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 43 Citations 6,117 171 World Ranking 3853 National Ranking 358

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Gene

Zhu-Hong You focuses on Artificial intelligence, Machine learning, Support vector machine, Cross-validation and Computational biology. His study ties his expertise on Pattern recognition together with the subject of Artificial intelligence. His Machine learning research includes themes of Drug target and Data mining.

The concepts of his Support vector machine study are interwoven with issues in Classifier, Topology, Protein–protein interaction, Protein sequencing and Gene regulatory network. His Cross-validation research incorporates elements of Colon neoplasm, Similarity, Bioinformatics and Disease Association. Biological network is closely connected to Disease in his research, which is encompassed under the umbrella topic of Computational biology.

His most cited work include:

  • Long non-coding RNAs and complex diseases: from experimental results to computational models (296 citations)
  • MicroRNAs and complex diseases: from experimental results to computational models. (214 citations)
  • Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis (204 citations)

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

His scientific interests lie mostly in Artificial intelligence, Machine learning, Classifier, Support vector machine and Computational biology. His Artificial intelligence research incorporates themes from Protein sequencing, Protein–protein interaction and Pattern recognition. His Machine learning research is multidisciplinary, relying on both Graph and Representation.

His research in Classifier focuses on subjects like Drug target, which are connected to Enzyme. His Support vector machine research includes themes of Autoencoder, Bioinformatics and Feature vector. His Computational biology research incorporates elements of microRNA, Gene, Disease and Cross-validation.

He most often published in these fields:

  • Artificial intelligence (62.86%)
  • Machine learning (39.59%)
  • Classifier (29.39%)

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

  • Artificial intelligence (62.86%)
  • Machine learning (39.59%)
  • Random forest (11.02%)

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

His main research concerns Artificial intelligence, Machine learning, Random forest, Computational biology and Disease. His biological study spans a wide range of topics, including Drug target and Pattern recognition. His study in Machine learning is interdisciplinary in nature, drawing from both Graph, Semantic similarity and Drug discovery.

His Random forest study incorporates themes from Node, Network embedding, Representation and Computational model. His research investigates the connection with Computational biology and areas like microRNA which intersect with concerns in Disease Association and Colon neoplasm. He focuses mostly in the field of Disease, narrowing it down to topics relating to Embedding and, in certain cases, Data mining.

Between 2019 and 2021, his most popular works were:

  • Combining High Speed ELM Learning with a Deep Convolutional Neural Network Feature Encoding for Predicting Protein-RNA Interactions (20 citations)
  • An efficient approach based on multi-sources information to predict circRNA–disease associations using deep convolutional neural network (13 citations)
  • iCDA-CGR: Identification of circRNA-disease associations based on Chaos Game Representation. (12 citations)

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

  • Artificial intelligence
  • Machine learning
  • Gene

Zhu-Hong You spends much of his time researching Artificial intelligence, Machine learning, Computational biology, Classifier and Disease. With his scientific publications, his incorporates both Artificial intelligence and Stacking. His Kernel study, which is part of a larger body of work in Machine learning, is frequently linked to Reductionism, bridging the gap between disciplines.

His Computational biology research is multidisciplinary, incorporating perspectives in Random forest and microRNA. His biological study deals with issues like Semantic similarity, which deal with fields such as Autoencoder and Support vector machine. His work deals with themes such as Circular RNA, Graph embedding and Source code, which intersect with Disease.

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

Long non-coding RNAs and complex diseases: from experimental results to computational models

Xing Chen;Chenggang Clarence Yan;Xu Zhang;Zhu-Hong You.
Briefings in Bioinformatics (2016)

368 Citations

MicroRNAs and complex diseases: from experimental results to computational models.

Xing Chen;Di Xie;Qi Zhao;Zhu-Hong You.
Briefings in Bioinformatics (2019)

253 Citations

Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis

Zhu-Hong You;Ying-Ke Lei;Lin Zhu;Junfeng Xia.
BMC Bioinformatics (2013)

246 Citations

PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction.

Zhu-Hong You;Zhi-An Huang;Zexuan Zhu;Gui-Ying Yan.
PLOS Computational Biology (2017)

243 Citations

WBSMDA: Within and Between Score for MiRNA-Disease Association prediction.

Xing Chen;Chenggang Clarence Yan;Chenggang Clarence Yan;Xu Zhang;Zhu-Hong You.
Scientific Reports (2016)

240 Citations

A Nonnegative Latent Factor Model for Large-Scale Sparse Matrices in Recommender Systems via Alternating Direction Method

Xin Luo;MengChu Zhou;Shuai Li;Zhuhong You.
IEEE Transactions on Neural Networks (2016)

208 Citations

Using manifold embedding for assessing and predicting protein interactions from high-throughput experimental data

Zhu-Hong You;Ying-Ke Lei;Jie Gui;De-Shuang Huang.
Bioinformatics (2010)

198 Citations

BNPMDA: Bipartite Network Projection for MiRNA-Disease Association prediction.

Xing Chen;Di Xie;Lei Wang;Qi Zhao.
Bioinformatics (2018)

179 Citations

HGIMDA: Heterogeneous graph inference for miRNA-disease association prediction

Xing Chen;Chenggang Clarence Yan;Xu Zhang;Zhu-Hong You.
Oncotarget (2016)

166 Citations

IRWRLDA: improved random walk with restart for lncRNA-disease association prediction.

Xing Chen;Zhu-Hong You;Gui-Ying Yan;Dun-Wei Gong.
Oncotarget (2016)

138 Citations

Best Scientists Citing Zhu-Hong You

Shuai Li

Shuai Li

Rutgers, The State University of New Jersey

Publications: 64

Xin Luo

Xin Luo

Chinese Academy of Sciences

Publications: 52

MengChu Zhou

MengChu Zhou

New Jersey Institute of Technology

Publications: 41

Xing Chen

Xing Chen

China University of Mining and Technology

Publications: 40

De-Shuang Huang

De-Shuang Huang

Tongji University

Publications: 28

Jijun Tang

Jijun Tang

University of South Carolina

Publications: 25

Quan Zou

Quan Zou

University of Electronic Science and Technology of China

Publications: 24

Fang-Xiang Wu

Fang-Xiang Wu

University of Saskatchewan

Publications: 20

Jianqiang Li

Jianqiang Li

Beijing University of Technology

Publications: 17

Jianxin Wang

Jianxin Wang

Central South University

Publications: 16

Jiangning Song

Jiangning Song

Monash University

Publications: 15

Dong-Qing Wei

Dong-Qing Wei

Shanghai Jiao Tong University

Publications: 13

Qinghua Cui

Qinghua Cui

Peking University

Publications: 12

Xiangxiang Zeng

Xiangxiang Zeng

Hunan University

Publications: 11

Bin Liu

Bin Liu

Nanjing University

Publications: 9

Xiaoli Li

Xiaoli Li

Agency for Science, Technology and Research

Publications: 8

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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