Kanix Wang
Impact in
- Ophthalmology top 10%
- Glaucoma and retinal disorders
- Retinal Diseases and Treatments
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- Toxoplasma gondii Research Studies
Papers in
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- Bioinformatics and Genomic Networks 2
- Machine Learning in Bioinformatics 1
- Biomedical Text Mining and Ontologies 1
- Genetics 4
- Genetic Associations and Epidemiology 2
- Genetic Mapping and Diversity in Plants and Animals 2
- Co-authors
- Andrey Rzhetsky (5 shared papers)Hoifung Poon (1 shared paper)Nancy J. Cox (2 shared papers)Hallie Gaitsch (1 shared paper)Christopher S. Lyttle (2 shared papers)Robert D. Gibbons (1 shared paper)Steven C. Bagley (1 shared paper)Edwin H. Cook (1 shared paper)
- Journals
- PLoS Computational Biology (2 papers)Nature Computational Science (1 paper)Nature Genetics (1 paper)Journal of the American Medical Informatics Association (1 paper)INFORMS journal on computing (1 paper)
- Partner nations
- United StatesJapanSaudi Arabia
In The Last Decade
Kanix Wang
7 papers receiving 250 citations
Peers
Comparison fields: 5 of 81
- Ophthalmology 45
- Parasitology 23
- Genetics 67
- Psychiatry and Mental health 28
- Cognitive Neuroscience 34
Countries citing papers authored by Kanix Wang
This map shows the geographic impact of Kanix 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 Kanix Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kanix Wang more than expected).
Fields of papers citing papers by Kanix Wang
This network shows the impact of papers produced by Kanix 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 Kanix Wang. The network helps show where Kanix Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Kanix 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 | 2017 | 154 | |
| 2 | 2014 | 41 | |
| 3 | 2016 | 28 | |
| 4 | 2012 | 16 | |
| 5 | 2014 | 10 | |
| 6 | 2023 | 4 | |
| 7 | 2021 | 3 | |
| 8 | 2024 | 0 |
About Kanix Wang
Kanix Wang is a scholar working on Molecular Biology, Genetics, Epidemiology, Artificial Intelligence and Infectious Diseases, having authored 8 papers that have together received 256 indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (2 papers), Genetic Mapping and Diversity in Plants and Animals (2 papers), Bioinformatics and Genomic Networks (2 papers), Attention Deficit Hyperactivity Disorder (1 paper), Machine Learning in Bioinformatics (1 paper), Natural Language Processing Techniques (1 paper), Child Nutrition and Feeding Issues (1 paper) and Biomedical Text Mining and Ontologies (1 paper). The work is most often cited by research in Ophthalmology (45 citations), Parasitology (23 citations), Genetics (67 citations), Psychiatry and Mental health (28 citations) and Cognitive Neuroscience (34 citations). Kanix Wang has collaborated with scholars based in United States, Japan and Saudi Arabia. Frequent co-authors include Andrey Rzhetsky, Hoifung Poon, Nancy J. Cox, Hallie Gaitsch, Christopher S. Lyttle, Robert D. Gibbons, Steven C. Bagley, Edwin H. Cook, Russ B. Altman and Ying Zhou. Their work appears in journals such as PLoS Computational Biology, Nature Computational Science, Nature Genetics, Journal of the American Medical Informatics Association and INFORMS journal on computing.
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.