D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 59 Citations 9,396 200 World Ranking 1602 National Ranking 151

Research.com Recognitions

Awards & Achievements

2015 - ACM Senior Member

Overview

What is he best known for?

The fields of study he is best known for:

  • Gene
  • Artificial intelligence
  • DNA

His scientific interests lie mostly in Artificial intelligence, Machine learning, Data mining, Web server and Support vector machine. He combines topics linked to Pattern recognition with his work on Artificial intelligence. His Machine learning study frequently draws connections between related disciplines such as Benchmark.

His research integrates issues of Dimensionality reduction and Evolutionary information in his study of Data mining. His study looks at the intersection of Web server and topics like Identification with RNA, Computational biology, Cellular differentiation, Stability and microRNA. He has researched Support vector machine in several fields, including Discriminative model and Pseudo amino acid composition.

His most cited work include:

  • Biological functions of microRNAs: a review (424 citations)
  • The Symbiodinium kawagutii genome illuminates dinoflagellate gene expression and coral symbiosis (270 citations)
  • A novel features ranking metric with application to scalable visual and bioinformatics data classification (248 citations)

What are the main themes of his work throughout his whole career to date?

Quan Zou spends much of his time researching Artificial intelligence, Machine learning, Computational biology, Data mining and Gene. His Artificial intelligence research includes elements of Web server and Pattern recognition. The Machine learning study combines topics in areas such as Representation, Benchmark and Identification.

His work in Computational biology tackles topics such as RNA which are related to areas like Sequence analysis. His is involved in several facets of Gene study, as is seen by his studies on microRNA and Gene expression. His microRNA study frequently intersects with other fields, such as Regulation of gene expression.

He most often published in these fields:

  • Artificial intelligence (45.51%)
  • Machine learning (33.44%)
  • Computational biology (30.03%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (45.51%)
  • Computational biology (30.03%)
  • Machine learning (33.44%)

In recent papers he was focusing on the following fields of study:

Artificial intelligence, Computational biology, Machine learning, Feature and Support vector machine are his primary areas of study. His work investigates the relationship between Artificial intelligence and topics such as Pattern recognition that intersect with problems in Reduction. His studies in Computational biology integrate themes in fields like RNA, Genome, Identification, DNA and Convolutional neural network.

He combines subjects such as Data mining and Sequencing data with his study of RNA. His study in Machine learning is interdisciplinary in nature, drawing from both Web server, Identification, Feature extraction and Benchmark. Quan Zou has researched Feature in several fields, including Ensemble forecasting and Peptide.

Between 2019 and 2021, his most popular works were:

  • Empirical comparison and analysis of web-based cell-penetrating peptide prediction tools (47 citations)
  • Predicting disease-associated circular RNAs using deep forests combined with positive-unlabeled learning methods. (38 citations)
  • Computational methods for identifying the critical nodes in biological networks. (30 citations)

In his most recent research, the most cited papers focused on:

  • Gene
  • Artificial intelligence
  • DNA

Quan Zou mainly focuses on Machine learning, Artificial intelligence, Computational biology, Web server and Identification. His Machine learning research includes themes of Sequencing data and Benchmark. His research on Artificial intelligence frequently links to adjacent areas such as Measure.

His Computational biology study integrates concerns from other disciplines, such as Identification, Feature, Genome and DNA. His research in Web server intersects with topics in Data mining, Sequence alignment, Particle swarm optimization, Extreme learning machine and Web application. The concepts of his Identification study are interwoven with issues in Overfitting, Robustness, Bacteria, Feature learning and Effector.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Biological functions of microRNAs: a review

Yong Huang;Xing Jia Shen;Quan Zou;Sheng Peng Wang.
Journal of Physiology and Biochemistry (2011)

591 Citations

The Symbiodinium kawagutii genome illuminates dinoflagellate gene expression and coral symbiosis

Senjie Lin;Senjie Lin;Shifeng Cheng;Shifeng Cheng;Bo Song;Xiao Zhong.
Science (2015)

329 Citations

A novel features ranking metric with application to scalable visual and bioinformatics data classification

Quan Zou;Jiancang Zeng;Liujuan Cao;Rongrong Ji.
Neurocomputing (2016)

312 Citations

Integrative approaches for predicting microRNA function and prioritizing disease-related microRNA using biological interaction networks

Xiangxiang Zeng;Xuan Zhang;Quan Zou.
Briefings in Bioinformatics (2016)

290 Citations

Inferring MicroRNA-Disease Associations by Random Walk on a Heterogeneous Network with Multiple Data Sources

Yuansheng Liu;Xiangxiang Zeng;Zengyou He;Quan Zou.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2017)

237 Citations

LibD3C: Ensemble classifiers with a clustering and dynamic selection strategy

Chen Lin;Wenqiang Chen;Cheng Qiu;Yunfeng Wu.
Neurocomputing (2014)

234 Citations

Similarity computation strategies in the microRNA-disease network: a survey

Quan Zou;Jinjin Li;Li Song;Xiangxiang Zeng.
Briefings in Functional Genomics (2015)

224 Citations

A comprehensive overview and evaluation of circular RNA detection tools.

Xiangxiang Zeng;Wei Lin;Maozu Guo;Quan Zou.
PLOS Computational Biology (2017)

224 Citations

Survey of MapReduce frame operation in bioinformatics

Quan Zou;Xu-Bin Li;Wen-Rui Jiang;Zi-Yu Lin.
Briefings in Bioinformatics (2014)

216 Citations

Predicting Diabetes Mellitus With Machine Learning Techniques.

Quan Zou;Kaiyang Qu;Yamei Luo;Dehui Yin.
Frontiers in Genetics (2018)

179 Citations

Editorial Boards

Current Bioinformatics
(Impact Factor: 4.85)

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Best Scientists Citing Quan Zou

Wei Chen

Wei Chen

North China University of Science and Technology

Publications: 81

Senjie Lin

Senjie Lin

University of Connecticut

Publications: 46

Kuo-Chen Chou

Kuo-Chen Chou

The Gordon Life Science Institute

Publications: 42

Jijun Tang

Jijun Tang

University of South Carolina

Publications: 29

Zhu-Hong You

Zhu-Hong You

Chinese Academy of Sciences

Publications: 29

Tao Huang

Tao Huang

Chinese Academy of Sciences

Publications: 25

Yu-Dong Cai

Yu-Dong Cai

Shanghai University

Publications: 23

Jiangning Song

Jiangning Song

Monash University

Publications: 23

Fang-Xiang Wu

Fang-Xiang Wu

University of Saskatchewan

Publications: 22

Xiaolong Wang

Xiaolong Wang

Chinese Academy of Sciences

Publications: 22

Leyi Wei

Leyi Wei

Shandong University

Publications: 21

Christian R. Voolstra

Christian R. Voolstra

University of Konstanz

Publications: 21

Jianxin Wang

Jianxin Wang

Central South University

Publications: 15

Yi Pan

Yi Pan

Shenzhen Institutes of Advanced Technology

Publications: 14

Xing Chen

Xing Chen

China University of Mining and Technology

Publications: 13

Mark A. Ragan

Mark A. Ragan

University of Queensland

Publications: 12

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