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黄涛
Life Sciences
中国科学院大学
上海
Language: 中文, 英语
计算生物学
机器学习
生物医学大数据
网络分析
基因本体论
蛋白质相互作用
表观遗传学
精准医学
多组学
深度学习
Areas of Focus
- 计算生物学
- 生物医学大数据的机器学习
Work Experience
- 2022-11~现在 - 中国科学院上海营养与健康研究所 - 研究员
- 2014-11~2022-11 - 中国科学院上海营养与健康研究所 - 副研究员
- 2012-08~2014-08 - 美国纽约西奈山伊坎医学院 - 博士后
- 2007-09~2012-07 - 中国科学院上海生命科学研究院 - 博士
- 2003-09~2007-07 - 华中科技大学 - 学士
Academic Background & Achievements
- 2007-09--2012-07 博士: 中国科学院上海生命科学研究院
- 2003-09--2007-07 学士: 华中科技大学
Publications
- Analyzing domain features of small proteins using a machine-learning method, 黄涛, 2024
- Integrating multi-omics data of childhood asthma using a deep association model, 黄涛, 2024
- Identification of key genes associated with persistent immune changes and secondary immune activation responses induced by influenza vaccination after COVID-19 recovery by machine learning methods, 黄涛, 2024
- Identification of Protein-Protein Interaction Associated Functions Based on Gene Ontology, 黄涛, 2024
- Investigate the Epigenetic Connections of Obesity Between Mother and Child With Machine Learning Methods, 黄涛, 2023
- Seq-RBPPred: Predicting RNA-Binding Proteins from Sequence, 黄涛, 2023
- Anomaly Detection Models for SARS-CoV-2 Surveillance Based on Genome k-mers, 黄涛, 2023
- Analysis and prediction of protein stability based on interaction network, gene ontology, and KEGG pathway enrichment scores, 黄涛, 2023
- A cell marker-based clustering strategy (cmCluster) for precise cell type identification of scRNA-seq data, 黄涛, 2022
- Comparative analysis of NovaSeq 6000 and MGISEQ 2000 single-cell RNA sequencing data, 黄涛, 2022
- Computational Systems Biology: Methods and Protocols, 黄涛, 2018
- Precision Medicine, 黄涛, 2020
- Liquid Biopsies: Methods and Protocols, 黄涛, 2023
- Epigenetics - Regulation and New Perspectives, 黄涛, 2023
Awards
- 2023: 2023 Highly Cited Chinese Researchers, Elsevier
- 2023: Research.com Best Biology and Biochemistry Scientists in China, 328th
- 2022: Research.com Best Biology and Biochemistry Scientists in China, 350th
- 2022: 2022 Highly Cited Chinese Researchers, Elsevier
- 2022: World’s Top 2% Scientists, Stanford University
- 2021: 2021 Highly Cited Chinese Researchers, Elsevier
- 2021: World’s Top 2% Scientists, Stanford University
- 2020: The Top 25 Voices in Precision Medicine Asia
- 2020: 2020 Highly Cited Chinese Researchers, Elsevier
- 2020: World’s Top 2% Scientists, Stanford University
- 2019: Big Data Research Top Cited Articles Award Winner
