K. Shanker
Impact in
- Cancer Research top 2%
- Cancer-related molecular mechanisms research
- Molecular Biology top 2%
- RNA modifications and cancer
- Epigenetics and DNA Methylation
- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Cancer-related gene regulation
- RNA Research and Splicing
Papers in
-
- Gene expression and cancer classification 3
- Bioinformatics and Genomic Networks 3
- Molecular Biology Techniques and Applications 2
- Genomics and Chromatin Dynamics 2
- Biomedical Text Mining and Ontologies 1
-
- Advanced Proteomics Techniques and Applications 1
- Co-authors
- Arul M. Chinnaiyan (2 shared papers)Debashis Ghosh (2 shared papers)Terrence R. Barrette (2 shared papers)Nandan Deshpande (3 shared papers)Jianjun Yu (2 shared papers)Daniel R. Rhodes (2 shared papers)Akhilesh Pandey (3 shared papers)J. Daniel Navarro (1 shared paper)
- Journals
- Neoplasia (1 paper)Gene (1 paper)Proceedings of the National Academy of Sciences (1 paper)BMC Bioinformatics (1 paper)
- Partner nations
- IndiaUnited StatesDenmark
In The Last Decade
K. Shanker
4 papers receiving 3.6k citations
K. Shanker's Hit Papers
Peers
Comparison fields: 5 of 107
- Cancer Research 1.0k
- Molecular Biology 2.8k
- Oncology 869
- Pulmonary and Respiratory Medicine 789
- Cell Biology 316
Countries citing papers authored by K. Shanker
This map shows the geographic impact of K. Shanker'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 K. Shanker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites K. Shanker more than expected).
Fields of papers citing papers by K. Shanker
This network shows the impact of papers produced by K. Shanker. 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 K. Shanker. The network helps show where K. Shanker may publish in the future.
Co-authors
The 14 scholars most cited alongside K. Shanker, 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 | ONCOMINE: A Cancer Microarray Database and Integrated Data-Mining Platform Hit paper breakdown → | 2004 | 2835 |
| 2 | Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression Hit paper breakdown → | 2004 | 789 |
| 3 | 2004 | 7 | |
| 4 | 2005 | 6 |
About K. Shanker
K. Shanker is a scholar working on Molecular Biology, Spectroscopy, Infectious Diseases, Organic Chemistry and Surgery, having authored 4 papers that have together received 3.6k indexed citations. Recurring topics across this work include Gene expression and cancer classification (3 papers), Bioinformatics and Genomic Networks (3 papers), Molecular Biology Techniques and Applications (2 papers), Genomics and Chromatin Dynamics (2 papers), Biomedical Text Mining and Ontologies (1 paper) and Advanced Proteomics Techniques and Applications (1 paper). The work is most often cited by research in Cancer Research (1.0k citations), Molecular Biology (2.8k citations), Oncology (869 citations), Pulmonary and Respiratory Medicine (789 citations) and Cell Biology (316 citations). K. Shanker has collaborated with scholars based in India, United States and Denmark. Frequent co-authors include Arul M. Chinnaiyan, Debashis Ghosh, Terrence R. Barrette, Nandan Deshpande, Jianjun Yu, Daniel R. Rhodes, Akhilesh Pandey, J. Daniel Navarro, Suraj Peri and Curt I. Civin. Their work appears in journals such as Neoplasia, Gene, Proceedings of the National Academy of Sciences and BMC 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.