Xing-Ming Zhao

975 total citations
27 papers, 705 citations indexed

About

Xing-Ming Zhao is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Xing-Ming Zhao has authored 27 papers receiving a total of 705 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 7 papers in Computational Theory and Mathematics and 4 papers in Artificial Intelligence. Recurrent topics in Xing-Ming Zhao's work include Bioinformatics and Genomic Networks (8 papers), Computational Drug Discovery Methods (7 papers) and Machine Learning in Bioinformatics (4 papers). Xing-Ming Zhao is often cited by papers focused on Bioinformatics and Genomic Networks (8 papers), Computational Drug Discovery Methods (7 papers) and Machine Learning in Bioinformatics (4 papers). Xing-Ming Zhao collaborates with scholars based in China, United Kingdom and Japan. Xing-Ming Zhao's co-authors include Luonan Chen, Minghui Wang, Yu Liu, Ao Li, Xiaoping Liu, Béatrice Duval, Jin‐Kao Hao, Rui Liu, Xiujun Zhang and Keqin Liu and has published in prestigious journals such as Bioinformatics, PLoS ONE and Cell Death and Differentiation.

In The Last Decade

Xing-Ming Zhao

27 papers receiving 699 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Xing-Ming Zhao China 12 576 116 113 40 32 27 705
Natalja Kurbatova United Kingdom 7 530 0.9× 90 0.8× 79 0.7× 67 1.7× 49 1.5× 11 679
Dong Yue Canada 4 462 0.8× 73 0.6× 74 0.7× 36 0.9× 56 1.8× 6 695
Sven Heinicke United States 4 717 1.2× 136 1.2× 57 0.5× 84 2.1× 35 1.1× 4 814
Onur Sumer Canada 3 410 0.7× 73 0.6× 55 0.5× 33 0.8× 50 1.6× 3 603
Peter Gennemark Sweden 15 714 1.2× 109 0.9× 62 0.5× 62 1.6× 46 1.4× 55 1.2k
Yuexu Jiang United States 13 739 1.3× 51 0.4× 111 1.0× 40 1.0× 62 1.9× 35 995
Hao Dai China 14 443 0.8× 117 1.0× 56 0.5× 21 0.5× 38 1.2× 40 654
Alexander Mazein Luxembourg 13 636 1.1× 70 0.6× 55 0.5× 34 0.8× 15 0.5× 29 813
Phani Garapati United Kingdom 3 570 1.0× 109 0.9× 69 0.6× 81 2.0× 9 0.3× 4 698
Xiaohong Jing United States 14 515 0.9× 101 0.9× 244 2.2× 66 1.6× 25 0.8× 24 898

Countries citing papers authored by Xing-Ming Zhao

Since Specialization
Citations

This map shows the geographic impact of Xing-Ming Zhao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xing-Ming Zhao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xing-Ming Zhao more than expected).

Fields of papers citing papers by Xing-Ming Zhao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xing-Ming Zhao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xing-Ming Zhao. The network helps show where Xing-Ming Zhao may publish in the future.

Co-authorship network of co-authors of Xing-Ming Zhao

This figure shows the co-authorship network connecting the top 25 collaborators of Xing-Ming Zhao. A scholar is included among the top collaborators of Xing-Ming Zhao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xing-Ming Zhao. Xing-Ming Zhao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Shi, Kai, et al.. (2024). MicroHDF: predicting host phenotypes with metagenomic data using a deep forest-based framework. Briefings in Bioinformatics. 25(6). 3 indexed citations
2.
Wang, Minghui, et al.. (2018). DeepPhos: prediction of protein phosphorylation sites with deep learning. Bioinformatics. 35(16). 2766–2773. 139 indexed citations
3.
Wang, Yin‐Ying, et al.. (2016). A Survey on Computational Approaches to Predicting Adverse Drug Reactions. Current Topics in Medicinal Chemistry. 16(30). 3629–3635. 7 indexed citations
4.
Lee, Ji‐Hyun, Xing-Ming Zhao, Ina Yoon, et al.. (2016). Integrative analysis of mutational and transcriptional profiles reveals driver mutations of metastatic breast cancers. Cell Discovery. 2(1). 16025–16025. 62 indexed citations
5.
Han, Yang & Xing-Ming Zhao. (2016). A hybrid sequential feature selection approach for the diagnosis of Alzheimer's Disease. 1216–1220. 5 indexed citations
6.
Qin, Guimin, et al.. (2015). Inferring the miRNA-disease associations based on domain-disease associations. IFAC-PapersOnLine. 48(28). 7–11. 2 indexed citations
7.
Liu, Zexian, Yudong Cai, Xuejiang Guo, et al.. (2015). [Post-translational modification (PTM) bioinformatics in China: progresses and perspectives].. PubMed. 37(7). 621–34. 3 indexed citations
8.
Zhao, Xing-Ming, Guanghui Zhu, Béatrice Duval, et al.. (2014). Identifying cancer-related microRNAs based on gene expression data. Bioinformatics. 31(8). 1226–1234. 73 indexed citations
9.
Liu, Xiaoping, Rui Liu, Xing-Ming Zhao, & Luonan Chen. (2013). Detecting early-warning signals of type 1 diabetes and its leading biomolecular networks by dynamical network biomarkers. BMC Medical Genomics. 6(S2). S8–S8. 72 indexed citations
10.
Wang, Haiying, Huiru Zheng, Francisco Azuaje, & Xing-Ming Zhao. (2013). Drug-Domain Interaction Networks in Myocardial Infarction. IEEE Transactions on NanoBioscience. 12(3). 182–188. 2 indexed citations
11.
Wang, Yin‐Ying, Jose C. Nacher, & Xing-Ming Zhao. (2012). Predicting drug targets based on protein domains. Molecular BioSystems. 8(5). 1528–1534. 26 indexed citations
12.
Wang, Jiao, et al.. (2012). A systems biology approach to identify the signalling network regulated by Rho-GDI-γ during neural stem cell differentiation. Molecular BioSystems. 8(11). 2916–2923. 5 indexed citations
13.
Wang, Haiying, Huiru Zheng, Francisco Azuaje, & Xing-Ming Zhao. (2012). Drug-target network in myocardial infarction: A structural analysis. 22. 1–4. 1 indexed citations
14.
Zhao, Xing-Ming, et al.. (2010). ANALYSIS OF GENE EXPRESSION DATA USING RPEM ALGORITHM IN NORMAL MIXTURE MODEL WITH DYNAMIC ADJUSTMENT OF LEARNING RATE. International Journal of Pattern Recognition and Artificial Intelligence. 24(4). 651–666. 7 indexed citations
15.
Xia, Junfeng, et al.. (2010). Prediction of β-Hairpins in Proteins Using Physicochemical Properties and Structure Information. Protein and Peptide Letters. 17(9). 1123–1128. 10 indexed citations
16.
Liu, Xiaoping, Weihua Tang, Xing-Ming Zhao, & Luonan Chen. (2010). A Network Approach to Predict Pathogenic Genes for Fusarium graminearum. PLoS ONE. 5(10). e13021–e13021. 39 indexed citations
17.
18.
Gan, Yu, et al.. (2008). HCCS1 overexpression induces apoptosis via cathepsin D and intracellular calcium, and HCCS1 disruption in mice causes placental abnormality. Cell Death and Differentiation. 15(9). 1481–1490. 17 indexed citations
19.
Zhao, Xing-Ming, et al.. (2005). A Novel Markov Pairwise Protein Sequence Alignment Method for Sequence 665 Comparison. Protein and Peptide Letters. 12(7). 665–669. 1 indexed citations
20.
Zhao, Xing-Ming, et al.. (2005). A Novel Hybrid GA/RBFNN Technique for Protein Sequences Classification. Protein and Peptide Letters. 12(4). 383–386. 10 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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