data integration and logistic regression supported by the Northwestern Polytechnical University (NPU) under the name the startup fund for young professionals, No. 3102015QD029, CNY 80K, 2015-2016
荣誉获奖
学术成果 Academic Achievements Refereed Journal Papers[21] B Chen, T Wang, JL Zhang, SL Zhang, XQ Shang, Identification of Colon Cancer-Related RNAs Based on Heterogeneous Networks and Random Walk, Biology, 2022, 11, 1003 (Impact factor: 5.168).[20] B Chen, YR Han, XQ Shang. A novel COVID-19 related drug discovery approach based on non-equidimensional data clustering. Frontiers in Pharmacology 2022, 13, 813391 (Impact factor: 5.810)[19] B Chen, YR Han, XQ Shang. Identifying Disease Related Genes by Network Representation and Convolutional Neural Network. Frontiers in Cell and Developmental Biology 2021, 9, 629876 (Impact factor: 5.186)[18] B Chen, L Gao, XQ Shang*. A two-way rectification method for identifying differentially expressed genes by maximizing the co-function relationship. BMC Genomics 2021, 22(S1), 251-264. (Impact factor: 3.594)[17] B Chen, MT Yang, L Gao, T Jiang, XQ Shang. A functional network construction method to interpret the pathological process of colorectal cancer. International Journal of Data Mining and Bioinformatics 2020, 23(3), 251-264 (Impact factor: 0.772)[16] C Aouiche(#), B Chen(#,*), XQ Shang. Predicting Stage-Specific Recurrent Aberrations From Somatic Copy Number Dataset. Frontiers in Genetics 2020, 11, 160 (Impact factor: 3.258)[15] C Aouiche(#), B Chen(#,*), XQ Shang. Predicting stage-stepcific cancer related genes and their dynamic modules by integrating multiple datasets. BMC Bioinformatics 2019, 20, 194 (Impact factor: 2.213) [14] C Aouiche(#), XQ Shang*, B Chen(#,*). Copy number variation related disease genes. Quantitative Biology 2018, 6(2): 99-112. [13] B Chen, XQ Shang, M Li, JX Wang, FX Wu*. Identifying individual-cancer-related genes by rebalancing the training samples. IEEE Transactions on Nanobioscience 2016, 15(4), 309-315. (Impact factor: 1.969) [12] XQ Shang, Y Wang, B Chen*. Identifying essential proteins based on dynamic PPI networks and RNA-Seq datasets. SCIENCE CHINA Information Science 2016, 070106. (Impact factor: 0.885) [11] T Jiang, ZH Li, XQ Shang, B Chen, WB Li, ZL Yin. Constrained query of order-preserving submatrix in gene expression data.Frontiers of Computer Science in China. 2016, 10(6), 1052-1066.[10] B Chen, M Li, JX Wang, XQ Shang and FX Wu. A fast and high performance multiple data integration algorithm for identifying human disease genes. BMC Medical Genomics 2015, 8(Suppl 3): S2. (Impact factor: 2.873) [9] B Chen, M Li, JX Wang, FX Wu. Disease gene identification by using graph kernels and Markov random fields. SCIENCE CHINA Life Sciences 2014, 57(11), 1054-1063. (Impact factor: 1.512)[8] W Fan, B Chen, G Selvaraj and FX Wu. Discovering biological patterns from short time-series gene expression profiles with integrating PPI data. Neurocomputing 2014, 145, 3-13. (Impact factor: 2.005, EI Compendex)[7] B Chen, JX Wang, M Li and FX Wu. Identifying disease genes by integrating multiple data sources. BMC Medical Genomics 2014, 7(Suppl 2): S2. (Impact factor: 3.914)[6] J Sun, B Chen and FX Wu. An improved peptide-spectral matching algorithm through distributed search over multiple cores and multiple CPUs. Proteome Science 2014 12:18. (Impact factor: 1.878, equally contribution as the first author)[5] B Chen, W Fan, J Liu and FX Wu. Identifying protein complexes and functional modules – from static PPI networks to dynamic PPI networks. Briefings in Bioinformatics 2014, 15(2), 177-194. (Impact factor: 5.919) [4] B Chen and FX Wu. Identifying protein complexes based on multiple topological structures in PPI networks. IEEE Transactions on Nanobioscience 2013,12(3), 165-172. (Impact factor: 1.768, EI Compendex)[3] J Shi, B Chen and FX Wu. Unifying protein inference and peptide identification with feedback to updated consistency between peptides. Proteomics 2013, 13(2), 237-247. (Impact factor: 3.973)[2] B Chen, J Shi, S Zhang and FX Wu. Identifying protein complexes in protein-protein interaction networks by using clique seeds and graph entropy. Proteomics 2013, 13(2), 269-277. (Impact factor: 3.973)[1] Z Yuan, J Shi, W Lin, B Chen and FX Wu. Features-based deisotoping method for tandem mass spectra. Advances in Bioinformatics 2011, Article ID 210805, 12 pages. P.S. All the impact factors are based on the state of the publication year. Refereed Conference Papers:[16] B Chen, T Wang, and X Shang*. Identification and Analysis of Genes Involved in Stages of Colon Cancer. Intelligent Computing Theories and Application (ICIC 2019), International Conference on Intelligent Computing,accepted. (EI Compendex)[15] B Chen, L Gao, and X Shang*. A machine learning based method to identify differentially expressed genes. Intelligent Computing Theories and Application (ICIC 2020), International Conference on Intelligent Computing,accepted. (EI Compendex)[14] B Chen, L Gao, and X Shang*. Identifying functional evolution processes according to the pathological stages of colorectal cancer. Bioinformatics and Biomedicine (BIBM), 2019 IEEE International Conference on, 193-196. (EI Compendex)[13] B Chen, L Gao, and X Shang*. Identifying Differentially Expressed Genes Based on Differentially Expressed Edges. Intelligent Computing Theories and Application (ICIC 2019), International Conference on Intelligent Computing,105-115. (EI Compendex)[12] B Chen(#,*), C Aouiche(#), and X Shang. Integrating multiple datasets to discover stage-specific cancer related genes and stage-specific pathways. Bioinformatics and Biomedical Engineering (IWBBIO 2019), International Conference on, 240-250. (EI Compendex)[11] P Luo, L Tian, B Chen, Q Xiao, and FX Wu*. Predicting disease genes from clinical single sample-based PPI networks. Bioinformatics and Biomedical Engineering (IWBBIO 2018), International Conference on, 247-258. (EI Compendex)[10] P Luo, L Tian, B Chen, Q Xiao, and FX Wu*. Predicting gene-disease associations with manifold learning. Bioinformatics Research and Applications (ISBRA 2018), International Symposium on, 265-271. (EI Compendex)[9] B Chen, Y Jin, and X Shang*. Net2Image: A network representation method for identifying cancer-related genes. Bioinformatics Research and Applications (ISBRA 2017), International Symposium on, 337-343. (EI Compendex)[8] B Chen, XQ Shang, M Li, J Wang and FX Wu. A two-step logistic regression based algorithm for identifying individual-cancer-related genes. Bioinformatics and Biomedicine (BIBM), 2015 IEEE International Conference on, 195-200. (EI Compendex)[7] B Chen, M Li, J Wang and FX Wu. A logistic regression based algorithm for identifying human disease genes.Bioinformatics and Biomedicine (BIBM), 2014 IEEE International Conference on, 197-200. (EI Compendex)[6] B Chen, J Wang and FX Wu. Prioritizing human disease genes by multiple data integration. Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on, 621. (EI Compendex)[5] B Chen, J Shi and FX Wu. Not all protein complexes exhibit dense structures in S. cerevisiae PPI network. Bioinformatics and Biomedicine (BIBM), 2012 IEEE International Conference on, 470-473. (EI Compendex)[4] B Chen, Y Yan, J Shi, S Zhang and FX Wu. An improved graph entropy-based method for identifying protein complexes. Bioinformatics and Biomedicine (BIBM), 2011 IEEE International Conference on, 123-126. (EI Compendex)[3] J Shi, B Chen and FX Wu. Improving accuracy of peptide identification with consistency between peptides. Bioinformatics and Biomedicine (BIBM), 2011 IEEE International Conference on, 191-196. (EI Compendex)[2] B Chen, L Liu and FX Wu. Inferring gene regulatory networks from multiple time course gene expression datasets. Systems Biology (ISB), 2011 IEEE International Conference on, 12-17. (EI Compendex)[1] B Chen. Topological patterns identification for sneak circuit analysis. Reliability, Maintainability and Safety, 2009, ICRMS 2009. 8th International Conference on, 133-137. (EI Compendex)
科学研究
学术活动 Professional Activities 2019.Nov.18-21 BIBM 2019 - International Conference on Bioinformatics and Biomedicine, San Diego, USA2018.Aug.23-25 CBC 2019 - Bioinformatics conference, Guangzhou, China2019.Aug.03-06 ICIC 2019 - International Conference on Intelligent Computing, Nanchang, China2019.Jun22-23 IDMB 2019 - International Conference on Data Science, Medicine, and Bioinformatics, Nanning, China2019.May.05-08 IWBBIO 2019 - International Work-Conference on Bioinformatics and Biomedical Engineering, Granada, Spain2018.Oct12-14 CBC 2018 - Bioinformatics conference, Xi'an, China2018.Aug.18-21 ISB 2018 - International Conference on Computational Systems Biology, Guiyang, China2018.Mar.04-08 Keystone Symposia 2018 - Manipulation of the gut microbiota for metabolic health, Canmore, Canada