Kendric Wang
Impact in
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- Cancer Genomics and Diagnostics
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- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- RNA modifications and cancer
- Gene Regulatory Network Analysis
- RNA Research and Splicing
Papers in
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- Epigenetics and DNA Methylation 2
- Bioinformatics and Genomic Networks 2
- Histone Deacetylase Inhibitors Research 2
- Gene expression and cancer classification 2
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- Prostate Cancer Treatment and Research 3
- Co-authors
- Colin C. Collins (6 shared papers)Phuong Dao (2 shared papers)Anna Lapuk (2 shared papers)Martin Ester (1 shared paper)S. Cenk Sahinalp (1 shared paper)Peter W. Gout (3 shared papers)Yuzhuo Wang (3 shared papers)Martin Gleave (2 shared papers)
- Journals
- Oncotarget (2 papers)Genome Research (1 paper)Molecular Oncology (1 paper)PLoS ONE (1 paper)Bioinformatics (1 paper)
- Partner nations
- CanadaUnited StatesAustralia
In The Last Decade
Kendric Wang
6 papers receiving 233 citations
Peers
Comparison fields: 5 of 58
- Cancer Research 55
- Molecular Biology 177
- Computational Theory and Mathematics 33
- Pulmonary and Respiratory Medicine 65
- Oncology 37
Countries citing papers authored by Kendric Wang
This map shows the geographic impact of Kendric Wang'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 Kendric Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kendric Wang more than expected).
Fields of papers citing papers by Kendric Wang
This network shows the impact of papers produced by Kendric Wang. 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 Kendric Wang. The network helps show where Kendric Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Kendric Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 73 | |
| 2 | 2014 | 48 | |
| 3 | 2014 | 44 | |
| 4 | 2017 | 35 | |
| 5 | 2013 | 28 | |
| 6 | 2014 | 8 |
About Kendric Wang
Kendric Wang is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Oncology, Computational Theory and Mathematics and Infectious Diseases, having authored 6 papers that have together received 236 indexed citations. Recurring topics across this work include Prostate Cancer Treatment and Research (3 papers), Epigenetics and DNA Methylation (2 papers), Bioinformatics and Genomic Networks (2 papers), Computational Drug Discovery Methods (2 papers), Histone Deacetylase Inhibitors Research (2 papers), Cancer-related Molecular Pathways (2 papers), Gene expression and cancer classification (2 papers) and Cancer Diagnosis and Treatment (1 paper). The work is most often cited by research in Cancer Research (55 citations), Molecular Biology (177 citations), Computational Theory and Mathematics (33 citations), Pulmonary and Respiratory Medicine (65 citations) and Oncology (37 citations). Kendric Wang has collaborated with scholars based in Canada, United States and Australia. Frequent co-authors include Colin C. Collins, Phuong Dao, Anna Lapuk, Martin Ester, S. Cenk Sahinalp, Peter W. Gout, Yuzhuo Wang, Martin Gleave, Ladan Fazli and Robert Z. Qi. Their work appears in journals such as Oncotarget, Genome Research, Molecular Oncology, PLoS ONE and Bioinformatics.
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.