V. M. Chinchilli
Impact in
- Oncology top 10%
- HER2/EGFR in Cancer Research
Papers in
-
- Reliability and Agreement in Measurement 2
- Advanced Statistical Process Monitoring 2
-
- Gene expression and cancer classification 1
- Co-authors
- A. Lipton (1 shared paper)Y A Teramoto (1 shared paper)H Harvey (1 shared paper)Kerstin Konrad (1 shared paper)Kim Leitzel (1 shared paper)Howard Grossberg (1 shared paper)L. Demers (1 shared paper)Jiang Luo (1 shared paper)
- Journals
- Clinical Chemistry (1 paper)Domestic Animal Endocrinology (1 paper)Diabetes (1 paper)Journal of Biopharmaceutical Statistics (1 paper)Biometrics (1 paper)
- Partner nations
- United StatesAustraliaGermany
In The Last Decade
V. M. Chinchilli
13 papers receiving 711 citations
Peers
Comparison fields: 5 of 88
- Oncology 223
- Behavioral Neuroscience 26
- Small Animals 51
- Genetics 151
- Cancer Research 71
Countries citing papers authored by V. M. Chinchilli
This map shows the geographic impact of V. M. Chinchilli'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 V. M. Chinchilli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites V. M. Chinchilli more than expected).
Fields of papers citing papers by V. M. Chinchilli
This network shows the impact of papers produced by V. M. Chinchilli. 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 V. M. Chinchilli. The network helps show where V. M. Chinchilli may publish in the future.
Co-authors
The 25 scholars most cited alongside V. M. Chinchilli, 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 | 1995 | 265 | |
| 2 | 2000 | 163 | |
| 3 | 2014 | 101 | |
| 4 | 2016 | 87 | |
| 5 | 2004 | 63 | |
| 6 | 1995 | 30 | |
| 7 | 2020 | 17 | |
| 8 | 1994 | 7 | |
| 9 | 1990 | 4 | |
| 10 | 2002 | 2 | |
| 11 | Robust analysis of within-unit variances in repeated measurement experiments. | 1997 | 1 |
| 12 | 2018 | 1 | |
| 13 | 1997 | 1 | |
| 14 | 2026 | 0 |
About V. M. Chinchilli
V. M. Chinchilli is a scholar working on Statistics, Probability and Uncertainty, Molecular Biology, Management Science and Operations Research, Genetics and Statistics and Probability, having authored 14 papers that have together received 742 indexed citations. Recurring topics across this work include Optimal Experimental Design Methods (3 papers), Reliability and Agreement in Measurement (2 papers), Statistical Methods in Clinical Trials (2 papers), Advanced Statistical Process Monitoring (2 papers), Advanced Statistical Methods and Models (2 papers), Human-Animal Interaction Studies (1 paper), Gene expression and cancer classification (1 paper) and Respiratory Support and Mechanisms (1 paper). The work is most often cited by research in Oncology (223 citations), Behavioral Neuroscience (26 citations), Small Animals (51 citations), Genetics (151 citations) and Cancer Research (71 citations). V. M. Chinchilli has collaborated with scholars based in United States, Australia and Germany. Frequent co-authors include A. Lipton, Y A Teramoto, H Harvey, Kerstin Konrad, Kim Leitzel, Howard Grossberg, L. Demers, Jiang Luo, Z Lin and Joanna Floros. Their work appears in journals such as Clinical Chemistry, Domestic Animal Endocrinology, Diabetes, Journal of Biopharmaceutical Statistics and Biometrics.
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.