Maya Palnitkar
Impact in
- Molecular Medicine top 5%
- Antibiotic Resistance in Bacteria
- Genetics top 5%
- Bacterial Genetics and Biotechnology
Papers in
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- DNA Repair Mechanisms 1
- Plant biochemistry and biosynthesis 1
- Mitochondrial Function and Pathology 1
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- Thyroid Disorders and Treatments 3
- Growth Hormone and Insulin-like Growth Factors 2
- Co-authors
- J. Deisenhofer (6 shared papers)Susan K. Buchanan (2 shared papers)Barbara Smith (2 shared papers)Eva S. Istvan (1 shared paper)Mischa Machius (2 shared papers)Lalitha Venkatramani (1 shared paper)Ranjan Chakraborty (1 shared paper)Lothar Esser (1 shared paper)
- Journals
- Proceedings of the National Academy of Sciences (3 papers)Advances in experimental medicine and biology (1 paper)Thyroid (1 paper)The EMBO Journal (1 paper)Neuroendocrinology (1 paper)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Maya Palnitkar
9 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 106
- Molecular Medicine 93
- Genetics 314
- Endocrine and Autonomic Systems 65
- Molecular Biology 696
- Cellular and Molecular Neuroscience 153
Countries citing papers authored by Maya Palnitkar
This map shows the geographic impact of Maya Palnitkar'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 Maya Palnitkar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maya Palnitkar more than expected).
Fields of papers citing papers by Maya Palnitkar
This network shows the impact of papers produced by Maya Palnitkar. 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 Maya Palnitkar. The network helps show where Maya Palnitkar may publish in the future.
Co-authors
The 23 scholars most cited alongside Maya Palnitkar, 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 | 1999 | 475 | |
| 2 | 2000 | 260 | |
| 3 | 2004 | 249 | |
| 4 | 1999 | 87 | |
| 5 | 2010 | 63 | |
| 6 | 2011 | 48 | |
| 7 | 1991 | 47 | |
| 8 | 1991 | 17 | |
| 9 | 2008 | 7 |
About Maya Palnitkar
Maya Palnitkar is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Cancer Research, Materials Chemistry and Surgery, having authored 9 papers that have together received 1.3k indexed citations. Recurring topics across this work include Thyroid Disorders and Treatments (3 papers), Enzyme Structure and Function (2 papers), Growth Hormone and Insulin-like Growth Factors (2 papers), Cancer, Hypoxia, and Metabolism (2 papers), DNA Repair Mechanisms (1 paper), Plant biochemistry and biosynthesis (1 paper), Mitochondrial Function and Pathology (1 paper) and Neuroscience and Neuropharmacology Research (1 paper). The work is most often cited by research in Molecular Medicine (93 citations), Genetics (314 citations), Endocrine and Autonomic Systems (65 citations), Molecular Biology (696 citations) and Cellular and Molecular Neuroscience (153 citations). Maya Palnitkar has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include J. Deisenhofer, Susan K. Buchanan, Barbara Smith, Eva S. Istvan, Mischa Machius, Lalitha Venkatramani, Ranjan Chakraborty, Lothar Esser, Dick Van der Helm and Chad A. Brautigam. Their work appears in journals such as Proceedings of the National Academy of Sciences, Advances in experimental medicine and biology, Thyroid, The EMBO Journal and Neuroendocrinology.
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.