宁乔 教学系   数据科学与大数据技术教学系
  • 专业技术职务:
  • 行政职务:
  • 研究方向:机器学习,生物信息学
  • 学位:博士
  • 联系方式:
  • 电子邮箱:
个人资料
  • 性别:
  • 部门: 教学系
  • 民族: 汉族
  • 专业技术职务:
  • 行政职务:
  • 研究方向: 机器学习,生物信息学
  • 毕业院校: 东北师范大学
  • 学位: 博士
  • 政治面貌: 群众
  • 联系电话: 13578767143
  • 电子邮箱: ningq669@dlmu.edu.cn
  • 办公地址:
  • 通信地址:
  • 传真:
  • 邮编: 116026
教育经历 2010.09-2014.07 东北师范大学 计算机科学与技术专业 本科
2014.09-2016.07 东北师范大学 计算机应用技术专业 硕士
2017.11-2018.11 美国加州大学旧金山分校 生物化学与生物物理专业 联合培养博士
2016.09-2020.01 东北师范大学 智能环境分析与规划专业 博士
工作经历

研究领域 主要研究方向为:机器学习,生物信息学,数据挖掘等,并在该研究领域发表SCI期刊论文十余篇。

序号 论文题目 刊物或会议 发表时间 检索情况 作者
1 Analysis and Prediction of Human Acetylation using a Cascade Classifier based on Support Vector Machine. BMC bioinformatics 2019 SCI 1/5
2 dForml(KNN)-PseAAC: Detecting Formylation sites from protein sequences using K-nearest neighbor algorithm via Chou's 5-step rule and Pseudo components. Journal of Theoretical Biology 2019 SCI 1/3
3 Identifying N6-methyladenosine sites using extreme gradient boosting system optimized by particle swarm optimizer. Journal of Theoretical Biology 2019 SCI 3/6
4 Detecting Succinylation sites from protein sequences using ensemble support vector machine. BMC bioinformatics 2018 SCI 1/5
5 An Improved Binary Differential Evolution Algorithm for Feature Selection in Molecular Signatures. Molecular Informatics 2017 SCI 3/5
6 Identification of S-glutathionylation sites in species-specific proteins by incorporating five sequence-derived features into the general pseudo-amino acid composition. Journal of Theoretical Biology 2016 SCI 2/5
7 PGlcS: Prediction of protein O-GlcNAcylation sites with multiple features and analysis. Journal of Theoretical Biology 2015 SCI 2/5
8 Accurate in silico identification of protein succinylation sites using an iterative semi-supervised learning technique. Journal of Theoretical Biology 2015 SCI 2/4
9 PGluS: prediction of protein S-glutathionylation sites with multiple features and analysis. Molecular Biosystem 2015 SCI 2/5
10 Position-Specific Analysis and Prediction of Protein Pupylation Sites Based on Multiple Features. Biomed Research International 2013 SCI 3/5
11 Identification of Protein Pupylation Sites Using Bi-Profile Bayes Feature Extraction and Ensemble Learning. Mathematical Problems in Engineering 2013 SCI 3/6
12 A Novel Framework Based on ACO and PSO for RNA Secondary Structure Prediction. Mathematical Problems in Engineering 2013 SCI 3/4
13 Bioinformatics resources and tools for conformational B-cell epitope prediction. Computational & Mathematical Methods in Medicine 2013 SCI 4/9

版权所有©大连海事大学信息技术学院