Madhavi Tippani
- Biophysics top 5%
- Cell Image Analysis Techniques 4
- Neurology top 10%
- Neuroinflammation and Neurodegeneration Mechanisms 5
- Biological Psychiatry top 10%
- Developmental Neuroscience top 10%
- Neurogenesis and neuroplasticity mechanisms 3
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- Single-cell and spatial transcriptomics 9
- RNA Research and Splicing 3
- Gene expression and cancer classification 3
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- Genetic Associations and Epidemiology 2
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- Memory and Neural Mechanisms 2
- Co-authors
- Kristen R. MaynardThomas M. HydeKeri MartinowichAndrew E. JaffeJoel E. KleinmanLeonardo Collado‐TorresStephanie C. HicksMatthew N. Tran
- Journals
- Nucleic Acids Research (1 paper)Neuron (1 paper)SHILAP Revista de lepidopterología (1 paper)
- Partner nations
- United StatesFranceJapan
In The Last Decade
Madhavi Tippani
16 papers receiving 771 citations
Hit Papers
Peers
Comparison fields: 5 of 92
- Biophysics 84
- Neurology 112
- Biological Psychiatry 32
- Developmental Neuroscience 44
- Molecular Biology 631
Countries citing papers authored by Madhavi Tippani
This map shows the geographic impact of Madhavi Tippani'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 Madhavi Tippani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Madhavi Tippani more than expected).
Fields of papers citing papers by Madhavi Tippani
This network shows the impact of papers produced by Madhavi Tippani. 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 Madhavi Tippani. The network helps show where Madhavi Tippani may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Madhavi Tippani, 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 | 2025 | 5 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 8 | |
| 5 | 2024 | 2 | |
| 6 | 2023 | 6 | |
| 7 | 2023 | 9 | |
| 8 | 2023 | 5 | |
| 9 | 2023 | 10 | |
| 10 | 2023 | 4 | |
| 11 | 2022 | 7 | |
| 12 | 2022 | 2 | |
| 13 | 2021 | 107 | |
| 14 | Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortexbreakdown → | 2021 | 557 |
| 15 | 2021 | 11 | |
| 16 | 2020 | 41 | |
| 17 | 2020 | 0 |
About Madhavi Tippani
Madhavi Tippani is a scholar working on Biophysics, Neurology and Developmental Neuroscience, having authored 17 papers that have together received 776 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (9 papers), Neuroinflammation and Neurodegeneration Mechanisms (5 papers), Cell Image Analysis Techniques (4 papers), RNA Research and Splicing (3 papers), Gene expression and cancer classification (3 papers), Neurogenesis and neuroplasticity mechanisms (3 papers), Genetic Associations and Epidemiology (2 papers) and Memory and Neural Mechanisms (2 papers). The work is most often cited by research in Biophysics (84 citations), Neurology (112 citations) and Biological Psychiatry (32 citations). Madhavi Tippani has collaborated with scholars based in United States, France and Japan. Frequent co-authors include Kristen R. Maynard, Thomas M. Hyde, Keri Martinowich, Andrew E. Jaffe, Joel E. Kleinman, Leonardo Collado‐Torres, Stephanie C. Hicks, Matthew N. Tran, Brianna K. Barry and Lukas M. Weber. Their work appears in journals such as Nucleic Acids Research, Neuron and SHILAP Revista de lepidopterología.
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.