其他博士生导师

黄涛
博士 青年研究员 博士生导师

中科院计算生物学重点实验室,计算基因组学和大数据课题组

研究方向:生物医学大数据的机器学习和网络分析

电子邮件(E-mail):huangtao@sibs.ac.cn

电话(Tel):54923269

简历
2020-至     今:中国科学院上海营养与健康研究所 青年研究员
2014-至     今:中国科学院上海生命科学研究院/上海营养与健康研究所 副研究员
2012-2014年:美国纽约西奈山伊坎医学院 博士后
2007-2012年:中国科学院上海生命科学研究院 生物信息学 博士
2003-2007年:华中科技大学 生物信息学 学士

研究内容
1. 可解释机器学习:采用机器学习的方法从生物医学大数据中提取关键特征和分类规则,发现复杂数据背后隐藏的逻辑规律,进而揭示生物学机制。
2. 多组学整合网络构建和分析:整合多组学数据构建调控网络,分析网络拓扑结构,发现关键调控因子。
3. 基于网络特征的机器学习:使用图嵌入等方法,对网络节点进行向量化表示,以基于网络的向量为特征进行机器学习。

代表性论文 (* 通讯作者)

  1. Ding S#, Wang D#, Zhou X#, Chen L, Feng K, Xu X, Huang T*, Li Z*, Cai Y*. Predicting Heart Cell Types by Using Transcriptome Profiles and a Machine Learning Method. Life 2022, 12(2):228.
  2. Shi X#, Zhang L#, Li Y#, Xue J, Liang F, Ni H-W, Wang X, Cai Z, Shen L, Huang T*, He B*. Integrative Analysis of Bulk and Single-Cell RNA Sequencing Data Reveals Cell Types Involved in Heart Failure. Frontiers in Bioengineering and Biotechnology 2021, 9:779225.
  3. Zhang H, Wang S*, Huang T*. Identification of Chronic Hypersensitivity Pneumonitis Biomarkers with Machine Learning and Differential Co-expression Analysis. Current Gene Therapy 2021, 21(4):299-303.
  4. Xu Y#, Liu X#, Cao X#, Huang C#, Liu E#, Qian S#, Liu X#, Wu Y, Dong F, Qiu CW, Qiu J, Hua K, Su W, Wu J, Xu H, Han Y, Fu C, Yin Z, Liu M, Roepman R, Dietmann S, Virta M, Kengara F, Zhang Z, Zhang L, Zhao T, Dai J, Yang J, Lan L, Luo M, Liu Z, An T, Zhang B, He X, Cong S, Liu X, Zhang W, Lewis J, Tiedje J, Wang Q*, An Z*, Wang F*, Zhang L*, Huang T*, Lu C*, Cai Z*, Wang F*, Zhang J*. Artificial intelligence: A powerful paradigm for scientific research. Innovation (New York, NY) 2021, 2(4):100179.
  5. Li T#, Huang T#, Guo C, Wang A, Shi X, Mo X, Lu Q, Sun J, Hui T, Tian G, Wang L*, Yang J*. Genomic Variation, Origin Tracing and Vaccine Development of SARS-CoV-2: A Systematic Review. Innovation (New York, NY) 2021, 2(2):100116.
  6. Ren X#, Wang S#, Huang T*. Decipher the connections between proteins and phenotypes. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics 2020, 1868(11):140503.
  7. Chen L, Pan X, Guo W, Gan Z, Zhang Y-H, Niu Z, Huang T*, Cai Y-D*. Investigating the gene expression profiles of cells in seven embryonic stages with machine learning algorithms. Genomics 2020, 112(3):2524-2534.
  8. Liu F#, Dong H#, Mei Z, Huang T*. Investigation of miRNA and mRNA co-expression network in ependymoma. Frontiers in Bioengineering and Biotechnology 2020, 8:177.
  9. Li J#, Lu L#, Zhang YH, Xu Y, Liu M, Feng K, Chen L, Kong X*, Huang T*, Cai YD*. Identification of leukemia stem cell expression signatures through Monte Carlo feature selection strategy and support vector machine. Cancer Gene Therapy 2020, 27(1):56-69.
  10. Chen L#, Pan X#, Zhang Y-H, Liu M, Huang T*, Cai Y-D*. Classification of widely and rarely expressed genes with recurrent neural network. Computational and Structural Biotechnology Journal 2019, 17:49-60.
  11. Ma Y-S#, Huang T#, Zhong X-M#, Zhang H-W#, Cong X-L, Xu H, Lu G-X, Yu F, Xue S-B, Lv Z-W, Fu D*. Proteogenomic characterization and comprehensive integrative genomic analysis of human colorectal cancer liver metastasis. Molecular Cancer 2018, 17(1):139.
  12. Shi X#, Huang T#, Wang J#, Liang Y, Gu C, Xu Y, Sun J, Lu Y, Sun K*, Chen S*, Yu Y*. Next-generation sequencing identifies novel genes with rare variants in total anomalous pulmonary venous connection. EBioMedicine 2018, 38:217-227.
  13. Cai L#*, Huang T#, Su J#, Zhang X, Chen W, Zhang F, He L*, Chou K-C. Implications of Newly Identified Brain eQTL Genes and Their Interactors in Schizophrenia. Molecular Therapy - Nucleic Acids 2018, 12:433-442.
  14. Li J, Huang T*. Predicting and analyzing early wake-up associated gene expressions by integrating GWAS and eQTL studies. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease 2018, 1864(6 Pt B):2241-2246.
  15. Liu C#, Zhang Y-H#, Huang T*, Cai Y*. Identification of transcription factors that may reprogram lung adenocarcinoma. Artificial Intelligence in Medicine 2017, 83:52-57.
  16. Zhang N#, Wang M#, Zhang P, Huang T*. Classification of cancers based on copy number variation landscapes. Biochimica et Biophysica Acta (BBA) - General Subjects 2016, 1860(11, Part B):2750-2755.
  17. Zhou Y, Wu K, Jiang J, Huang J, Zhang P, Zhu Y, Hu G, Lang J, Shi Y, Hu L, Huang T*, Kong X*. Integrative Analysis Reveals Enhanced Regulatory Effects of Human Long Intergenic Non-Coding RNAs in Lung Adenocarcinoma. Journal of Genetics and Genomics 2015, 42(8):423-436.
  18. Huang T#*, Wang M#, Cai Y-D*. Analysis of the preferences for splice codes across tissues. Protein & Cell 2015, 6(12):904-907.
  19. Huang T, Wang C, Zhang G, Xie L*, Li Y*. SySAP: a system-level predictor of deleterious single amino acid polymorphisms. Protein & Cell 2012, 3(1):38-43.
  20. Huang T, Chen L, Liu XJ*, Cai YD*. Predicting triplet of transcription factor - mediating enzyme - target gene by functional profiles. Neurocomputing 2011, 74(17):3677-3681.